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» Bayesian sensing hidden Markov models for speech recognition
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ACL
2012
13 years 8 months ago
A Nonparametric Bayesian Approach to Acoustic Model Discovery
We investigate the problem of acoustic modeling in which prior language-specific knowledge and transcribed data are unavailable. We present an unsupervised model that simultaneou...
Chia-ying Lee, James R. Glass
ICMI
2004
Springer
159views Biometrics» more  ICMI 2004»
15 years 11 months ago
A segment-based audio-visual speech recognizer: data collection, development, and initial experiments
This paper presents the development and evaluation of a speaker-independent audio-visual speech recognition (AVSR) system that utilizes a segment-based modeling strategy. To suppo...
Timothy J. Hazen, Kate Saenko, Chia-Hao La, James ...
NAACL
2010
15 years 3 months ago
Investigations into the Crandem Approach to Word Recognition
We suggest improvements to a previously proposed framework for integrating Conditional Random Fields and Hidden Markov Models, dubbed a Crandem system (2009). The previous authors...
Rohit Prabhavalkar, Preethi Jyothi, William Hartma...
BIOADIT
2004
Springer
15 years 9 months ago
Biologically Plausible Speech Recognition with LSTM Neural Nets
Abstract. Long Short-Term Memory (LSTM) recurrent neural networks (RNNs) are local in space and time and closely related to a biological model of memory in the prefrontal cortex. N...
Alex Graves, Douglas Eck, Nicole Beringer, Jü...
ICASSP
2011
IEEE
14 years 9 months ago
Multi-view and multi-objective semi-supervised learning for large vocabulary continuous speech recognition
Current hidden Markov acoustic modeling for large vocabulary continuous speech recognition (LVCSR) relies on the availability of abundant labeled transcriptions. Given that speech...
Xiaodong Cui, Jing Huang, Jen-Tzung Chien