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Sinhala Speech Recognition for Interactive Voice Response Systems Accessed Through Mobile Phones

机译:通过手机访问的交互式语音响应系统的僧伽罗语语音识别

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This paper presents the development of a Sinhala Speech Recognition System to be deployed in an Interactive Voice Response (IVR) system of a telecommunication service provider. The main objectives are to recognize Sinhala digits and names of Sinhala songs to be set up as ringback tones. Sinhala being a phonetic language, its features are studied to develop a list of 47 phonemes. A continuous speech recognition system is developed based on Hidden Markov Model (HMM). The acoustic model is trained using the voice through mobile phone. The outcome is a speaker independent speech recognition system which is capable of recognizing 10 digits and 50 Sinhala songs. A word error rate (WER) of 11.2% using a speech corpus of 0.862 hours and a sentence error rate (SER) of 5.7% using a speech corpus of 1.388 hours are achieved for digits and songs respectively.
机译:本文介绍了Sinhala语音识别系统的开发,该系统将部署在电信服务提供商的交互式语音响应(IVR)系统中。主要目的是识别要设置为回铃音的僧伽罗语数字和僧伽罗语歌曲的名称。僧伽罗语是一种语音语言,对其功能进行了研究,以开发出47种音素的列表。基于隐马尔可夫模型(HMM)开发了一种连续语音识别系统。通过手机使用语音训练声学模型。结果是独立于说话者的语音识别系统,该系统能够识别10位数字和50篇僧伽罗歌曲。对于数字和歌曲,使用0.862小时的语料库的单词错误率(WER)为11.2%,使用1.388小时的语料库的句子错误率(SER)为5.7%。

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