An improved approach to robust speech recognition using minimum error classification

Speech Communication ◽

10.1016/s0167-6393(99)00027-8 ◽

2000 ◽

Vol 30 (1) ◽

pp. 27-36 ◽

Author(s):

Min-Tau Lin ◽

Andreas Spanias ◽

Philipos Loizou

Keyword(s):

Speech Recognition ◽

Robust Speech Recognition ◽

Minimum Error ◽

Error Classification

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A novel spotting-based approach to continuous speech recognition: Minimum error classification of keyword-sequences.

Journal of the Acoustical Society of Japan (E) ◽

10.1250/ast.16.147 ◽

1995 ◽

Vol 16 (3) ◽

pp. 147-157 ◽

Author(s):

Takashi Komori ◽

Shigeru Katagiri

Keyword(s):

Speech Recognition ◽

Continuous Speech ◽

Continuous Speech Recognition ◽

Minimum Error ◽

Error Classification

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A frequency-weighted HMM based on minimum error classification for noisy speech recognition

1997 IEEE International Conference on Acoustics, Speech, and Signal Processing ◽

10.1109/icassp.1997.596237 ◽

2002 ◽

Author(s):

H. Matsumoto ◽

M. Ono

Keyword(s):

Speech Recognition ◽

Noisy Speech ◽

Minimum Error ◽

Error Classification ◽

Noisy Speech Recognition

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Exploring Low-Dimensional Structures of Modulation Spectra for Robust Speech Recognition

10.21437/interspeech.2017-611 ◽

2017 ◽

Author(s):

Bi-Cheng Yan ◽

Chin-Hong Shih ◽

Shih-Hung Liu ◽

Berlin Chen

Keyword(s):

Speech Recognition ◽

Robust Speech Recognition ◽

Low Dimensional

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Toward Robust Speech Recognition and Understanding

The Journal of VLSI Signal Processing Systems for Signal Image and Video Technology ◽

10.1007/s11265-005-4149-x ◽

2005 ◽

Vol 41 (3) ◽

pp. 245-254 ◽

Author(s):

Sadaoki Furui

Keyword(s):

Speech Recognition ◽

Robust Speech Recognition

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Deep bidirectional neural networks for robust speech recognition under heavy background noise

Materials Today Proceedings ◽

10.1016/j.matpr.2021.02.640 ◽

2021 ◽

Author(s):

Jeevan Reddy Koya ◽

S.P. Venu Madhava Rao

Keyword(s):

Neural Networks ◽

Speech Recognition ◽

Background Noise ◽

Robust Speech Recognition

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Performance evaluation of front-end algorithms for robust speech recognition

Proceedings of the Eighth International Symposium on Signal Processing and Its Applications, 2005. ◽

10.1109/isspa.2005.1581037 ◽

2006 ◽

Author(s):

O. Cheng ◽

W. Abdulla ◽

Z. Salcic

Keyword(s):

Performance Evaluation ◽

Speech Recognition ◽

Robust Speech Recognition ◽

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Analysis of CFA-BF: Novel combined fixed/adaptive beamforming for robust speech recognition in real car environments

Speech Communication ◽

10.1016/j.specom.2009.09.001 ◽

2010 ◽

Vol 52 (2) ◽

pp. 134-149 ◽

Author(s):

John H.L. Hansen ◽

Xianxian Zhang

Keyword(s):

Speech Recognition ◽

Adaptive Beamforming ◽

Robust Speech Recognition

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Research of a Non-Specific Person Noise-Robust Speech Recognition System

2009 5th International Conference on Wireless Communications, Networking and Mobile Computing ◽

10.1109/wicom.2009.5301587 ◽

2009 ◽

Author(s):

Jing Bai ◽

Xueying Zhang

Keyword(s):

Speech Recognition ◽

Recognition System ◽

Robust Speech Recognition ◽

Speech Recognition System ◽

Noise Robust Speech Recognition ◽

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Limited Training Data Robust Speech Recognition Using Kernel-Based Acoustic Models

2006 IEEE International Conference on Acoustics Speed and Signal Processing Proceedings ◽

10.1109/icassp.2006.1660226 ◽

2006 ◽

Author(s):

M. Schaffoner ◽

S.E. Kruger ◽

E. Andelic ◽

M. Katz ◽

A. Wendemuth

Keyword(s):

Speech Recognition ◽

Training Data ◽

Robust Speech Recognition ◽

Acoustic Models

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Improving Viterbi Bayesian predictive classification via sequential bayesian learning in robust speech recognition

Speech Communication ◽

10.1016/s0167-6393(99)00018-7 ◽

1999 ◽

Vol 28 (4) ◽

pp. 313-326 ◽

Author(s):

Hui Jiang ◽

Keikichi Hirose ◽

Qiang Huo

Keyword(s):

Speech Recognition ◽

Bayesian Learning ◽

Robust Speech Recognition

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