About: Audio-Visual Speech Recognition in Noisy Audio Environments     Goto   Sponge   NotDistinct   Permalink

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  • It is a well-known fact that the visual part of speech can improve the resulting recognition rate mainly in noisy conditions. Main goal of this work is to find a set of visual features which would be possible to use in our audio-visual speech recognition systems. Discrete Cosine Transform (DCT) and Active Appearance Model (AAM) based visual features are extracted from visual speech signals, enhanced by a simplified variant of Hierarchical Linear Discriminant Analysis (HiLDA) and normalized across speakers. The visual features are then combined with standard MFCC audio features by the middle fusion method. The results from audio-visual speech recognition are compared with the results from experiments where the log-spectra minimum mean square error and multiband spectral subtraction methods for reducing additive noise in the audio signal are used.
  • It is a well-known fact that the visual part of speech can improve the resulting recognition rate mainly in noisy conditions. Main goal of this work is to find a set of visual features which would be possible to use in our audio-visual speech recognition systems. Discrete Cosine Transform (DCT) and Active Appearance Model (AAM) based visual features are extracted from visual speech signals, enhanced by a simplified variant of Hierarchical Linear Discriminant Analysis (HiLDA) and normalized across speakers. The visual features are then combined with standard MFCC audio features by the middle fusion method. The results from audio-visual speech recognition are compared with the results from experiments where the log-spectra minimum mean square error and multiband spectral subtraction methods for reducing additive noise in the audio signal are used. (en)
Title
  • Audio-Visual Speech Recognition in Noisy Audio Environments
  • Audio-Visual Speech Recognition in Noisy Audio Environments (en)
skos:prefLabel
  • Audio-Visual Speech Recognition in Noisy Audio Environments
  • Audio-Visual Speech Recognition in Noisy Audio Environments (en)
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  • RIV/46747885:24220/13:#0002802!RIV14-MSM-24220___
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  • 62506
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  • RIV/46747885:24220/13:#0002802
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  • AAM; Audio visual speech recognition; Discrete Cosine Transform(DCT); HiLDA; Linear discriminant analysis; Minimum mean square errors; Multi-band spectral subtractions; Visual speech features (en)
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  • [AD2CBFB0FAEE]
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  • Itálie
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  • Proc. of 36th International Conference on Telecommunications and Signal Processing (TSP 2013)
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  • Chaloupka, Josef
  • Paleček, Karel
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number of pages
http://bibframe.org/vocab/doi
  • 10.1109/TSP.2013.6613979
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  • Neuveden
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  • 9781479904044
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  • 24220
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