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A Comparative Study of Recognition Technique Used for Development of Automatic Stuttered Speech Dysfluency Recognition System

机译:口吃语音自动识别系统开发中识别技术的比较研究

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Objectives: This paper is an attempt to compare the work done around the world for development of stuttered speech database and approaches for analysis of stuttered speech and recognition system. Methods/Statistical Analysis: In particular we have compared the different methods adopted by the researchers around the world for development of speech database and the techniques implemented on these developed databases. We have compared the databases on the basis of utterances, gender, age group, speech dysfluencies and type of samples. The recognition systems are compared on the basis of feature used, classification techniques and the accuracy. Findings: Speech recognition based application is getting more popularized and now being implemented at various places. However, the developed speech recognition systems cannot handle the speech dysfluencies. Very less work had been carried out till date for stuttered speech recognition system. The work for Indian languages is very negligible. The only work carried out is for Kannada. There is no major contribution for other Indian Languages. This paper shows the current status and the notable work carried in other languages. Application/Improvements: There is a need to develop more such systems for other Indian languages which will be very helpful for multilingual society like India.
机译:目标:本文旨在比较世界范围内为发展口吃语音数据库所做的工作以及口吃语音分析和识别系统的方法。方法/统计分析:特别是,我们比较了世界各地研究人员采用的不同方法来开发语音数据库以及在这些已开发的数据库上实施的技术。我们根据话语,性别,年龄组,言语不适应和样本类型对数据库进行了比较。根据使用的特征,分类技术和准确性比较识别系统。发现:基于语音识别的应用程序越来越普及,现在已在各个地方实现。但是,已开发的语音识别系统无法处理语音不适当的情况。迄今为止,针对口吃语音识别系统的工作很少。印度语言的工作可忽略不计。进行的唯一工作是针对卡纳达语。其他印度语言没有重大贡献。本文显示了其他语言的当前状态和值得注意的工作。应用/改进:有必要为其他印度语言开发更多这样的系统,这将对像印度这样的多语种社会非常有帮助。

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