Large Vocabulary Continuous Speech Recognition - Berlin Chen

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Word Graph Rescoring (2/6)• If word hypotheses ending at each time frame havescores higher than a predefined threshold– Their associated decoding information, such as the word startand end speech frames, the identities of current and predecessorwords, and the acoustic score, can be kept in order to build aword graph for further higher-order language model rescoring• E.g., a bigram LM was used in the tree search procedure,while a trigram LM in the word graph rescoring procedure• Keep track of word hypotheses whose scores are veryclose to the locally optimal hypothesis, but that do notsurvive due to the recombination process台灣入聯活動P( 活動 | 台灣入聯 )Bigram History Assumed中華民國入聯tP( 活動 | 中華民國入聯 )t 3t 2t 1Speech – Berlin Chen 40
Word Graph Rescoring (3/6)• If bigram LM is employed in the tree-copy searcht– For a word hypothesis ending at time , information aboutits beginning time and its immediate predecessor word should beretainedτ( t ; v,w) = B ( t,S ; arc )vbeginning time of wv : immediate predecessor word of w– The acoustic score of a word hypothesis is also retainedacoustic score of wACvww( w; τ , t ) = Q ( t,S ; arc ) H ( v,τ)( w; 0t)( w; 1t )( w t )AC v,0τAC v,τ1; τ2 2AC v,vvnEwEwFor each possible word hypothesis ,not only the word segment with the bestpredecessor word were recorded(those do not survive due to re-combinationare also kept)Speech – Berlin Chen 41
Page 1 and 2: Large Vocabulary ContinuousSpeech R
Page 3 and 4: Why LVCSR Difficult ? (2/2)• Maxi
Page 5 and 6: Classification of Approaches to LVC
Page 7 and 8: Word-conditioned vs. Time-condition
Page 9 and 10: Word-Conditioned Tree-Copy Search (
Page 11 and 12: Lexical/Phonetic Tree (2/2)• Reas
Page 13 and 14: Context-Dependent Phonetic Constrai
Page 15 and 16: Word-Conditioned Search (1/3)• Wo
Page 17 and 18: Word-Conditioned Search (3/3)Backtr
Page 19 and 20: WC: Implementation Issues (2/3)•
Page 21 and 22: WC: Pruning of Path Hypotheses (1/5
Page 27 and 28: WC: Language Model Look-ahead (2/2)
Page 29 and 30: WC: Acoustic Look-ahead (2/3)• Po
Page 31 and 32: More Details on Time-Conditioned Se
Page 33 and 34: TC: Decomposition of Search History
Page 35 and 36: TC vs. WC: Conflicting Expectations
Page 37 and 38: TC vs. A* search (2/2)- Operations
Page 39: Word Graph Rescoring (1/6)• Tree-
Page 43 and 44: Word Graph Rescoring (5/6)• “Wo
Page 45: • Feature ExtractionConfiguration

Large Vocabulary Continuous Speech Recognition - Berlin Chen

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