Large Vocabulary Continuous Speech Recognition - Berlin Chen

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Word-Conditioned Search (2/3)• Integration of acoustic and linguistic knowledge bymeans of tree-dimensional coordinates– A network (dynamically) built to describe sentences in terms ofwords• Language models for network transition probabilities– A network (statically) built to describe words in terms of phone• The pronunciation dictionary (organized as a phonetic tree)• Transition penalties are applied– A network (statically) built to describe a phone unit in terms ofsequences of HMM states• Spectral vectors derived from the speech signal are consumedSpeech – Berlin Chen 16
Word-Conditioned Search (3/3)BacktrackingInformationshould bemanipulated• Three basic operations performed– Acoustic-level re-combinations within tree arcs• Viterbi search( t, s;arc) = max ⎡ Q n ( t 1, s ; arc) P( s s ′ ; arc) ⎤−1− ′P( x s arc)Q −1v1 s′⎢⎣v1⎥⎦n t;– Tree arc extensionsQ( t S ; arc ) Q ( t − 1, S ar c )n − 1 , = n −′v01vM;11arc’– Language-model-level recombination• Word end hypotheses sharing the same history wererecombinednnH ( v ; t ) max ⎡−1α2= Q n ( t , Sv; arcE) P ( vnv ) ⎤−1⋅v vn11⎢⎣ 1⎥⎦ v 1v 2nQ t , S ; arc = H v ; tnv 2( ) ( )0The beginning state The ending stateB2( t, S arcB)v′ 01 −1Q n ;一群影響生活疫情影響生活n=3s Ms 0v 3arcn-1P( 生活 | 一群影響 )Q一群影響(-.S生活 , ,-)P( 生活 | 疫情影響 )Q疫情影響(-.S生活 , ,-)Speech – Berlin Chen 17
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: Word-Conditioned Search (1/3)• Wo
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 and 40: Word Graph Rescoring (1/6)• Tree-
Page 41 and 42: Word Graph Rescoring (3/6)• If bi
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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