FAST SEARCH IN SPEECH RECOGNITION

Speech recognition involves searching for the most likely one of a number of sequences of words, given a speech signal. Each such sequence is a composite sequence, composed of consecutive sequences of states. Searching involves a number of searches, each in a respective search space containing a sub...

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description Speech recognition involves searching for the most likely one of a number of sequences of words, given a speech signal. Each such sequence is a composite sequence, composed of consecutive sequences of states. Searching involves a number of searches, each in a respective search space containing a subset of the sequences of states. In each search only the more likely sequences of states in the relevant search space are considered. In a first embodiment different search spaces are made up of sequences of states that follow preceding sequences from a class of sequences of words. Different classes define different ones of the search spaces. Classes are distinguished on the basis of phonetic history rather than word history, as represented by the sequences of states in the composite sequence up to the sequence of states in the search space. Thus, the number of words or parts thereof whose identity is used to distinguish different classes is varied depending on a length of one or more last words represented by the composite sequence. In a second embodiment, a plurality different composite sequences are involved in a search through a joint sequence of states, for which representative likelihood information for the plurality is used to decide whether or not to discard it in the search. At the end of the search the likelihood for the different composite sequences is regenerated from the joint sequence if it survived the search, and further search is based on the regenerated likelihood. In a third embodiment, this technique is applied within searches at the subword level.
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Searching involves a number of searches, each in a respective search space containing a subset of the sequences of states. In each search only the more likely sequences of states in the relevant search space are considered. In a first embodiment different search spaces are made up of sequences of states that follow preceding sequences from a class of sequences of words. Different classes define different ones of the search spaces. Classes are distinguished on the basis of phonetic history rather than word history, as represented by the sequences of states in the composite sequence up to the sequence of states in the search space. Thus, the number of words or parts thereof whose identity is used to distinguish different classes is varied depending on a length of one or more last words represented by the composite sequence. In a second embodiment, a plurality different composite sequences are involved in a search through a joint sequence of states, for which representative likelihood information for the plurality is used to decide whether or not to discard it in the search. At the end of the search the likelihood for the different composite sequences is regenerated from the joint sequence if it survived the search, and further search is based on the regenerated likelihood. 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In a second embodiment, a plurality different composite sequences are involved in a search through a joint sequence of states, for which representative likelihood information for the plurality is used to decide whether or not to discard it in the search. At the end of the search the likelihood for the different composite sequences is regenerated from the joint sequence if it survived the search, and further search is based on the regenerated likelihood. 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Each such sequence is a composite sequence, composed of consecutive sequences of states. Searching involves a number of searches, each in a respective search space containing a subset of the sequences of states. In each search only the more likely sequences of states in the relevant search space are considered. In a first embodiment different search spaces are made up of sequences of states that follow preceding sequences from a class of sequences of words. Different classes define different ones of the search spaces. Classes are distinguished on the basis of phonetic history rather than word history, as represented by the sequences of states in the composite sequence up to the sequence of states in the search space. Thus, the number of words or parts thereof whose identity is used to distinguish different classes is varied depending on a length of one or more last words represented by the composite sequence. In a second embodiment, a plurality different composite sequences are involved in a search through a joint sequence of states, for which representative likelihood information for the plurality is used to decide whether or not to discard it in the search. At the end of the search the likelihood for the different composite sequences is regenerated from the joint sequence if it survived the search, and further search is based on the regenerated likelihood. In a third embodiment, this technique is applied within searches at the subword level.</abstract><edition>7</edition><oa>free_for_read</oa></addata></record>
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language eng ; fre ; ger
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subjects ACOUSTICS
MUSICAL INSTRUMENTS
PHYSICS
SPEECH ANALYSIS OR SYNTHESIS
SPEECH OR AUDIO CODING OR DECODING
SPEECH OR VOICE PROCESSING
SPEECH RECOGNITION
title FAST SEARCH IN SPEECH RECOGNITION
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