Robust speech recognition in the presence of noise using medical data

Theologos Athanaselis,Stelios Bakamidis,G A Giannopoulos,Ioannis Dologlou,Evita Fotinea

Crete（2008）

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摘要

This paper discusses the improvement of speech recognition in the presence of noise, when a parametric method of signal enhancement is used. The speech enhancement method improves the performance of voice control MRI. This is important since errors in the presence of noise are more frequent and tend to make applications, such as spoken dialogue systems, too cumbersome to use. The input signal is corrupted with MRI noise with varying signal-to-noise ratio. A non-linear spectral subtraction method (NSS) as well as an SVD based noise reduction techniques (ISE) are used in conjunction with the Speech Recognition system of the FAST project, to quantify the impact of speech enhancement.

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关键词

biomedical mri,noise,singular value decomposition,speech enhancement,speech recognition,svd,medical data,noise reduction techniques,nonlinear spectral subtraction method,parametric method,robust speech recognition,signal enhancement,spoken dialogue systems,voice control mri,non-linear spectral subtraction,speech recognition system,truncated svd procedure,hidden markov models,speech,noise reduction,signal to noise ratio,magnetic resonance imaging

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