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Robust Speech Recognition Using Improved Vector Taylor Series Algorithm for Embedded Systems
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DOI：10.1109/TCE.2010.5505999.png)
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Abstract
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This paper proposes a novel robust speech recognition technique using improved vector Taylor series (VTS) algorithm for embedded systems. It uses a hidden Markov model (HMM) to replace the Gaussian mixture model (GMM) for estimating the clean speech feature, and gives the closed-form solutions of the noise parameters including the mean and variance at each expectation-maximization (EM) iteration. The experimental results show that the proposed algorithm makes a good balance between the computational complexity and recognition accuracy, and thus is more useful for embedded systems(1).
Keywords:
Robust speech recognition
vector Taylor series
feature compensation
hidden Markov model
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10.9
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