A common technique for robust speech recognition is feature compensation.
特征补偿是一种常用的鲁棒性识别技术。
A robust speech recognition system in high noise environment is introduced and its performance is discussed in this paper.
开发了一高噪声环境下特定人孤立词的语音识别系统，讨论了系统性能的考核情况。
The paper introduces the definition and estimation methods of speaking rate in speech recognition, and presents a novel robust estimation method.
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 experiments also show that the audio-visual continuous speech recognition system is robust in noisy environments.
基于特征口形的音频-视频混合连续语音识别系统具有很好的抗噪性。
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.
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.
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。
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