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.
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。
In different background noisy environments, we conduct experiments about SNR, basic accuracy, noise resistant ability and system environment adaptability with different microphones.
在不同背景噪声下，采用不同的话筒，分别进行了有关信噪比、基本精度、抗噪能力以及系统对环境改变的适应性等实验。
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。
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。
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