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Automatic Speech Recognition

Automatic speech recognition (ASR) can be defined as the independent, computer‐driven transcription of spoken language into readable text in real time (Stuckless, 1994). In a nutshell, ASR is technology that allows a computer to identify the words that a person speaks into a microphone or telephone and convert it to written text. Having a machine to understand fluently spoken speech has driven speech research for more than 50 years. Although ASR technology is not yet at the point where machines understand all speech, in any acoustic environment, or by any person, it is used on a day‐to‐day basis in a number of applications and services. The ultimate goal of ASR research is to allow a computer to recognize in real‐time, with 100% accuracy, all words that are intelligibly spoken by any person, independent of vocabulary size, noise, speaker characteristics or accent. Today, if the system is trained to learn an individual speaker's voice, then much larger vocabularies are possible and accuracy can be greater than 90%. Commercially available ASR systems usually require only a short period of speaker training and may successfully capture continuous speech with a large vocabulary at normal pace with a very high accuracy. Most commercial companies claim that recognition software can achieve between 98% to 99% accuracy if operated under optimal conditions. `Optimal conditions' usually assume that users: have speech characteristics which match the training data, can achieve proper speaker adaptation, and work in a clean noise environment (e.g. quiet space). This explains why some users, especially those whose speech is heavily accented, might achieve recognition rates much lower than expected. The earliest attempts to devise systems for automatic speech recognition by machine were made in the 1950s. Speech recognition technology was designed initially for individuals in the disability community. For example, voice recognition can help people with musculoskeletal disabilities caused by multiple sclerosis, cerebral palsy, or arthritis achieve maximum productivity on computers. During the early 1990s, tremendous market opportunities emerged for speech recognition computer technology. The early versions of these products were clunky and hard to use. The early language recognition systems had to make compromises: they were "tuned" to be dependent on a particular speaker, or had small vocabulary, or used a very stylized and rigid syntax. However, in the computer industry, nothing stays the same for very long and by the end of the 1990s there was a whole new crop of commercial …