A Simple Identification Method for Differentiating Between Ambient and Target Speech
A Simple Identification Method for Differentiating Between Ambient and Target Speech
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DOI：
10.1109/gcce46687.2019.9015499
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发表时间：
2019-10
期刊：
影响因子：
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通讯作者：
Naoto Kosaka;Kohei Kido;Yumi Wakita
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文献类型：
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作者：
Naoto Kosaka;Kohei Kido;Yumi Wakita
支持餐桌对话的系统的实际使用，例如在餐馆和社区房间中，需要将麦克风附近的目标对话与背景中的环境声学噪声分离。基于声学分析，我们证实了麦克风附近的对话和环境声音之间的差异表示在每个话语的功率电平的标准差（SD）。在嘈杂的环境对话的情况下，在餐厅，我们计算的边界之间的SD的功率值的麦克风附近的目标话语和环境对话使用线性判别分析（LDA）的方法。使用计算出的边界，我们评估了该系统的性能，在区分麦克风附近的目标对话从环境噪声引起的外来扬声器。实验结果表明，使用四个扬声器的平均识别率为83.5%。
The practical use of a system that supports table conversations, such as in restaurants and community rooms, requires the separation of target conversations near microphones from ambient acoustic noise in the background. Based on acoustic analysis, we confirmed that the difference between a conversation near a microphone and ambient sounds is represented in the standard deviation (SD) of the power levels of each utterance. In the case of noisy ambient conversation in a restaurant, we calculated the boundary between the SD of power values of target utterances near a microphone and that of ambient conversation using the Linear Discriminant Analysis (LDA) method. Using the calculated boundaries, we evaluated the performance of the system in distinguishing target conversations near microphones from ambient acoustic noise caused by extraneous speakers. Experimental results using four speakers demonstrated an average identification rate of 83.5%.