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This paper presents an entropy-based algorithm for accurate and robust endpoint detection for speech recognition under noisy environments. Instead of using the conventional energy-based features, the spectral entropy is developed to identify the speech segments accurately. Experimental results show that this algorithm outperforms the energy-based algorithms(More)
This paper presents the use of a variety of lters in the temporal trajectories of frequency band spectrum to extract speech recognition features for environmental robustness. Three kind of lters for emphasizing the statistically important parts of speech are proposed. First, a bank of RASTA-like band-pass lters to t the statistical peaks of modulation(More)
In this paper, an improved mismatch function by considering signal correlation between speech and noise is proposed to better estimate the noisy speech HMM's. A linearized model based on Taylor series expansion approach is used to approximate the proposed mismatch function. The parameters of the noisy speech HMM's can be estimated more precisely by(More)
BACKGROUND It was still rare for the quantitative magnetic resonance imaging (MRI) research of regional changes in hippocampus sclerosis (HS) in Chinese patients with epilepsy. This study aimed to study the hippocampal volumes (HVs) with quantitative MRI measurement in Chinese patients with epilepsy. METHODS Forty-six Chinese patients with epilepsy(More)
This paper presents an approach of automatic selection of phonetically distributed sentence sets for speaker adaptation, and applies the concept to the task of Mandarin speech recognition with very large vocabulary. This is a different approach to the adaptation data selection problem. A computer algorithm is developed to select minimum sets of phonetically(More)
In order to pursue high performance of Chinese information access on the Internet, this paper presents an attractive approach with a successful integration of efficient speech recognition and information retrieval techniques. A working system based on the proposed approach for speech retrieval of real-time Chinese netnews services has been implemented and(More)
The parallel model combination (PMC) technique has been shown to achieve very good performance for speech recognition under noisy conditions. In this approach, the speech signal and the noise are assumed uncorrelated during modeling. In this paper, a new correlated PMC is proposed by properly estimating and modeling the nonzero correlation between the(More)