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137
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NAACL
1994
15 years 5 months ago
High-Accuracy Large-Vocabulary Speech Recognition Using Mixture Tying and Consistency Modeling
Improved acoustic modeling can significantly decrease the error rate in large-vocabulary speech recognition. Our approach to the problem is twofold. We first propose a scheme that...
Vassilios Digalakis, Hy Murveit
152
Voted
ICASSP
2010
IEEE
15 years 3 months ago
Evaluation of random-projection-based feature combination on speech recognition
Random projection has been suggested as a means of dimensionality reduction, where the original data are projected onto a subspace using a random matrix. It represents a computati...
Tetsuya Takiguchi, Jeff Bilmes, Mariko Yoshii, Yas...
136
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INTERSPEECH
2010
14 years 10 months ago
SCARF: a segmental conditional random field toolkit for speech recognition
This paper describes a new toolkit - SCARF - for doing speech recognition with segmental conditional random fields. It is designed to allow for the integration of numerous, possib...
Geoffrey Zweig, Patrick Nguyen
101
Voted
INTERSPEECH
2010
14 years 10 months ago
Nonlinear enhancement of onset for robust speech recognition
In this paper we present a novel algorithm called Suppression of Slowly-varying components and the Falling edge of the power envelope (SSF) to enhance spectral features for robust...
Chanwoo Kim, Richard M. Stern
145
Voted
TASLP
2010
97views more  TASLP 2010»
14 years 10 months ago
Hierarchical Bayesian Language Models for Conversational Speech Recognition
Traditional n-gram language models are widely used in state-of-the-art large vocabulary speech recognition systems. This simple model suffers from some limitations, such as overfi...
Songfang Huang, Steve Renals