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An efficient distributed speech processing in noisy mobile communications

机译:嘈杂的移动通信中的高效分布式语音处理

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Mobile communications are greatly influenced by environmental noise that may cause a significant deterioration in automatic speech recognition (ASR) systems performance. In this paper, we present a new framework integrating a noise-robust front-end in distributed speech recognition (DSR) systems. Using the Aurora-2 speech database, the authors evaluate the development of an additional feature set for Mel-frequency-based European Telecommunications Standards Institute advanced front-end (ETSI-AFE) which we refer to as power-normalized cepstral coefficients (PNCCs). The experimental results show that, the proposed approach achieves a significant improvement in word recognition accuracy compared to the current ETSI-AFE deployed by the DSR technology on today's mobile phones.
机译:移动通信受到环境噪声的极大影响,环境噪声可能导致自动语音识别(ASR)系统性能显着下降。在本文中,我们提出了一个在分布式语音识别(DSR)系统中集成了抗噪前端的新框架。使用Aurora-2语音数据库,作者评估了基于Mel频率的欧洲电信标准协会高级前端(ETSI-AFE)的附加功能集的开发,我们将其称为功率归一化倒谱系数(PNCC) 。实验结果表明,与DSR技术在当今移动电话上部署的当前ETSI-AFE相比,该方法在单词识别准确度方面实现了显着提高。

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