Histogram-Based Quantization for Robust and/or Distributed Speech Recognition

In a distributed speech recognition (DSR) framework, the speech features are quantized and compressed at the client and recognized at the server. However, recognition accuracy is degraded by environmental noise at the input, quantization distortion, and transmission errors. In this paper, histogram-...

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Veröffentlicht in:	IEEE transactions on audio, speech, and language processing speech, and language processing, 2008-05, Vol.16 (4), p.859-873
Hauptverfasser:	WAN, Chia-Yu, LEE, Lin-Shan
Format:	Artikel
Sprache:	eng
Schlagworte:	Applied sciences Coding, codes Decoding Degradation Error compensation Errors Exact sciences and technology Histograms Information, signal and communications theory Noise Noise robustness Quantization Recognition robustness Sampling, quantization Signal and communications theory Signal processing Speech Speech processing Speech recognition Statistics Telecommunications and information theory Testing Transmission error Uncertainty vector quantization (VQ) Voice recognition Working environment noise
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