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Speech production knowledge has been used to enhance the phonetic representation and the performance of automatic speech recognition (ASR) systems successfully. Representations of speech production make simple explanations for many phenomena observed in speech. These phenomena can not be easily analyzed from either acoustic signal or phonetic transcription alone. One of the most important aspects...
With increasing demands for a natural interaction between human and machine, emotion perception from speech signals is becoming an important interaction interface. In this paper, we give a feature extraction framework for speech emotion recognition and present a novel method to extract emotion information based on group sparsity in tensor space. The speech signal is encoded as cortical representation...
Although the SSA has been studied extensively for speech enhancement, not too much attention has been paid to discuss the method to identify signal subspace dimension. In this paper we present a novel signal subspace dimension estimator based on Frobenius norm, with which subspace-based multi-channel speech enhancement is robust to such adverse acoustic environments as room reverberation and low input...
In this paper, a two-stage multi-speaker identification (SID) system is proposed for mixed speeches with multiple speakers speaking simultaneously. By investigating the second stage processing, we improved the performance of multi-speaker SID from 94.6% to 99.0% on a standard testing set, and comparing with another state-of-art system, the proposed results were also a little better. We also examined...
The theoretic foundation of traditional microphone array post-filters is the assumption that the noise between sensors is uncorrelated. However, this assumption is inaccurate in real environments since the correlated noise exists. In this paper, a generalized microphone array post-filter is proposed to deal with both the correlated and uncorrelated noise in environments and a novel perceptual filter...
In environments of strong background noise and reverberations, enhancement performance of classic microphone array enhancement systems is still not enough. Since ICA (independent component analysis) can separate independent sources only from observations, in this paper ICA is applied to highly noisy sensor signals to obtain cleaner speech signals, which are taken as inputs to the following microphone...
This paper presents a novel maximum a posteriori (MAP) denoising algorithm based on the independent component analysis (ICA). We demonstrate that the employment of individual ICA transformations for signal and noise can provide the best estimate within the linear framework. The signal enhancement problem is categorized based on the distribution of signal and noise being Gaussian or non-Gaussian and...
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