| Speech recognition (in many contexts also
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| | achieve very high performance in
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| known as 'automatic speech recognition',
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| | controlled conditions. Part of the
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| computer speech recognition or
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| | confusion mainly comes from the mixed
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| erroneously as Voice Recognition) is the
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| | usage of the term speech recognition and
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| process of converting a speech signal to
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| | dictation.
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| a sequence of words, by means of an
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| | Speaker-dependent dictation systems
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| algorithm implemented as a computer
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| | requiring a short period of training can
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| program.
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| | capture continuous speech with a large
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| Speech recognition applications that have
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| | vocabulary at normal pace with a very
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| emerged over the last few years include
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| | high accuracy. Most commercial companies
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| voice dialing (e.g., Call home), call
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| | claim that recognition software can
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| routing (e.g., I would like to make a
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| | achieve between 98% to 99% accuracy
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| collect call), simple data entry (e.g.,
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| | (getting one to two words out of one
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| entering a credit card number),
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| | hundred wrong) if operated under optimal
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| preparation of structured documents
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| | conditions. These optimal conditions
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| (e.g., a radiology report), domotic
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| | usually means the test subjects have 1)
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| appliances control and content-based
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| | matching speaker characteristics with the
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| spoken audio search (e.g. find a podcast
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| | training data, 2) proper speaker
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| where particular words were spoken).
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| | adaptation, and 3) clean environment
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| Voice recognition or speaker recognition
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| | (e.g. office space). (This explains why
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| is a related process that attempts to
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| | some users, especially accented, might
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| identify the person speaking, as opposed
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| | actually find that the recognition rate
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| to what is being said.
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| | could be perceptually much lower than the
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| Speech recognition technology
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| | expected 98% to 99%).
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| In terms of technology, most of the
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| | Other, limited vocabulary, systems
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| technical text books nowadays emphasize
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| | requiring no training can recognize a
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| the use of Hidden Markov Model as the
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| | small number of words (for instance, the
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| underlying technology. The dynamic
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| | ten digits) from most speakers. Such
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| programming approach, the neural
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| | systems are popular for routing incoming
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| network-based approach and the
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| | phone calls to their destinations in
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| knowledge-based learning approach have
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| | large organizations.
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| been studied intensively in the 1980s and
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| | Both acoustic modeling and language
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| 1990s.
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| | modeling are important studies in modern
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| Performance of speech recognition systems
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| | statistical speech recognition. In this
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| The performance of a speech recognition
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| | entry, we will focus on explaining the
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| systems is usually specified in terms of
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| | use of hidden Markov model (HMM) because
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| accuracy and speed. Accuracy is measured
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| | notably it is very widely used in many
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| with the word error rate, whereas speed
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| | systems. (Language modeling has many
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| is measured with the real time factor.
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| | other applications such as smart keyboard
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| Most speech recognition users would tend
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| | and document classification; please refer
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| to agree that dictation machines can
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| | to the corresponding entries.)
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