Toward optimizing stream fusion in multistream recognition of speech

A multistream phoneme recognition framework is proposed based on forming streams from different spectrotemporal modulations of speech. Phoneme posterior probabilities were estimated from each stream separately and combined at the output level. A statistical model of the final estimated posterior pro...

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Bibliographic Details
Published in:The Journal of the Acoustical Society of America 2011-07, Vol.130 (1), p.EL14-EL18
Main Authors: Mesgarani, Nima, Thomas, Samuel, Hermansky, Hynek
Format: Article
Language:English
Subjects:
Acoustic signal processing
Acoustics
Exact sciences and technology
Fourier Analysis
Fundamental areas of phenomenology (including applications)
Humans
Mathematical models
Models, Statistical
Modulation
Neural Networks (Computer)
Noise - adverse effects
Pattern Recognition, Automated
Phonemes
Phonetics
Physics
Recognition
Signal Processing, Computer-Assisted
Sound Spectrography
Speech
Speech Acoustics
Speech recognition
Speech Recognition Software
Statistics
Streams
Time Factors
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Summary:A multistream phoneme recognition framework is proposed based on forming streams from different spectrotemporal modulations of speech. Phoneme posterior probabilities were estimated from each stream separately and combined at the output level. A statistical model of the final estimated posterior probabilities is used to characterize the system performance. During the operation, the best fusion architecture is chosen automatically to maximize the similarity of output statistics to clean condition. Results on phoneme recognition from noisy speech indicate the effectiveness of the proposed method.
ISSN:0001-4966
1520-8524
DOI:10.1121/1.3595744