摘要
随着信息技术与计算机技术的迅速发展,计算机应用深入到我们生活、工作的方方面面,人与计算机的联系越来越密切,人机交互研究,特别是语音方式的人机交互研究越来越广泛受到关注。人们不满于键盘鼠标的人机交互方式,希望使用更方便的图象语音,并且有个性化的特征。语音转换技术就是这样一种技术,它使语音形式的人机交互个性化,具有重要的理论和应用意义,是本论文的主要研究对象。
音色转换(Voice Conversion)是一项改变说话人声音特征的技术即转换说话人的音色个性特征而保持说话内容不变,在语音即时聊天,电影、广播、电视中剪辑和配音,语音合成的语料库收集,语音合成后端语音的个性化处理,在情报部门等都有很多应用。音色转换主要转换说话人的特征,本文着眼点是在高质量STRAIGHT语音分析合成下语音特征参数提取的研究。
本文主要完成了以下几方面的工作:(1)了解音色转换的研究现状,熟悉各种音色转换方法的基础上,对其进行了优劣的比较的研究。(2)在STRAIGHT分析算法的基础上采用动态特征参数,优化对特征参数的提取,提高了声音转换的质量。
With the development of information technology and computer science, the application of computer pervads every aspect of our lives. In modem life, computer and human being already gets more and more closed with each other.The research on "Human-Computer Interaction Techniques" became a hot issue. People don' t remain the satisfaction with typical inputting instrument using: such as key board & mouse. People prefer to get a more convinent and effective way to interact with compucter. Now "Voice Conversion" comes.In this paper we focus on the topic of voice conversion which makes the computer-human interaction more individualized and effective. And actually it will bring convenience to our real life. This technology is meaningful in theory and application and will be widely accepted on its own merits.
Voice conversion is a technque for modifying a source speaker's speech to sound as if it was spoken by a target speaker. Voice conversion will serve as an invaluable tool for many applications in speech technology,such as instant reversion to the other side in chat,also can be used for dubbing movies for TV broadcast and can provide various distinctive voice to speech synthesis.It also can be used in intelligence department.Voice conversion mainly convert a source speaker's acoustic features to target speaker's.Tthis paper's emphasis on researching acoustic fwatures in voice conversion system.
In this paper,we have achieve purpose:Firstly,we carries on the research comparison to each kind of acoustic features. Secondly,after the STRAIGHT analyse speech,we used dynamic features optimizes to improve the quality of converted speech.
引文
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