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首页> 外文会议>IEEE/RSJ 2010 International Conference on Intelligent Robots and Systems >Improvement of speech recognition performance for spoken-oriented robot dialog system using end-fire array
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Improvement of speech recognition performance for spoken-oriented robot dialog system using end-fire array

机译：使用端射阵列提高面向口语的机器人对话系统的语音识别性能

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摘要

In this paper, we propose a microphone array structure for a spoken-oriented robot dialog system that is designed to discriminate the direction of arrival (DOA) of the target speech and that of the robot internal noise. First, we investigate the performance of the noise estimation conducted by semi-blind source separation (SBSS) in presence of both the diffuse background noise and the robot internal noise. The result indicates that the noise estimation of the SBSS is not good. Next, we analyze the DOA of the robot internal noise in order to determine the reason of the above resu we find out that the internal noise is always in-phase at the microphone array and overlap spacial with the target speech. Based on this fact, we propose to change the microphone array structure from the broadside array to the end-fire array in order to discriminate the DOAs of the target speech and the internal noise. Finally, we evaluate the word accuracy in a dictation task in presence of both diffuse background noise and robot internal noise to confirm the advantage of the proposed structure. Simulation results shows that the proposed microphone array structure results in approximately 10% improvement of the speech recognition performance.
机译：在本文中，我们为面向语音的机器人对话系统提出了一种麦克风阵列结构，该结构旨在区分目标语音的到达方向（DOA）和机器人内部噪声的到达方向。首先，我们研究了在存在扩散背景噪声和机器人内部噪声的情况下，通过半盲源分离（SBSS）进行噪声估计的性能。结果表明，SBSS的噪声估计不佳。接下来，我们分析机器人内部噪声的DOA，以确定导致上述结果的原因;我们发现，内部噪声在麦克风阵列处始终是同相的，并且与目标语音重叠。基于这一事实，我们建议将麦克风阵列结构从宽边阵列更改为端射阵列，以区分目标语音的DOA和内部噪声。最后，我们在存在扩散背景噪声和机器人内部噪声的情况下，在听写任务中评估单词的准确性，以确认所提出结构的优势。仿真结果表明，所提出的麦克风阵列结构可使语音识别性能提高约10％。

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