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Combination method of Bone-conduction Speech and Air-conduction Speechfor Speaker Recognition

机译:用于扬声器识别的骨传导语音和空气传导语音组合方法

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Recently, some new sensors, such as bone-conductive micro-phones, throat microphones, and non-audible murmur (NAM) microphones, besides conventional condenser microphones have been developed for collecting speech data. Accordingly, some researchers began to study speaker and speech recognition using speech data collected by these new sensors. We focus on bone-conduction speech data collected by the bone-conductive microphone. This paper proposes a novel speaker identification method which combines "bone-conduction speech" and "air-conduction speech". The proposed method conducts speaker identification by integrating the similarity calculated by air-conduction speech model and similarity calculated by bone-conduction speech model. For evaluating the proposed method, we conduct the speaker identification experiment using part of a large bone-conduction speech corpus constructed by National Research Institute of Police Science, Japan (NRIPS). Experimental results show that the proposed method can reduce a identification error rate of air-conduction speech and bone-conduction speech. Especially, the proposed method achieves that the average error reduction rate from air-conduction speech to the proposed method is 35.8%.
机译:最近,已经开发出除了传统的冷凝器麦克风之外的一些新传感器,例如骨导电微电话,喉部麦克风和非声音杂音(NAM)麦克风用于收集语音数据。因此,一些研究人员开始使用这些新传感器收集的语音数据学习演讲者和语音识别。我们专注于由骨导电麦克风收集的骨传导语音数据。本文提出了一种新颖的扬声器识别方法,它结合了“骨传导语音”和“空气传导语音”。所提出的方法通过集成通过骨传导语音模型计算的空气传导语音模型和相似性计算的相似性来进行扬声器识别。为了评估所提出的方法,我们使用由日本国家研究所(NRIPS)的国家研究所建造的大型骨传导语料库的一部分进行扬声器识别实验。实验结果表明,该方法可以降低空气传导语音和骨传导语音的识别误差率。特别是,所提出的方法实现了从空气传导语音到所提出的方法的平均误差降低率为35.8%。

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