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首页> 外文期刊>Journal of computer sciences >Speech Segmentation Using Dynamic Windows and Thresholds for Arabic and English Languages
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Speech Segmentation Using Dynamic Windows and Thresholds for Arabic and English Languages

机译:使用动态窗口和阈值对阿拉伯语和英语进行语音分割

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Segmentation of audio data such as human speech (splitting each word in separate audio file - .WAV file) has been a major concern when working with multimedia such as recordings from radio or TV. The main focus of the segmentation of boundaries of spoken language has been on using energy and zero crossing thresholds for endpoint detection. Errors in endpoint detection are still a main cause of low accuracy of segmentation systems. The goal of this research is to develop an efficient algorithm in order to segment the speech of human in both languages of English and Arabic in different speaking speed with high accuracy. Simulation results show that the developed algorithm achieved high accuracy when segmenting human speech in English language up to 91.6% in average, while it is 89.0% of Arabic language.
机译:在处理诸如广播或电视节目之类的多媒体内容时,诸如人类语音之类的音频数据分段(将每个单词拆分为单独的音频文件-.WAV文件)一直是一个主要的关注点。口语边界分割的主要焦点一直在使用能量和零交叉阈值进行端点检测。端点检测中的错误仍然是分割系统准确性低的主要原因。这项研究的目的是开发一种有效的算法,以高准确度将人类的语音以英语和阿拉伯语两种语言以不同的说话速度进行分割。仿真结果表明,所开发的算法在对人的英语语言进行语音分割时,平均精度达到91.6%,而阿拉伯语为89.0%。

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