Voice Recognition

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Speech recognition (in many contexts also known as 'automatic speech recognition', computer speech recognition or erroneously as Voice Recognition) is the process of converting a speech signal to a sequence of words, by means of an algorithm implemented as a computer program. Speech recognition applications that have emerged over the last years include voice dialing (e.g., Call home), call routing (e.g., I would like to make a collect call), simple data entry (e.g., entering a credit card number), and preparation of structured documents (e.g., a radiology report).

Voice Verification or speaker recognition is a related process that attempts to identify the person speaking, as opposed to what is being said.

Speech recognition technology

In terms of technology, most of the technical text books nowadays emphasize the use of Hidden Markov Model as the underlying technology. The dynamic programming approach, the neural network-based approach and the knowledge-based learning approach have been studied intensively in the 1980s and 1990s.

Performance of speech recognition systems

The performance of a speech recognition systems is usually specified in terms of accuracy and speed. Accuracy is measured with the word error rate, whereas speed is measured with the real time factor.

Most speech recognition users would tend to agree that dictation machines can achieve very high performance in controlled conditions. Part of the confusion mainly comes from the mixed usage of the term speech recognition and dictation.

Speaker-dependent dictation systems requiring a short period of training can 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 (getting one to two words out of one hundred wrong) if operated under optimal conditions. These optimal conditions usually means the test subjects have 1) matching speaker characteristics with the training data, 2) proper speaker adaptation, and 3) clean environment (e.g. office space). (This explains why some users, especially accented, might actually find that the recognition rate could be perceptually much lower than the expected 98% to 99%).

Other, limited vocabulary, systems requiring no training can recognize a small number of words (for instance, the ten digits) from most speakers. Such systems are popular for routing incoming phone calls to their destinations in large organizations.

Read more at Wikipedia.org