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Block-diagonal covariance joint subspace tying and model compensation for noise robust automatic speech recognition
Block-diagonal covariance joint subspace tying and model compensation for noise robust automatic speech recognition
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机译:块对角协方差联合子空间绑定和模型补偿,用于噪声鲁棒的自动语音识别
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摘要
Model compression is combined with model compensation. Model compression is needed in embedded ASR to reduce the size and the computational complexity of compressed models. Model-compensation is used to adapt in real-time to changing noise environments. The present invention allows for the design of smaller ASR engines (memory consumption reduced to up to one-sixth) with reduced impact on recognition accuracy and/or robustness to noises.
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