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A multi-lingual speech recognition system using a neural network approach

机译:使用神经网络方法的多语言语音识别系统

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A learning vector quantization method based on the dynamic time warping scheme is proposed for the speech recognition. The optimized speech database and adequate time-alignment vector matching can be achieved. The recognition accuracy for different users is improved by adapting the speech database using the learning vector quantization method. An user-friendly software system of the proposed method is implemented to demonstrate the recognition of 200 voice commands. Various languages and dialects can be realized in our system with a high recognition accuracy. The evaluation board of speech recognition using an 8051 microprocessor has been designed for the industrial applications. A pipelined programmable micro-architecture of the speech recognition processor is developed for the high-performance and high-speed recognition system.
机译:提出了一种基于动态时间规整方案的学习矢量量化方法。可以实现优化的语音数据库和足够的时间对齐矢量匹配。通过使用学习矢量量化方法调整语音数据库,可以提高对不同用户的识别精度。实现了该方法的用户友好软件系统,以演示对200个语音命令的识别。在我们的系统中可以实现各种语言和方言,并且具有很高的识别精度。使用8051微处理器的语音识别评估板专为工业应用而设计。针对高性能和高速识别系统,开发了语音识别处理器的流水线可编程微体系结构。

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