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Speech Recognition using Digital Signal Processing

Speech recognition methods can be divided into text-independent and text dependent methods. In a text independent system, speaker models capture characteristics of somebody's speech, which show up irrespective of what one is saying. In a text-dependent system, on the other hand, the recognition of the speaker's identity is based on his or her speaking one or more specific phrases, like passwords, card numbers, PIN codes, etc. This paper is based on text independent speaker recognition system and makes use of Mel frequency cepstrum coefficients to process the input signal and vector quantization approach to identify the speaker. The above task is implemented using MATLAB. Digital Signal Processing (DSP) is one of the most commonly used hardware platform that provides good development flexibility and requires relatively short application development cycle. DSP techniques have been at the heart of progress in Speech Processing during the last 25years.Simultaneously speech processing has been an important catalyst for the development of DSP theory and practice. Today DSP methods are used in speech analysis, synthesis, coding, recognition, enhancement as well as voice modification, speaker recognition, language identification. Speech recognition is generally computationally-intensive task and includes many of digital signal processing algorithms.