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In this paper, we propose a feature adaptation method that combines speech features from multiple microphone channels for robust automatic speech recognition (ASR). The proposed method first transforms the features in all channels using channel-dependent linear transforms, and then sum the channels into one channel for acoustic modeling. The transform parameters are estimated by maximizing the likelihood...
Parametric histogram equalization (PHEQ) is a simple and effective way to reduce noise and channel effects in automatic speech recognition. Recently, we proposed to adapt the PHEQ transform towards individual test utterance to further improve the performance of PHEQ. In this paper, we improve the adaptation of PHEQ by exploiting the correlation between speech feature elements. Previously, PHEQ is...
In this paper, we propose a novel feature space adaptation technique to improve the robustness of speech recognition in noisy environments. Histogram equalization (HEQ) is an effective technique for improving robustness by reducing the difference between clean and noisy features. A weakness of HEQ is that it does not take into account acoustic model, resulting in possible mismatch between HEQ-processed...
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