New Entropy Based Combination Rules in HMM/ANN Multi-stream ASR
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In this thesis, the framework of multi-stream combination has been explored to improve the noise robustness of automatic speech recognition (ASR) systems. The central idea of multi-stream ASR is to combine information from several sources to improve the pe ...
Recently, entropy measures at different stages of recognition have been used in automatic speech recognition (ASR) task. In a recent paper, we proposed that formant positions of a spectrum can be captured by multi-resolution spectral entropy feature. In th ...
In recent papers, entropy computed from sub-bands of the spectrum was used as a feature for automatic speech recognition. In the present paper, we further study the sub-band spectral entropy features which can give the flatness/peakiness of the sub-band sp ...
In this thesis, the framework of multi-stream combination has been explored to improve the noise robustness of automatic speech recognition (ASR) systems. The central idea of multi-stream ASR is to combine information from several sources to improve the pe ...
In this thesis, the framework of multi-stream combination has been explored to improve the noise robustness of automatic speech recognition (ASR) systems. The central idea of multi-stream ASR is to combine information from several sources to improve the pe ...
Multi-stream based automatic speech recognition (ASR) systems outperform their single stream counterparts, especially in the case of noisy speech. However, the main issues in multi-stream systems are to know a) Which streams to be combined, and b) How to c ...
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Recently, entropy measures at different stages of recognition have been used in automatic speech recognition (ASR) task. In a recent paper, we proposed that formant positions of a spectrum can be captured by multi-resolution spectral entropy feature. In th ...
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