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Phone-dependent channel compensated hidden Markov model for telephone speech recognition

机译:用于电话语音识别的依赖电话的信道补偿隐马尔可夫模型

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摘要

We propose the phone-dependent channel compensated hidden Markov model (PDCC-HMM) for telephone speech recognition. The PDCC-HMM is derived by modifying the conventional hidden Markov model (HMM) with the phone-dependent channel compensation vectors. The telephone speech is recognized efficiently by using the derived PDCC-HMM. Experiments demonstrate the robustness of PDCC-HMM in speech recognition and show the significant reduction of recognition error rate by 50% compared to the conventional HMM method.
机译:我们提出了用于电话语音识别的依赖于电话的信道补偿隐藏马尔可夫模型(PDCC-HMM)。通过使用电话相关的信道补偿向量修改常规的隐马尔可夫模型(HMM),可以得出PDCC-HMM。通过使用派生的PDCC-HMM,可以有效地识别电话语音。实验证明了PDCC-HMM在语音识别中的鲁棒性,并表明与传统的HMM方法相比,识别错误率显着降低了50%。

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