提出了一种平行子状态隐马尔可夫模型用作噪声鲁棒语音识别的声学模型。
In this paper, a parallel sub-state hidden Markov model, which integrates the clean speech and noise information, and each state of the model has several parallel sub-states, is presented.
分析了语音识别系统中语速的定义与估计方法，提出了基于持续时间分布的鲁棒语速估计法。
The paper introduces the definition and estimation methods of speaking rate in speech recognition, and presents a novel robust estimation method.
实验结果表明，这种方法不仅有明显的语音增强效果，且应用于噪声环境下的说话人识别系统时，能够提高系统的鲁棒性。
Experiments show that the new arithmetic not only has excellent effects on speech improvement but also has potential to improve robustness of a speaker recognition system in noisy environments.
本文还讨论了在语音信号的声学处理环节提高语音识别鲁棒性的问题和方法。
The problems and challenges for improving robust Mandarin digit speech recognition at the acoustic processing stage was also discussed.
而人工神经网络以其自适应、并行性、非线性、鲁棒性和学习特性被广泛应用于语音识别领域。
ANN is widely used in speech recognition field due to its self adapting, parallelism, non-linearity, robustness and learning ability.
特征参数的选取对整个语音识别系统的实时性、鲁棒性有很大的影响。
The chosen speech feature parameters have great effects on robustness and real-time of the speech recognition system.
提出了一种基于SDCN算法的鲁棒性语音命令识别。
A robust voice command recognition based on SDCN algorithm was presented.
实验表明，LOPDI算法能够显著提高语音识别系统对加性噪声的鲁棒性。
Experimental result shows that LOPDI algorithm can greatly increase automatic speech recognition system's robustness against additive noise.
语音识别系统的实用化，需要对噪声有很强的鲁棒性，而噪声环境下的端点检测对整个识别系统性能起着关键的作用。
While speech recognition system is put into use, it must be robust to noise. The endpoint detection in noisy background plays an important role in the whole recognition system.
通过对听觉谱和L PC倒谱对比分析，得到了听觉谱适宜用作语音识别并具有良好的噪声鲁棒性的结论。
The spectrum of auditory model and LPC-CEP shows that this auditory model not only represents speech signal well, but also is noise robust.
为了使语音识别系统在不同噪声环境下仍能具有较好的性能，就需要采用各种方法来增强识别系统的鲁棒性。
In order to make the speech recognition system maintain the good performance under these noise conditions, we must use various methods to enhance the robustness of system.
因此，噪声鲁棒性一直是语音识别研究中一个非常重要的方面。
Therefore, the noise robustness is a very important part of speech recognition research.
最后从识别率、鲁棒性方面对该系统进行了测试和分析，实验结果表明，该语音识别系统是稳定的实用的。
At last the system is tested and analyzed in recognition rate and robust. The experiments show that the system is stable and practical.
最后从识别率、鲁棒性方面对该系统进行了测试和分析，实验结果表明，该语音识别系统是稳定的实用的。
At last the system is tested and analyzed in recognition rate and robust. The experiments show that the system is stable and practical.
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