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TASLP
2010
122views more  TASLP 2010»
13 years 2 months ago
Error Approximation and Minimum Phone Error Acoustic Model Estimation
Minimum phone error (MPE) acoustic parameter estimation involves calculation of edit distances (errors) between correct and incorrect hypotheses. In the context of large vocabulary...
Matt Gibson 0002, Thomas Hain
ICASSP
2009
IEEE
14 years 2 months ago
A flat direct model for speech recognition
We introduce a direct model for speech recognition that assumes an unstructured, i.e., flat text output. The flat model allows us to model arbitrary attributes and dependences o...
Georg Heigold, Geoffrey Zweig, Xiao Li, Patrick Ng...
INTERSPEECH
2010
13 years 2 months ago
Decision tree state clustering with word and syllable features
In large vocabulary continuous speech recognition, decision trees are widely used to cluster triphone states. In addition to commonly used phonetically based questions, others hav...
Hank Liao, Christopher Alberti, Michiel Bacchiani,...
ICMCS
2006
IEEE
112views Multimedia» more  ICMCS 2006»
14 years 1 months ago
Minimum Phoneme Error based Filter Bank Analysis for Speech Recognition
In this paper the optimal filter-bank design method based on the Minimum Phone Error (MPE) criteria is investigated. We use Gaussian type filter bank for optimization and variou...
Hao Huang, Jie Zhu
FTSIG
2007
136views more  FTSIG 2007»
13 years 7 months ago
The Application of Hidden Markov Models in Speech Recognition
Hidden Markov Models (HMMs) provide a simple and effective framework for modelling time-varying spectral vector sequences. As a consequence, almost all present day large vocabula...
Mark J. F. Gales, Steve Young