text:
From Publishers Weekly
This gripping first book introduces a secondary world impressive in depth and believability, complete with shadowy assassin guilds and prophecies of the walking dead. Intricate religious and political beliefs lend depth to a mature sword-and-sorcery context. Grimbert revitalizes the traditional heroic quest with believable characters, political intrigue, and fizzling gender tension. This adult fairytale hides profound truths in enchanting archetypes and should satisfy fans of both epic fantasy and suspense.-Publishers Weekly (starred review)
– Tor.com


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Jackson County
Linda Luedeman, 201 N. Armstrong St., Crothersville, 10-by-30 addition to building, filed Oct. 4.
Willard E. Fleetwood, 12683 E. County Road 1000N, Seymour, variance from 50-foot strip of ground to 30-foot strip of ground for a new residence, filed Oct. 4.
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subset: commoncrawl


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Associate Professor of Fashion
Sheila Johnson Design Center
Steven Faerm is an Associate Professor of Fashion Design at Parsons School of Design (Program Director, BFA Fashion Design, 2007-2011). A Parsons alumnus (94') and Designer of the Year Nominee, he began teaching in 1998 while working for such designers as Marc Jacobs and Donna Karan. He has been recognized for his teaching by winning "The University Distinguished Teaching Award" and The BFA Fashion Design Program's "Teaching Excellence Award."
Steven has created college- and pre-college programs and courses for Parsons and other international institutions, and has served as a consultant for Rhode Island School of Design, Pratt Institute, and Otis College of Art and Design. He has taught and lectured for such institutions as Harvard University, Massachusetts Institute of Technology (MIT), Brown University, Donghua University in Shanghai, The University of Palermo (UP) in Buenos Aires, and The Spero Villioti School in South Africa. Since 2012, he has co-produced an annual academic journal dedicated to fashion education with UP.
His publications include two books that are featured on international college-level required reading lists and available in seven languages: Fashion Design Course: Principles Practices, and Techniques (2010) and Creating a Successful Fashion Collection: Everything You Need to Develop a Great Line and Portfolio (2012). He is currently writing a third book about fashion design education and pedagogy, while continuing to produce papers for academic journals and serving as a consultant for three publishing houses.
Areas of scholarship and research included the future of fashion design education, pedagogy, and student development.
EdM Harvard University Graduate School of Education
MSEd Bank Street College of Education
BFA Parsons School of Design
Faerm, S. (2012). Creating a successful fashion collection: Everything you need to develop a great line and portfolio. New York: Barron's Educational Series Inc; London: A & C Black Publishers, Ltd.
Faerm, S. (2010). Fashion design course: Principles, practice, and techniques: The Practical Guide for Aspiring Fashion Designers. New York: Barron's Educational Series Inc.; London: Thames and Hudson.
Palomo-Lovinski, N. & Faerm, S. (2014). Shifting ideas of time and place in fashion. Shapeshifting: A Conference on Transformative Paradigms of Fashion and Textile Design.
Faerm, S. (2014). Building best practices for fashion design pedagogy: Meaning, preparation, and impact. Cuaderno, 53, 189-213.
Fry, A. & Faerm, S. (2014). Post-recession consumerism in the U.S.: The influence of cheap and chic consumer products on perceptions of Income Inequality. Cuaderno, 53, 169-188.
Faerm, S. (2013). From classroom to design room: The transitional experience of the fashion design graduate. Cuaderno, 48, 129-152. Buenos Aires, Argentina: The University of Palermo.
Fry, A., Arakji, R., & Faerm, S. (2013). Achieving the new graduate dream: Building sustainable business success at a small scale. Cuaderno, 48,153-175. Buenos Aires, Argentina: The University of Palermo.
Faerm, S. (2012). Towards a future pedagogy: The evolution of fashion design education. International Journal of Humanities and Social Science, 2 (23), 210-219.
Palomo-Lovinski, N. & Faerm, S. (2009). What is good design?: The shifts in fashion education of the 21st Century. Design Principles and Practices: An International Journal, 3 (6), 89-98.
Faerm, S. (2014). A Dodging The Higher Ed. Crisis: College Tuition, Student Loans, and How Course Hybridization Can Help. M / I / S / C / Magazine Online.
Faerm, S. (2013). A More Responsive and Responsible Design Education. M / I / S / C / Magazine Online.
Faerm, S. (2013). Why Art and Design Higher Education Needs Advanced Pedagogy. M / I / S / C / Magazine Online.
Faerm, S. (2013). Foreword. In Fitzgerald, T. & Taylor, A., 1,000 Dresses: The Fashion Design Resource. New York: Barron's Educational Series Inc.
Faerm, S. (2013). Finding Aesthetic Inspiration in a Commodity Driven World. M / I / S / C / Magazine.
Faerm, S. (2013). Foreword. In F. Knop (Ed.), Journal of the Center for Studies in Design and Communications: Multidisciplinary Approaches on the Fashion System, 48, 107-111. Buenos Aires: University of Palermo.
Faerm, S. (2009). Foreword. In Grandon, A. & Fitzgerald, T., 200 Projects to Get You Into Fashion Design. New York: Barron's Educational Series Inc.; London: A & C Black Publishers, Ltd.
pedagogy, design education, student development, fashion design, fashion industry, young adult development, fashion theory, education, international educational entrepreneurship
The Faculty Award (2011)
The University Distinguished Teaching Award (2008)
Designer of the Year Nominee (1994)
Fashion Portfolio
Fashion and the Narrative
Design Studio 3


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i can only connect my server by ssh,none web browser and other GUI tools.
migrated from stackoverflow.com Dec 23 '11 at 5:42
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closed as not a real question by mailq, Iain, Shane Madden♦, Mircea Vutcovici, splattne Dec 24 '11 at 12:37
It's difficult to tell what is being asked here. This question is ambiguous, vague, incomplete, overly broad, or rhetorical and cannot be reasonably answered in its current form. For help clarifying this question so that it can be reopened, visit the help center.If this question can be reworded to fit the rules in the help center, please edit the question.
If you want to import the certificates in apache web server, then you need to configure in the SSL Virtualhost the SSLCertificateChainFile option.


text:
Zee Two Joey Toddler Seat Review
by Hollie at BabyGizmo.com
Valco Baby now has an innovative NEW lightweight option for those parents with twins plus toddler, multiples or 3 young children -- the Zee Two & Joey Toddler Seat. The all purpose, compact fold Zee Two Stroller can now take a Joey seat and transform from a double to a triple stroller comfortably accommodating 3 children.
Hollie Schultz , the baby gear expert from Baby Gizmo (who previously reviewed the Zee Two Stroller) has video reviewed & approved the NEW Joey Toddler Seat for the Zee Two Stroller.
Here's a little taste of the review "Toddlers love it because when they sit in here they sit up high, they can see everything, its a really great seat for the front guy. Now its easy to install and let me tell you its very secure on the stroller, you don't have to worry about any tipping hazards...!"
Watch the full review from BabyGizmo.com
Snap Ultra ~ Valco Baby Lightweight Stroller Review 2015
by The Car Crash Detective more>>
O' Snap, a Snap Duo Double Stroller Review
featured on 'As the Stroller Turns' more>>
Stroller Options for Twins Plus One
by Busy Mommy Mediamore>>
Valco Baby Snap Ultra Stroller Review
by Mom's Stroller Reviews more>>


text:
|Publication number
|Publication type
|Application number
|Publication date
|Apr 17, 2007
|Filing date
|May 10, 2000
|Priority date
|May 10, 2000
|Fee status
|Also published as
|Publication number
|Albert S. Feng, Douglas Jones, Bruce C. Wheeler, Robert C. Bilger, Charissa R. Lansing, William D. O'Brien
|Original Assignee
|Board Of Trustees Of University Of Illinois
|Export Citation
|BiBTeX, EndNote, RefMan
|Patent Citations (70), Non-Patent Citations (6), Referenced by (121), Classifications (9), Legal Events (3)
|External Links: USPTO, USPTO Assignment, Espacenet
The present application is related to U.S. patent application Ser. No. 08/666,757 filed 19 Jun. 1996, U.S. patent application Ser. No. 09/193,058 filed 16 Nov. 1998, and the U.S. Patent Application entitled "Interference Suppression Techniques" and filed on even date herewith, all of which are hereby incorporated by reference.
The present invention relates to acoustic signal processing, and more particularly, but not exclusively, relates to communication between components of a hearing aid.
The difficulty of extracting a desired sound in the presence of interfering sound sources is a long-standing problem. Especially troublesome is the separation of desired sound from unwanted sound with hearing aids. Generally, such devices do not permit selective amplification of a desired sound when contaminated by noise from a nearby source—particularly when the noise is more intense. This problem is even more severe when the desired sound emanates from a selected speaker and the nearby noise is produced by several talkers.
One technique to address such problems is a hearing aid system that includes two or more components worn by a user in different locations. During operation, it is generally desirable that one or more communication links be established between these components using wireless interconnect technology. Interconnecting these components by wires or cables to facilitate communication is greatly undesirable. Furthermore, communication through the transmission of electromagnetic signals through the air also has certain drawbacks, such as the potential for interference by stray signals and the difficulty of incorporating the necessary transmission and reception circuits into a device of a size that can be comfortably worn by the user.
Thus, there continues to be a demand for further contributions in this area of technology.
One form of the present invention includes a unique hearing aid system. Other forms include unique devices and methods for processing and communicating signals for a hearing aid. Further forms, embodiments, objects, features, aspects, benefits, and advantages of the present invention shall become apparent from the detailed drawings and descriptions provided herein.
In the following figures, like reference numerals represent like features. In some cases, the figures or selected features thereof are not drawn to scale to enhance clarity.
While the present invention may be embodied in many different forms, for the purpose of promoting an understanding of the principles of the invention, reference will now be made to the embodiments illustrated in the drawings and specific language will be used to describe the same. It will nevertheless be understood that no limitation of the scope of the invention is thereby intended. Any alterations and further modifications in the described embodiments, and any further applications of the principles of the invention as described herein are contemplated as would normally occur to one skilled in the art to which the invention relates.
Acoustic I/O components 30 a, 30 b are each disposed in a corresponding passage of the ears E1, E2 of user 21, and include acoustic sensors 22 a, 22 b opposing earphones 24 a, 24 b, respectively. Acoustic sensors 22 a and 22 b collectively form acoustic sensing array 22. In one embodiment, acoustic sensors 22 a, 22 b are omnidirectional dynamic microphones. In other embodiments, a different type of microphone or sensor type can be utilized as would occur to one skilled in the art. Acoustic I/O components 30 a, 30 b also each include a pair of signal conductors 33 that are alternatively designated electrode pairs 33 a, 33 b, respectively (shown in phantom).
Processing component 30 c also includes a pair of conductors 33 alternatively designated electrode pair 33 c (also shown in phantom). Processing component 30 c is worn outside ears E1, E2 on the wrist of user 21, and resembles a common wrist watch device.
Referring additionally to
Each acoustic signal input/output component 30 a, 30 b includes input (I/P) circuitry 34 coupled to a respective acoustic sensor 22 a, 22 b and output (O/P) circuitry 35 coupled to a respective earphone 24 a, 24 b. The input circuitry 34 is further coupled to a corresponding transmitter circuit (TXR) 36. For each acoustic I/O component 30 a, 30 b, input circuitry 34 conditions signals received from the respective acoustic sensor 22 a, 22 b for transmission by the transmitter 36 coupled thereto. In one embodiment, input circuitry 34 includes filtering, amplification, and an analog-to-digital (A/D) converter to provide a signal to transmitter 36 in a desired digital format. For this embodiment, transmitter 36 can be arranged to modulate digital input from input circuitry 34 using pulse code modulation (PCM), pulse amplitude modulation (PAM) such as a frequency-shift-keying (FSK) technique, or a different digital communication scheme as would occur to those skilled in the art.
In another embodiment, input circuitry 34 is configured to transmit an analog signal representative of acoustic excitation detected by the respective acoustic sensor 22 a or 22 b. For this embodiment, transmitter 36 can be configured to transmit signals in a frequency modulated (FM) form or other analog communication format as would occur to those skilled in the art. In still other embodiments, input circuitry 34 and/or transmitter 36 can be configured in a different manner, such as two or more separate units; or as a single, integral transmission unit.
Output circuitry 35 for each acoustic I/O component 30 a, 30 b is operatively coupled to a corresponding receiver circuit (RXR) 37. Output circuitry 35 receives communication signals from the coupled receiver 37 and is arranged to condition such signals to provide a desired output to a respective earphone 24 a or 24 b of the corresponding acoustic I/O component 30 a or 30 b. As described in connection with input circuitry 34 and transmitter 36, output circuitry 35 and receiver 37 are configured to compatibly process signals based on the desired communication format.
Processing component 30 c also includes one or more transmitters 36 and receivers 37 which are operatively coupled to signal processing subsystem 44. Processing component 30 c further includes a user input control 46 and auxiliary output 48 coupled to signal processing subsystem 44. Signal processing subsystem 44 processes inputs received by the one or more receivers 37 of processing component 30 c and generates corresponding output signals for transmission by the one or more transmitters 36 of processing component 30 c.
Communication between modules 30 is performed by electrical conduction along one or more pathways formed by skin 26. The double-headed arrows 27 a, 27 b represent such communication pathways along portions of skin 26 between skin regions 26 a, 26 b, and 26 c. Electrode pairs 33 a, 33 b, 33 c provide for electrical coupling of components 30 a, 30 b, 30 c to skin regions 26 a, 26 b, 26 c, respectively. The electrical properties of human skin under nominal conditions facilitate the transmission of information in the form of a time varying electrical signal. Electrical conduction using human skin as a transmission medium can be described using a lumped element model at lower signal frequencies or a waveguide model at higher signal frequencies. To transmit an electric signal along skin 26, transmitter 36 of one of modules 30 applies a suitable time varying electric potential across a corresponding one of the electrode pairs 33 a, 33 b, 33 c electrically coupled to skin 26. The electric signal is transmitted by a closed electric circuit that links the communicating modules 30. This closed circuit includes electrical conduction pathways formed by skin 26 between the electrode pairs 33 a, 33 b, 33 c of the communicating modules 30.
Because of the intervening dielectric layer 32, electrode pairs 33 a, 33 b, 33 c capacitively couple to the respective skin regions 26 a, 26 b, 26 c. Layer 32 is composed and dimensioned relative to operating frequencies selected for transmitters 34 and receivers 37 to provide for suitable communication between modules 30 of system 20. In other embodiments, layer 32 may be absent, permitting direct contact between conductors 33 and skin 26, thereby allowing transmission by resistive coupling.
During operation of system 20, sound is detected with acoustic sensors 22 a, 22 b of components 30 a, 30 b. The corresponding acoustic input signals are conditioned with input circuitry 34 and supplied to transmitter 36 for each of the acoustic I/O components 30 a, 30 b. Transmitter 36 transmits the conditioned acoustic input signals along pathways 27 a, 27 b through electrode pairs 33 a, 33 b coupled to skin regions 26 a, 26 b, respectively. Processing component 30 c receives signals transmitted along pathways 27 a, 27 b with its one or more receivers 37 via electrical coupling of electrode pair 33 c with skin region 26 c. Processing component 30 c processes received signals with signal processing subsystem 44. A few nonlimiting examples of various configurations of subsystem 44 are described in connection with the signal processing arrangements of
Processing component 30 c transmits corresponding acoustic output signals to acoustic I/O components 30 a, 30 b along pathways 27 a, 27 b with its one or more transmitters 36 via electrode pair 33 c. Each acoustic I/O component 30 a, 30 b receives acoustic output signals supplied by processing component 30 c with a corresponding receiver 37. The receivers 37 of acoustic I/O components 30 a, 30 b provide signals to the corresponding output circuitry 37 that drives a respective earphone 24 a, 24 b.
Processing component 30 c also includes user input control 46 and auxiliary output 48. Control 46 can be utilized to change user-selectable parameters for signal processing subsystem 44. Alternatively or additionally, control 46 can provide for selection between different signal processing arrangements for system 20, such as those described in connection with
Modules 30 are each capable of "two way" communication given the ability to both transmit and receive communication signals. For each module 30, one electrode pair 33 a, 33 b, or 33 c is shared by the corresponding transmitter(s) 36 and receiver(s) 37. In an alternative embodiment, one or more modules can include multiple electrode pairs, with a different electrode pair dedicated to each module transmitter or receiver. Further, to distinguish between different communication sources and destinations, different carrier frequencies can be used. Accordingly, processing component 30 c could include a different transmitter and receiver for each acoustic I/O component 30 a, 30 b or multiplex between settings of a single transmitter and receiver. Alternatively or additionally, transmitted signals can be encoded with signal source and/or signal destination information for later decoding by the receiving component.
In other alternative embodiments, communication between certain modules is only one-way (unidirectional). Such one-way communication may be desired when a hearing aid system component only includes an acoustic input device such as sensor 22 a or 22 b or only an acoustic output device, such as earphone 24 a or 24 b. Further, different communication signal formats/modulations can be used for different communication pathways. In still further embodiments, one or more communication techniques besides electrical conduction along the skin are utilized.
Referring to
Referring to
It should be understood that modules of systems 20, 20 a, 20 b include power supplies and other components as would occur to those skilled in the art for implementation. Also, in other embodiments, modules of the various systems 20, 20 a, 20 b may be exchanged, duplicated, or deleted as would occur to those skilled in the art. Also, various signal processing techniques may be implemented by the processing components of systems 20, 20 a, 20 b, a few of which are described in connection with
Referring to
Sensors 22 a, 22 b are separated by distance D as illustrated by the like labeled line segment along lateral axis T. Lateral axis T is perpendicular to azimuthal axis AZ. Midpoint M represents the halfway point along distance D between sensor 22 a and sensor 22 b. Axis AZ intersects midpoint M and acoustic source 112. Axis AZ is designated as a point of reference (zero degrees) for sources 112, 114, 116 in the azimuthal plane and for sensors 22 a, 22 b. For the depicted embodiment, sources 114, 116 define azimuthal angles 114 a, 116 a relative to axis AZ of about −65� and +22�, respectively. Correspondingly, acoustic source 112 is at 0� relative to axis AZ. In one mode of operation, the "on axis" alignment of acoustic source 112 with axis AZ selects it as a desired source of acoustic excitation to be monitored with arrangement 110. In contrast, the "off-axis" sources 114, 116 are treated as noise and suppressed by arrangement 110, which is explained in more detail hereinafter. To adjust the direction being monitored, sensors 22 a, 22 b can be moved to change the position of axis AZ. Accordingly, user 21 can move his or her head to change the relative position of axis AZ defined between sensors 22 a, 22 b for arrangement 110. In an additional or alternative operating mode, the designated monitoring direction can be adjusted by changing a direction indicator incorporated in the routine of
For the convenience of description, sensors 22 a, 22 b are designated as belonging to left channel L and right channel R, respectively. Further, the analog time domain signals provided by sensors 22 a, 22 b are designated xL(t) and xR(t) for the respective channels L and R, where t represents time. Components 30 a, 30 b condition and format input signals xL(t) and xR(t) in a manner suitable for transmission to processing component 30 c. Either before or after transmission, signals xL(t) and xR(t) undergo an analog-to-digital (A/D) conversion with appropriate sampling hardware to provide discrete signals xL(z) and xR(z), corresponding to channels L and R, respectively; where z indexes discrete sampling events. The sampling rate fs is selected to provide desired fidelity for a frequency range of interest.
For arrangement 110, signal processing subsystem 44 is configured to include signal processor 42 operatively coupled to memory 50. Memory 50 is further depicted with buffers 52, 54. Processor 42 can be a software or firmware programmable device, a state logic machine, or a combination of both programmable and dedicated hardware. Furthermore, processor 42 can be comprised of one or more components and can include one or more Central Processing Units (CPUs). In one embodiment, processor 42 is in the form of a digitally programmable, highly integrated semiconductor chip particularly suited for signal processing. In other embodiments, processor 42 may be of a general purpose type or other arrangement as would occur to those skilled in the art. Likewise, memory 50 can be variously configured as would occur to those skilled in the art. Memory 50 can include one or more types of solid-state electronic memory, magnetic memory, or optical memory of the volatile and/or nonvolatile variety. Furthermore, memory can be integral with processor 42 and/or comprised of one or more distinct elements. Processing subsystem 44 can also include any oscillators, control clocks, interfaces, signal conditioners, additional filters, limiters, converters, power supplies, communication ports, or other types of components as would occur to those skilled in the art to implement the present invention. In one embodiment, subsystem 44 is provided in the form of a single microelectronic device.
Referring also to the flow chart of
In stage 246, a fast discrete fourier transform (FFT) algorithm is executed on a sequence of samples xL(z) and xR(z) and stored in buffer 54 for each channel L and R to provide corresponding frequency domain signals XL(k) and XR(k); where k is an index to the discrete frequencies of the FFTs. The set of samples xL(z) and xR(z) upon which an FFT is performed can be described in terms of a time duration of the sample data. Typically, for a given sampling rate fs, each FFT is based on more than 100 samples. Furthermore, for stage 246, FFT calculations include application of a windowing technique to the sample data. One embodiment utilizes a Hamming window. In other embodiments, data windowing can be absent or a different type utilized, the FFT can be based on a different sampling approach, and/or a different transform can be employed as would occur to those skilled in the art. After the transformation, the resulting spectra XL(k) and XR(k) are stored in FFT buffer 54 of memory 50. These spectra are generally complex-valued.
It has been found that reception of acoustic excitation emanating from a desired direction can be improved by weighting and summing the input signals in a manner arranged to minimize the variance (or equivalently, the energy) of the resulting output signal while under the constraint that signals from the desired direction are output with a predetermined gain. The following relationship (1) expresses this linear combination of the frequency domain input signals:
Y(k)=W L*(k)X L(k)+W R*(k)X R(k)=W H(k)X(k); (1)
Y(k) is the output signal in frequency domain form, WL(k) and WR(k) are complex valued multipliers (weights) for each frequency k corresponding to channels L and R, the superscript "*" denotes the complex conjugate operation, and the superscript "H" denotes taking the Hermitian of a vector. For this approach, it is desired to determine an "optimal" set of weights WL(k) and WR(k) to minimize variance of Y(k). Minimizing the variance generally causes cancellation of sources not aligned with the desired direction. For the mode of operation where the desired direction is along axis AZ, frequency components which do not originate from directly ahead of the array are attenuated because they are not consistent in phase across the left and right channels L, R, and therefore have a larger variance than a source directly ahead. Minimizing the variance in this case is equivalent to minimizing the output power of off-axis sources, as related by the optimization goal of relationship (2) that follows:
where Y(k) is the output signal described in connection with relationship (1). In one form, the constraint requires that "on axis" acoustic signals from sources along the axis AZ be passed with unity gain as provided in relationship (3) that follows:
e H W(k)=1 (3)
Here e is a two element vector which corresponds to the desired direction. When this direction is coincident with axis AZ, sensors 22 a and 22 b generally receive the signal at the same time and amplitude, and thus, for source 112 of the illustrated embodiment, the vector e is real-valued with equal weighted elements—for instance eH=[0.5 0.5]. In contrast, if the selected acoustic source is not on axis AZ, then sensors 22 a, 22 b can be moved to align axis AZ with it.
In an additional or alternative mode of operation, the elements of vector e can be selected to monitor along a desired direction that is not coincident with axis AZ. For such operating modes, vector e becomes complex-valued to represent the appropriate time/phase delays between sensors 22 a, 22 b that correspond to acoustic excitation off axis AZ. Thus, vector e operates as the direction indicator previously described. Correspondingly, alternative embodiments can be arranged to select a desired acoustic excitation source by establishing a different geometric relationship relative to axis AZ. For instance, the direction for monitoring a desired source can be disposed at a nonzero azimuthal angle relative to axis AZ. Indeed, by changing vector e, the monitoring direction can be steered from one location to another without moving either sensor 22 a, 22 b.
For inputs XL(k) and XR(k) that are indicative of stationary random processes (which is typical of speech signals over small periods of time), the following weight vector W(k) relationship (4) can be determined from relationships (2) and (3):
where e is the vector associated with the desired reception direction, R(k) is the correlation matrix for the kth frequency, W(k) is the optimal weight vector for the kth frequency and the superscript "−1" denotes the matrix inverse. The derivation of this relationship is explained in connection with a general model of the present invention applicable to embodiments with more than two sensors 22 a, 22 b in array 22.
The correlation matrix R(k) can be estimated from spectral data obtained via a number "M" of fast discrete Fourier transforms (FFTs) calculated over a relevant time interval. For the two channel L, R embodiment, the correlation matrix for the kth frequency, R(k), is expressed by the following relationship (5):
wherein Xl is the FFT in the frequency buffer for the left channel L and Xr is the FFT in the frequency buffer for right channel R obtained from previously stored FFTs that were calculated from an earlier execution of stage 246; "n" is an index to the number "N" of FFTs used for the calculation; and "M" is a regularization parameter. The terms Xll(k), Xlr(k), Xrl(k), and Xrr(k) represent the weighted sums for purposes of compact expression. It should be appreciated that the elements of the R(k) matrix are nonlinear, and therefore Y(k) is a nonlinear function of the inputs.
Accordingly, in stage 248 spectra Xl(k) and Xr(k) previously stored in buffer 54 are read from memory 50 in a First-In-First-Out (FIFO) sequence. Routine 240 then proceeds to stage 250. In stage 250, multiplier weights WL(k), WR(k) are applied to Xl(k) and Xr(k), respectively, in accordance with the relationship (1) for each frequency k to provide the output spectra Y(k). Routine 240 continues with stage 252 which performs an Inverse Fast Fourier Transform (IFFT) to change the Y(k) FFT determined in stage 250 into a discrete time domain form designated y(z). It should be understood that correspondence between Y(k) FFTs and output sample y(z) can vary. In one embodiment, there is one Y(k) FFT output for every y(z), providing a one-to-one correspondence. In another embodiment, there may be one Y(k) FFT for every 16 output samples y(z) desired, in which case the extra samples can be obtained from available Y(k) FFTs. In still other embodiments, a different correspondence may be established.
Next, in stage 254, digital-to-analog (D/A) conversion is performed with appropriate hardware to provide a corresponding analog output signal y(t). After conversion to the continuous time domain form, signal y(t) is transmitted from subsystem 44 of processing component 30 c to acoustic I/O components 30 a, 30 b. Output circuitry 37 conditions the received signals and drives earphones 24 a, 24 b. Arrangement 110 can be used to deliver generally the same sound to each ear of a user. Alternatively arrangement 110 can include further processing of output signals derived from y(t) to provide sound to each ear that selectively differs in terms of intensity and/or timing to account for differences in the orientation of the desired sound source relative to acoustic sensors 22 a, 22 b to improve sound perception.
After stage 254, routine 240 continues with conditional 256. In many applications it may not be desirable to recalculate the elements of weight vector W(k) for every Y(k). Accordingly, conditional 256 tests whether a desired time interval has passed since the last calculation of vector W(k). If this time period has not lapsed, then control flows to stage 258 to shift buffers 52, 54 to process the next group of signals. From stage 258, processing loop 260 closes, returning to conditional 244. Provided conditional 244 remains true, stage 246 is repeated for the next group of samples of xL(z) and xR(z) to determine the next pair of XL(k) and XR(k) FFTs for storage in buffer 54. Also, with each execution of processing loop 260, stages 248, 250, 252, 254 are repeated to process previously stored Xl(k) and Xr(k) FFTs to determine the next Y(k) FFT and correspondingly generate a continuous y(t). In this manner buffers 52, 54 are periodically shifted in stage 258 with each repetition of loop 260 until either process 240 halts as tested by conditional 244 or the time period of conditional 256 has lapsed.
If the test of conditional 256 is true, then routine 240 proceeds from the affirmative branch of conditional 256 to calculate the correlation matrix R(k) in accordance with relationship (5) in stage 262. From this new correlation matrix R(k), an updated vector W(k) is determined in accordance with relationship (4) in stage 264. From stage 264, update loop 270 continues with stage 258 previously described, and processing loop 260 is re-entered until routine 240 halts per conditional 244 or the time for another recalculation of vector W(k) arrives. Notably, the time period tested in conditional 256 may be measured in terms of the number of times loop 260 is repeated, the number of FFTs or samples generated between updates, and the like. Alternatively, the period between updates can be dynamically adjusted based on feedback from an operator or monitoring device (not shown).
Processing subsystem 44 performs the tests of conditionals 244 and 256, and executes the operations associated with stages 246, 248, 250, 252, 258, 262, and 264 of routine 240. In one embodiment, signal processor 42 is of a programmable type with software configured to execute these stages and conditionals. In other embodiments, some or all of these operations may be performed with dedicated hardware of subsystem 44. The A/D and D/A conversion operations of stages 242 and 254, respectively, can be performed by subsystem 44 or by acoustic I/O components 30 a, 30 c as appropriate for the particular type of communication signal format desired.
When routine 240 initially starts, earlier stored data is not generally available. Accordingly, appropriate seed values may be stored in buffers 52, 54 in support of initial processing. In other embodiments, a greater number of acoustic sensors can be included in array 22 and routine 240 can be adjusted accordingly. For this more general form, the output can be expressed by relationship (6) as follows:
Y(k)=W H(k)X(k) (6)
where the X(k) is a vector with an entry for each of "C" number of input channels and the weight vector W(k) is of like dimension. Equation (6) is the same at equation (1) but the dimension of each vector is C instead of 2. The output power can be expressed by relationship (7) as follows:
E[Y(k)2 ]=E[W(k)H X(k)X H(k)W(k)]=W(k)H R(k)W(k) (7)
where the correlation matrix R(k) is square with "C�C" dimensions. The vector e is the steering vector describing the weights and delays associated with a desired monitoring direction and is of the form provided by relationship (8) that follows:
where C is the number of array elements and φ is the desired monitoring direction expressed by relationship (9) as:
φ(k)=(2πDkf s/(CN)) for k=0,1, . . . , N−1 (9)
Thus, vector e may be varied with frequency to change the desired monitoring direction or "look-direction" and correspondingly steer the array. With the same constraint regarding vector e as described by relationship (3), the problem can be summarized by relationships (10) as follows:
This problem can be solved using the method of Lagrange multipliers generally characterized by relationship (11) as follows:
where the cost function is the output power, and the constraint is as listed above for vector e. A general vector solution begins with the Lagrange multiplier function H(W) of relationship (12):
where the factor of one half (�) is introduced to simplify later math. Taking the gradient of H(W) with respect to W(k), and setting this result equal to zero, relationship (13) results as follows:
∇W H(W)=R(k)W(k)+eλ=0 (13)
Also, relationship (14) follows:
W(k)=−R(k)−1 eλ (14)
Using this result in the constraint equation relationships (15) and (16) result as follows:
e H [−R(k)−1 eλ]=1 (15)
λ=−[e H R(k)−1 e] −1 (16)
and using relationship (114), the optimal weights are as set forth in relationship (17):
W opt =R(k)−1 e[e H R(k)−1 e] −1 (17)
Because the bracketed term is a scalar, relationship (4) has this term in the denominator, and thus is equivalent.
Returning to the two variable case for the sake of clarity, relationship (5) may be expressed more compactly by absorbing the weighted sums into the terms Xll, Xlr, Xrl and Xrr, and then renaming them as components of the correlation matrix R(k) per relationship (18):
Its inverse may be expressed in relationship (19) as:
where det( ) is the determinant operator. If the desired monitoring direction is perpendicular to the sensor array, e=[0.5 0.5]T, the numerator of relationship (4) may then be expressed by relationship (20) as:
Using the previous result, the denominator is expressed by relationship (21) as:
Canceling out the common factor of the determinant, the simplified relationship (22) is completed as:
It can also be expressed in terms of averages of the sums of correlations between the two channels in relationship (23) as:
where xl(k) and wr(k) are the desired weights for the left and right channels, respectively, for the kth frequency, and the components of the correlation matrix are now expressed by relationships (24) as:
just as in relationship (5). Thus, after computing the averaged sums (which may be kept as running averages), computational load can be reduced for this two channel embodiment.
Referring to FIGS. 1 and 8–11, signal processing arrangement 310 for system 20 is described, where like reference numerals refer to like features. The signal flow diagram of
For arrangement 310, subsystem 44 of system 20 is configured with appropriate processing hardware and/or software to include Digital Fourier Transform (DFT) stages 336 a, 336 b; delay operator 340; signal operator 350; localization operation 360; extraction stage 380, Inverse Fourier Transform 382; and post extraction processing 480. DFT stages 336 a, 336 b transform input signals xLn(k) and xRn(k) into spectral signals designated XLn(m) and XRn(m), respectively, using a short term discrete Fourier transform algorithm. Spectral signals XLn(m) and XRn(m) are expressed in terms of a number of discrete frequency components indexed by integer m; where m=1, 2, . . . , M. Also, as used herein, the subscripts L and R denote the left and right channels, respectively, and n indexes time frames for the discrete Fourier transform analysis.
Delay operator 340 receives spectral signals XLn(m) and XRn(m) from stages 336 a, 336 b, respectively. Delay operator 340 includes a number of dual delay lines (DDLs) 342 each corresponding to a different one of the component frequencies indexed by m. Thus, there are M different dual delay lines 342. However, only dual delay lines 342 corresponding to m=1 and m=M are shown in
The pair of frequency components from DFT stages 336 a, 336 b corresponding to a given value of m are inputs into a corresponding one of dual delay lines 342. For the examples illustrated in
Referring additionally to
For each dual delay line 342, the I number of pairs of multiplier taps 347 are each input to a different Operation Array (OA) 352 of operator 350. Each pair of taps 347 is provided to a different operation stage 354 within a corresponding operation array 352. In
For an arbitrary frequency ωm, delay times τi are given by equation (25) as follows:
where, i is the integer delay stage index in the range (i=1, . . . , I); ITDmax=D/c is the maximum Intermicrophone Time Difference; D is the distance between sensors 22 a, 22 b; and c is the speed of sound. Further, delay times τi are antisymmetric with respect to the midpoint of the delay stages corresponding to i=(I+1)/2 as indicated in the following equation (26):
As described in connection with arrangement 110 of
The azimuth positions in auditory space may be mapped to corresponding delayed signal pairs along each dual delay line 342 in accordance with equation (28) as follows:
Multipliers 346 have been included to multiply each corresponding delay stage 344 by an appropriate one of equalization factors αi(m); where i is the delay stage index previously described. Preferably, elements αi(m) are selected to compensate for differences in the noise intensity at sensors 22 a, 22 b as a function of both azimuth and frequency. In alternative embodiments where these differences can be neglected or are not present, αi(m) may be set to unity, making multipliers 346 unnecessary.
One preferred embodiment for determining equalization factors αi(m) assumes amplitude compensation is independent of frequency, regarding any departure from this model as being negligible. For this embodiment, the amplitude of the received sound pressure |p| varies with the source-receiver distance r in accordance with equations (A1) and (A2) as follows:
where |pL| and |pR| are the amplitude of sound pressures at sensors 22 a, 22 b.
r L=√{square root over ((l sin θi +D/2)2+(l cos θi)2)}{square root over ((l sin θi +D/2)2+(l cos θi)2)}=√{square root over (l2+lD sin θi+D2/4)}, (A3)
r R=√{square root over ((l sin θi −D/2)2+(l cos θi)2)}{square root over ((l sin θi −D/2)2+(l cos θi)2)}=√{square root over (l2−lD sin θi+D2/4)}. (A4)
For a given delayed signal pair in the dual delay-line 342 of
|p L|αi(m)=|p R|αl−i+1(m). (A5)
Substituting equation (A2) into equation (A5), equation (A6) results as follows:
By defining the value of αi(m) in accordance with equation (A7) as follows:
αi(m)=K√{square root over (l2+lD sin θi+D2/4)}, (A7)
where, K is in units of inverse length and is chosen to provide a convenient amplitude level, the value of αl−i+1(m) is given by equation (A8) as follows:
αl−i+1(m)=K√{square root over (l2+lD sin θl−i+1+D2/4)}= K√{square root over (l2−lD sin θi+D2/4)}, (A8)
where, the relation sin θl−i+1=sin θi can be obtained by substituting I-i+1 into i in equation (27). By substituting equations (A7) and (A8) into equation (A6), it may be verified that the values assigned to αi(m) in equation (A7) satisfy the condition established by equation (A6).
After obtaining the equalization factors αi(m) in accordance with this embodiment, minor adjustments are preferably made to calibrate for asymmetries in the sensor arrangement and other departures from the ideal case such as those that might result from media absorption of acoustic energy, an acoustic source geometry other than a point source, and dependence of amplitude decline on parameters other than distance.
After equalization by factors αi(m) with multipliers 346, the in-phase desired signal component is generally the same in the left and right channels of the dual delay lines 342 for the delayed signal pairs corresponding to i=isignal=s, and the in-phase noise signal component is generally the same in the left and right channels of the dual delay lines 342 for the delayed signal pairs corresponding to i=inoise=g for the case of a single, predominant interfering noise source. The desired signal at i=s may be expressed as Sn(m)=Asexp[j(ωmt+Φs)]; and the interfering signal at i=g may be expressed as Gn(m)=Agexp[j(ωmt+Φg)], where Φs and Φg denote initial phases. Based on these models, equalized signals αi(m)XLn (i)(m) for the left channel and αl−i+1(m)XRn (i)(m) for the right channel at any arbitrary point i (except i=s) along dual delay lines 342 may be expressed in equations (29) and (30) as follows:
αi(m)X Ln (i)(m)=A s exp j[ω m(t+τ s−τi)+φs ]+A g exp j[ω m(t+τ g−τi)+φg], (29)
αl−i+1(m)X Rn (i)(m)=A s exp j[ω m(t+τ l-s+1 −τ l−i+1)+φs ]+A g exp j[ω m(t+τ l-g+1−τl−i+1)+φg]. (30)
wherein equations (31) and (32) further define certain terms of equations (29) and (30) as follows:
X Ln (i)(m)=X Ln(m) exp (−2πf mτi) (31)
X Rn (i)(m)=X Rn(m) exp (−2πf mτl−i+1) (32)
Each signal pair αi(m)XLn (i)(m) and αl−i+1(m)XRn (i)(m) is input to a corresponding operation stage 354 of a corresponding one of operation arrays 352 for all m; where each operator array 352 corresponds to a different value of m as in the case of dual delay lines 342. For a given operation array 352, operation stages 354 corresponding to each value of I, except i=s, perform the operation defined by equation (33) as follows:
If the value of the denominator in equation (33) is too small, a small positive constant ε is added to the denominator to limit the magnitude of the output signal Xn (i)(m). No operation is performed by the operation stage 354 on the signal pair corresponding to i=s for all m (all operation arrays 352 of signal operator 350).
With the outputs from operation array 352, the simultaneous localization and identification of the spectral content of the desired signal may be performed with arrangement 310. Localization and extraction with arrangement 310 are further described by the signal flow diagram of
X n (i)(m)=S n(m)+G n(m)�νs,g (i)(m), i≠s (34)
where equation (35) further defines:
By applying equation (26) to equation (35), equation (36) results as follows:
The energy of the signal Xn (i)(m) is expressed in equation (37) as follows:
|X n (i)(m)|2 =|S n(m)+G n(m)�νs,g (i)(m)|2. (37)
A signal vector may be defined:
x(i)=(X1 (i)(1), X1 (i)(2), . . . , X1 (i)(M), X2 (i)(1), . . . , X2 (i)(M), . . . , XN (i)(1), . . . , XN (i)(M))T, i=1, . . . , I,
where, T denotes transposition. The energy ∥x(i)∥2 2 of the vector x(i) is given by equation (38) as follows:
Equation (38) is a double summation over time and frequency that approximates a double integration in a continuous time domain representation.
Further defining the following vectors:
s=(S1(1), S1(2), . . . , S1(M), S2(1), . . . , S2(M), . . . , SN(1), . . . , SN(M))T, and
g(i)=(G1(1)νs,g (i)(1), G1(2)νs,g (i)(2), . . . , G1(M)νs,g (i)(M), G2(1)νs,g (i)(1), . . . , G2(M)νs,g (i)(M), . . . , GN(1)νs,g (i)(1), . . . , GN(M)νs,g (i)(M))T, where i=1, . . . , I,
the energy of vectors s and g(i) are respectively defined by equations (39) and (40) as follows:
For a desired signal that is independent of the interfering source, the vectors s and g(i) are orthogonal. In accordance with the Theorem of Pythagoras, equation (41) results as follows:
∥x (i)∥2 2 =∥s+g (i)∥2 2 =∥s∥ 2 2 +∥g (i)∥2 2, i=1, . . . , I. (41)
Because ∥g(i)∥2 2≧0, equation (42) results as follows:
∥x(i)∥2 2≧∥s(i)∥2 2, i=1, . . . I. (42)
The equality in equation (42) is satisfied only when ∥g(i)∥2 2=0, which happens if either of the following two conditions are met: (a) Gn(m)=0, i.e., the noise source is silent—in which case there is no need for doing localization of the noise source and noise cancellation; and (b) νs,g (i)(m)=0; where equation (36) indicates that this second condition arises for i=g=inoise. Therefore, ∥x(i)∥2 2 has its minimum at i=g=inoise, which according to equation (42) is ∥s∥2 2. Equation (43) further describes this condition as follows:
Thus, the localization procedure includes finding the position inoise along the operation array 352 for each of the delay lines 342 that produces the minimum value of ∥x(i)∥2 2. Once the location inoise along the dual delay line 342 is determined, the azimuth position of the noise source may be determined with equation (27). The estimated noise location inoise may be utilized for noise cancellation or extraction of the desired signal as further described hereinafter. Indeed, operation stages 354 for all m corresponding to i=inoise provide the spectral components of the desired signal as given by equation (44):
Ś n(m)=X n (i
Localization operator 360 embodies the localization technique of arrangement 310.
Each summation operator 364 receives the results for each transform time frame n from the summation operator 362 corresponding to the same value of i and accumulates a sum of the results over time corresponding to n=1 through n=N transform time frames; where N is a quantity of time frames empirically determined to be suitable for localization. For the illustrated example, the upper summation operator 364 corresponds to i=1 and sums the results from the upper summation operator 362 over N samples; and the lower summation operator 364 corresponds to i=I and sums the results from the lower summation operator 362 over N samples.
The I number of values of ∥x(i)∥2 2 resulting from the I number of summation operators 364 are received by stage 366. Stage 366 compares the I number of ∥x(i)∥2 2 values to determine the value of i corresponding to the minimum ∥x(i)∥2 2. This value of i is output by stage 366 as i=g=inoise.
Referring back to
Stage 382 converts the M spectral components received from extraction unit 380 to transform the spectral approximation of the desired signal, Śn(m), from the frequency domain to the time domain as represented by signal śn(k). Signal śn(k) undergoes digital-to-analog conversion with subsystem 44 before transmission to acoustic I/O components 30 a, 30 b; or with components 30 a, 30 b after such transmission. Post extraction processing stage 480 processes the extracted output signal to provide separate acoustic output signals to each earphone 24 a, 24 b. As previously described, these separate signals may be generally the same or different to account for the position of the desired source relative to sensors 22 a, 22 b.
Another form of expression of equation (33) is given by equation (45) as follows:
X n (i)(m)=w Ln(m)X Ln (i)(m)+w Rn(m)X Rn (i)(m). (45)
The terms wLn and wRn are equivalent to beamforming weights for the left and right channels, respectively. As a result, the operation of equation (33) may be equivalently modeled as a beamforming procedure that places a null at the location corresponding to the predominant noise source, while steering to the desired output signal śn(t).
Referring to FIGS. 1 and 12–15, signal processing arrangement 410 for system 20 is described; where like reference numerals refer to like features. For arrangement 410, subsystem 44 is configured with appropriate hardware and/or software to include DFT stages 336 a, 336 b, delay operator 340, and signal operator 350 as described for arrangement 310; and localization operator 460 which is the same as localization operator 360 of arrangement 310 except that equalization factors αi(m) (i=1, . . . , I) are set to unity for the localization processes associated with localization operator 460. Furthermore, localization operator 460 of arrangement 410 directly receives the output signals of delay operator 340 instead of the output signals of signal operator 350, unlike arrangement 310.
The localization technique embodied in operator 460 begins by establishing two-dimensional (2-D) plots of coincidence loci in terms of frequency versus azimuth position. The coincidence points of each loci represent a minimum difference between the left and right channels for each frequency as indexed by m. This minimum difference may be expressed as the minimum magnitude difference δXn (i)(m) between the frequency domain representations XLp (i)(m) and XLp (i)(m), at each discrete frequency m, yielding M/2 potentially different loci. If the acoustic sources are spatially coherent, then these loci will be the same across all frequencies. This operation is described in equations (46)–(49) as follows:
i n(m)=argi min {δXn (i)(m)}, m=1, . . . , M/2. (46)
δX n (i)(m)=|X Ln (i)(m)−X Rn (i)(m)|, i=1, . . . , I; m=1, . . . , M/2, (47)
X Ln (i)(m)=X Ln(m)exp(−j2πτi m/M), i=1, . . . , I; m=1, . . . , M/2, (48)
X Rn (i)(m)=X Rn(m)exp(−j2πτl−i+1 m/M), i=1, . . . , I; m=1, . . . , M/2, (49)
If the amplitudes of the left and right channels are generally the same at a given position along dual delay lines 342 of arrangement 410 as indexed by i, then the values of δXn (i)(m) for the corresponding value of i is minimized, if not essentially zero. It is noted that, despite inter-sensor intensity differences, equalization factors αi(m) (i=1, . . . , I) should be maintained close to unity for the purpose of coincidence detection; otherwise, the minimal δXn (i)(m) will not correspond to the in-phase (coincidence) locations.
An alternative approach may be based on identifying coincidence loci from the phase difference. For this phase difference approach, the minimum of the phase difference between the left and right channel signals at positions along the dual delay lines 342, as indexed by i, are located as described by the following equations (50) and (51):
i n(m)=argi min{δXn (i)(m)}, m=1, . . . , M/2, (50)
δX n (i)(m)=|Im[X Ln (i)(m)X Rn (i)(m)†]|, i=1, . . . , I; m=1, . . . , M/2, (51)
where, Im[●] denotes the imaginary part of the argument, and the superscript † denotes a complex conjugate. Since the phase difference technique detects the minimum angle between two complex vectors, there is also no need to compensate for the inter-sensor intensity difference. While either the magnitude or phase difference approach may be effective without further processing to localize a single source, multiple sources often emit spectrally overlapping signals that lead to coincidence loci which correspond to nonexistent or phantom sources (e.g., at the midpoint between two equal intensity sources at the same frequency).
To reduce the occurrence of phantom information in the 2-D coincidence plot data, localization operator 460 integrates over time and frequency. When the signals are not correlated at each frequency, the mutual interference between the signals can be gradually attenuated by the temporal integration. This approach averages the locations of the coincidences, not the value of the function used to determine the minima, which is equivalent to applying a Kronecker delta function, δ(i−in(m)) to δXn (i)(m) and averaging the δ(i−in(m)) over time. In turn, the coincidence loci corresponding to the true position of the sources are enhanced. Integration over time applies a forgetting average to the 2-D coincidence plots acquired over a predetermined set of transform time frames from n=1, . . . , N; and is expressed by the summation approximation of equation (52) as follows:
where, 0<β<1 is a weighting coefficient which exponentially de-emphasizes (or forgets) the effect of previous coincidence results, δ(●) is the Kronecker delta function, θi represents the position along the dual delay-lines 342 corresponding to spatial azimuth θi [equation (26)], and N refers to the current time frame. To reduce the cluttering effect due to instantaneous interactions of the acoustic sources, the results of equation (52) are tested in accordance with the relationship defined by equation (53) as follows:
where Γ≧0, is an empirically determined threshold. While this approach assumes the inter-sensor delays are independent of frequency, it has been found that departures from this assumption may generally be considered negligible. By integrating the coincidence plots across frequency, a more robust and reliable indication of the locations of sources in space is obtained. Integration of Pn(θi,m) over frequency produces a localization pattern which is a function of azimuth. Two techniques to estimate the true position of the acoustic sources may be utilized. The first estimation technique is solely based on the straight vertical traces across frequency that correspond to different azimuths. For this technique, θd denotes the azimuth with which the integration is associated, such that θd=θi, and results in the summation over frequency of equation (54) as follows:
where, equation (54) approximates integration over time.
The peaks in Hn(θd) represent the source azimuth positions. If there are Q sources, Q peaks in HN(θd) may generally be expected. When compared with the patterns δ(i−in(m)) at each frequency, not only is the accuracy of localization enhanced when more than one sound source is present, but also almost immediate localization of multiple sources for the current frame is possible. Furthermore, although a dominant source usually has a higher peak in HN(θd) than do weaker sources, the height of a peak in HN(θd) only indirectly reflects the energy of the sound source. Rather, the height is influenced by several factors such as the energy of the signal component corresponding to θd relative to the energy of the other signal components for each frequency band, the number of frequency bands, and the duration over which the signal is dominant. In fact, each frequency is weighted equally in equation (52). As a result, masking of weaker sources by a dominant source is reduced. In contrast, existing time-domain cross-correlation methods incorporate the signal intensity, more heavily biasing sensitivity to the dominant source.
Notably, the interaural time difference is ambiguous for high frequency sounds where the acoustic wavelengths are less than the separation distance D between sensors 22 a, 22 b. This ambiguity arises from the occurrence of phase multiples above this intersensor distance related frequency, such that a particular phase difference Δφ cannot be distinguished from Δφ+2π. As a result, there is not a one-to-one relationship of position versus frequency above a certain frequency. Thus, in addition to the primary vertical trace corresponding to θd=θi, there are also secondary relationships that characterize the variation of position with frequency for each ambiguous phase multiple. These secondary relationships are taken into account for the second estimation technique for integrating over frequency. Equation (55) provides a means to determine a predictive coincidence pattern for a given azimuth that accounts for these secondary relationships as follows:
where the parameter γm,d is an integer, and each value of γm,d defines a contour in the pattern PN(θi,m). The primary relationship is associated with γm,d=0. For a specific θd, the range of valid γm,d is given by equation (56) as follows:
−ITD max f m(1+sin θd)≦γm,d ≦ITD max f m(1−sin θd) (56)
The graph 600 of
Notably, the existence of these ambiguities in PN(θi,m) may generate artifactual peaks in HN(θd) after integration along θd=θi. Superposition of the curved traces corresponding to several sources may induce a noisier HN(θd) term. When far away from the peaks of any real sources, the artifact peaks may erroneously indicate the detection of nonexistent sources; however, when close to the peaks corresponding to true sources, they may affect both the detection and localization of peaks of real sources in HN(θd). When it is desired to reduce the adverse impact of phase ambiguity, localization may take into account the secondary relationships in addition to the primary relationship for each given azimuth position. Thus, a coincidence pattern for each azimuthal direction θd (d=1, . . . , I) of interest may be determined and plotted that may be utilized as a "stencil" window having a shape defined by PN(θi,m) (i=1, . . . , I; m=1, . . . , M). In other words, each stencil is a predictive pattern of the coincidence points attributable to an acoustic source at the azimuth position of the primary contour, including phantom loci corresponding to other azimuth positions as a factor of frequency. The stencil pattern may be used to filter the data at different values of m.
By employing the equation (56), the integration approximation of equation (54) is modified as reflected in the following equation (57):
where A(θd) denotes the number of points involved in the summation. Notably, equation (54) is a special case of equation (57) corresponding to γm,d=0. Thus, equation (57) is used in place of equation (54) when the second technique of integration over frequency is desired. As shown in equation (26), both variables θi and τi are equivalent and represent the position in the dual delay-line. The difference between these variables is that θi indicates location along the dual delay-line by using its corresponding spatial azimuth, whereas τi denotes location by using the corresponding time-delay unit of value τi. Therefore, the stencil pattern becomes much simpler if the stencil filter function is expressed with τi as defined in the following equation (58):
where, τd relates to θd through equation (28). For a specific τd, the range of valid γm,d is given by equation (59) as follows:
−(ITD max/2+τd)f m≦γm,d≦(ITD max/2−τd)f m, γm,d is an integer. (59)
Changing value of τd only shifts the coincidence pattern (or stencil pattern) along the τi-axis without changing its shape. The approach characterized by equations (58) and (59) may be utilized as an alternative to separate patterns for each azimuth position of interest; however, because the scaling of the delay units τi is uniform along the dual delay-line, azimuthal partitioning by the dual delay-line is not uniform, with the regions close to the median plane having higher azimuthal resolution. On the other hand, in order to obtain an equivalent resolution in azimuth, using a uniform τi would require a much larger I of delay units than using a uniform θi.
The signal flow diagram of
Summation operators 466 pass results to summation operator 468 to approximate integration over frequency. Operators 468 may be configured in accordance with equation (54) if artifacts resulting from the secondary relationships at high frequencies are not present or may be ignored. Alternatively, stencil filtering with predictive coincidence patterns that include the secondary relationships may be performed by applying equation (57) with summation operator 468.
Referring back to
The localization techniques of localization operator 460 are particularly suited to localize more than two acoustic sources of comparable sound pressure levels and frequency ranges, and need not specify an on-axis desired source. As such, the localization techniques of arrangement 410 provide independent capabilities to localize and map more than two acoustic sources relative to a number of positions as defined with respect to sensors 22 a, 22 b. However, in other embodiments, the localization capability of localization operator 460 may also be utilized in conjunction with a designated reference source to perform extraction and noise suppression. Indeed, extraction operator 480 of the illustrated embodiment incorporates such features as more fully described hereinafter.
It has been discovered that by suppressing one or more different frequency components in each of a plurality of interfering sources after localization, it is possible to reduce the interference from the noise sources in complex acoustic environments, such as in the case of multi-talkers, in spite of the temporal and frequency overlaps between talkers. Although a given frequency component or set of components may only be suppressed in one of the interfering sources for a given time frame, the dynamic allocation of suppression of each of the frequencies among the localized interfering acoustic sources generally results in better intelligibility of the desired signal than is possible by simply nulling only the most offensive source at all frequencies.
Extraction operator 480 provides one implementation of this approach by utilizing localization information from localization operator 460 to identify Q interfering noise sources corresponding to positions other than i=s. The positions of the Q noise sources are represented by i=noise1, noise2, . . . , noiseQ. Notably, operator 480 receives the outputs of signal operator 350 as described in connection with arrangement 310, that presents corresponding signals Xn (i=noise1)(m), Xn (i=noise2)(m), . . . , Xn (i=noiseQ)(m) for each frequency m. These signals include a component of the desired signal at frequency m as well as components from sources other than the one to be canceled. For the purpose of extraction and suppression, the equalization factors αi(m) need not be set to unity once localization has taken place. To determine which frequency component or set of components to suppress in a particular noise source, the amplitudes of Xn (i=noise1)(m), Xn (i=noise2)(m), . . . , Xn (i=noiseQ)(m) are calculated and compared. The minimum Xn (inoise)(m), is taken as output Śn(m) as defined by the following equation (60):
Śn(m)=Xn (inoise)(m), (60)
where, Xn (inoise)(m) satisfies the condition expressed by equation (61) as follows:
|Xn (inoise)(m)|=min {|Xn (i=noise1)(m)|, |Xn (i=noise2)(m)|, . . . , |Xn (i=noiseQ)(m)|, |αs(m)XLn (s)(m)|}; (61)
for each value of m. It should be noted that, in equation (61), the original signal αs(m) XLn (s)(m) is included. The resulting beam pattern may at times amplify other less intense noise sources. When the amount of noise amplification is larger than the amount of cancellation of the most intense noise source, further conditions may be included in operator 480 to prevent changing the input signal for that frequency at that moment.
Many other embodiments of the present invention are envisioned. For example, any of arrangements 110, 310, 410 can be utilized for processing performed with system 20 a or 20 b. In another example, the signal processor 42 and memory 50 of arrangement 110 is utilized in part or in whole to implement features of processing arrangements 310 or 410.
Another embodiment includes operating a hearing aid including a first component and a second component, where the first component includes a pair of conductors. The first and second components are placed in contact with skin in a spaced apart relationship. The first pair of conductors are each electrically coupled to the skin through this placement. An electric potential is generated between the conductors to transmit an electrical communication signal from the first component to the skin in contact therewith. This signal is received by the second component over an electrical transmission pathway along the skin between the two components.
Yet another embodiment includes: operating a hearing aid including a first component and a second component, where the first component includes a first pair of electrodes and the second component includes a second pair of electrodes; electrically engaging the first pair of electrodes and the second pair of electrodes with skin; and transmitting an electrical signal from the first component to the second component by electrical conduction along the skin between the first pair of electrodes and the second pair of electrodes during this engagement.
In still another embodiment, a hearing aid is provided that includes first and second components, where the first component includes an acoustic sensor. The first and second components contact skin, and an electrical signal is transmitted from the first component to the second component during this contact by electrical conduction along a pathway formed by the skin between the first and second components.
A further embodiment includes a system comprising a hearing aid to enhance hearing of a user. This hearing aid includes a first component for placement in contact with the skin of the user. The first component includes a first pair of electrodes to electrically couple to the skin and a transmission circuit operable to transmit electrical signals to the skin through the first pair of electrodes. A second component is also included in the hearing aid that is spaced apart from the first component. This second component is sized for placement in a passageway of an ear of the user. The second component includes a receiver circuit. This receiver circuit receives the electrical signals by electrical conduction along the skin from the first component. The second component also includes an output device responsive to the electrical signals to stimulate hearing of the user.
Yet a further embodiment includes: detecting acoustic excitation with a number of acoustic sensors that provide a number of sensor signals; establishing a set of frequency components for each of the sensor signals; and determining an output signal representative of the acoustic excitation from a designated direction. This determination includes weighting the set of frequency components for each of the sensor signals to reduce variance of the output signal and provide a predefined gain of the acoustic excitation from the designated direction.
In another embodiment, a hearing aid includes a number of acoustic sensors in the presence of multiple acoustic sources that provide a corresponding number of sensor signals. A selected one of the acoustic sources is monitored. An output signal representative of the selected one of the acoustic sources is generated. This output signal is a weighted combination of the sensor signals that is calculated to minimize variance of the output signal.
Another embodiment includes: operating a voice input device including a number of acoustic sensors that provide a corresponding number of sensor signals; determining a set of frequency components for each of the sensor signals; and generating an output signal representative of acoustic excitation from a designated direction. This output signal is a weighted combination of the set of frequency components for each of the sensor signals calculated to minimize variance of the output signal.
Still a further embodiment includes an acoustic sensor array operable to detect acoustic excitation that includes two or more acoustic sensors each operable to provide a respective one of a number of sensor signals. Also included is a processor to determine a set of frequency components for each of the sensor signals and generate an output signal representative of the acoustic excitation from a designated direction. This output signal is calculated from a weighted combination of the set of frequency components for each of the sensor signals to reduce variance of the output signal subject to a gain constraint for the acoustic excitation from the designated direction.
In another embodiment, a signal processing system localizes and extracts acoustic excitation from a selected one of a number of acoustic sources. The system includes two spaced apart sensors to detect the sources and a processing subsystem with a delay line. The system can be provided in the form of two or more modules that communicate with each other using skin as a transmission medium. Alternatively or additionally, this embodiment may include filtering based on coincidence loci.
A further embodiment includes a processing system comprised of two or more modules that use skin as a communication medium. For this embodiment, a first signal is provided from a first acoustic sensor and a second signal from a second acoustic sensor spaced apart from the first acoustic sensor. The first and second signals each correspond to a composite of two or more acoustic sources that, in turn, include a plurality of interfering sources and a desired source. The interfering sources are localized by processing of the first and second signals to provide a corresponding number of interfering source signals. These signals each include a number of frequency components. One or more of the frequency components are suppressed for each of the interfering source signals.
The present invention will be further described with reference to the following specific examples. These experiments and results are intended to be illustrative of the present invention and should not be considered limiting or restrictive with regard to the scope of the present invention.
Experiments have been conducted using both analog FM signals and FSK digital communication techniques. In the analog FM test, a transmitter included a DSP56002 board from Motorola with a digital signal processor (DSP). The transmitter also included a direct digital synthesizer (DDS) modulator (AD7008) coupled to the board. The DDS provided a carrier frequency modulation (range: 1 Hz to 25 MHz) with a signal of frequency ≦18 kHz. The system was tested in the range of 50 kHz to 5 MHz. Signal-to-noise ratio (SNR) measurements relative to the noise floor indicated that preferred frequency ranges (60 dB) were 1.0–2.0 and 3.5–5.0 MHz, with a dip to 50 dB in the 2.0–3.5 MHz range. Low impedance HP 40493D foam Ag/AgCl electrodes with an area of 0.4 of a square inch were used to provide electrode pairs for most FM tests. The measurements above were taken at a transmit/receive separation of 7 cm. The signal was attenuated by 2–3 dB for each additional 20 cm of transmission length across the skin. No difference was noted between trials on one person in which the electrode were placed on the same arm relative to the case where the pairs were placed behind the two ears. Tests were also performed with custom electrodes (Easy-Flow 45 welding strips: Ag/Cu/Zn/Cd; 1.3 square inches) for which there was a loss of 3 dB; however signals could still be suitably sent from one ear to the other.
FSK testing used the DSP56002 board and the DDS for a transmitter, which was adjusted to provide modulated transmission signals in an FSK format. The DDS mapped the symbols to be transmitted into deviation frequencies off the center frequency. A center frequency of 5 MHz was used with deviation frequencies of 10, 13, 16, and 19 kHz. The transmitted signal was then sent to a receiver via skin transmission. The receiver comprised an RF/IF mixer coupled to a waveform generator. The waveform generator provided a 5 MHz signal that was used to demodulate the received signal, bringing it down to the kilohertz range. The mixer was coupled to DSP56302 processing board, which detected the mixed signals. A sampling rate of 48 kHz was used and 32 samples per symbol were acquired. Both cosine and sine wave matched filters, one pair of each target frequency (e.g., 10, 13, 16 and 19 kHz), were applied to the samples and the outputs were squared and summed to derive measures of signal strength at each frequency. The largest value was assumed to correspond to the frequency—and hence the code—which had been transmitted.
For the FSK testing, two pairs of electrodes (HP 40493D; connected to the transmitter and receiver, respectively) were placed upon different body parts (e.g., hands, neck and ear). Testing showed that the receiver still correctly identified symbols over a long transmission distance, e.g., from the hand to ear lobe. Testing was also performed to detect possible bit errors that may emanate from transmission through the skin. A 128 length input stream of 0's and 1's was sent over a direct connection and across the skin from the wrist to the ear lobe. There were no bit errors in this test. The results of these tests show that transmission of signals across the skin is feasible and reliable.
During the experiments, the current measured across the skin was in the range of 3–4 μA. This is well below the "Safe Current Limits for Electrical Apparatus" set by the American National Standards Institute (ANSI), i.e., 1 mA (rms) for frequencies of ≧1 MHz, and 1–2 order below the range that can pose danger for heart defibrillation. Furthermore, experiments have been conducted using a dielectric between the electrode pairs and skin; where the electrical coupling is capacitive. This indirect coupling technique has been found acceptable for transmission frequencies in the range of 100 MHz to 1.5 GHz.
All publications, patents, and patent applications cited in this specification are herein incorporated by reference as if each individual publication, patent, or patent application were specifically and individually indicated to be incorporated by reference and set forth in its entirety herein. Further, any theory, mechanism of operation, proof, or finding stated herein is meant to further enhance understanding of the present invention and is not intended to make the present invention in any way dependent upon such theory, mechanism of operation, proof, or finding. While the invention has been illustrated and described in detail in the drawings and foregoing description, the same is to be considered as illustrative and not restrictive in character, it being understood that only selected embodiments have been shown and described and that all changes, modifications and equivalents that come within the spirit of the invention as defined by the following claims are desired to be protected.
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|Otologics, Llc
|Low noise electret microphone
|Nov 8, 2012
|Mar 6, 2014
|Algor Korea Co., Ltd.
|Apparatus and method of shielding external noise for use in hearing aid device
|Sep 10, 2013
|Mar 13, 2014
|Algor Korea Co., Ltd.
|Hearing aid system for removing feedback noise and control method thereof
|Nov 15, 2013
|Mar 20, 2014
|Castani Co. L.L.C.
|Communications terminal, a system and a method for internet/network telephony
|Apr 2, 2015
|Oct 8, 2015
|Oticon A/S
|Binaural hearing assistance system comprising binaural noise reduction
|May 5, 2014
|Nov 5, 2015
|Nxp B.V.
|Electromagnetic induction field communication
|Sep 22, 2015
|Mar 23, 2016
|Oticon A/s
|A hearing assistance system comprising electrodes for picking up brain wave signals
|U.S. Classification
|381/312, 381/315, 455/100
|International Classification
|Cooperative Classification
|European Classification
|Sep 6, 2000
Owner name: UNIVERSITY OF ILLINOIS, THE, ILLINOIS
Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNORS:FENG, ALBERT S.;JONES, DOUGLAS L.;O BRIEN, WILLIAM D.;AND OTHERS;REEL/FRAME:011076/0266;SIGNING DATES FROM 20000627 TO 20000710
|Oct 5, 2010
|Fee payment
Year of fee payment: 4
|Oct 17, 2014
|Fee payment
Year of fee payment: 8