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KMID : 0917520030100030251
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Journal of Speech Sciences
2003 Volume.10 No. 3 p.251 ~ p.262
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Performance Comparison between the PMC and VTS Method for the Isolated Speech Recognition in Car Noise Environments
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Abstract
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There has been many research efforts to overcome the problems of speech recognition is noisy conditions. Among the noise-robut speech recognition methods, model-based adaptation approaches have been shown quite effective. Particularly, the PMC (parallel model combination) method is very popular and ha been shown to give considerably improved recognition results compared with the conventional methods. In this paper, we experimented with the VTS (vector Taylor series) algorithm, which is also based on the model parameter transformation but has not attracted much interests of the researchers in this area. To verify the effectiveness of it, we employed the algorithm in the continuous density HMM (Hidden Markov Model). We compared the performance of the VTS algorithm with the PMC method and could see that the it gave better results than the PMC method.
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