EAGER: Variance and Invariance in Voice Quality

这项早期的探索性研究拨款旨在开发一个语音源可变性的数据库和模型。一种跨人和语音任务的语音变化模型可以提高语音合成系统的自然度。此外，了解语音的哪些方面(如果有的话)是特定于说话人的，应该有助于开发更好的说话人识别和验证算法。知道一个人可以在不损害他们的声音身份的情况下改变他或她的声音质量的程度，也可以为医疗康复申请提供信息。因此，更好地理解人类的声音将对科学以及工程和医学应用产生重大影响。该项目有强大的外展和传播计划，并促进加州大学洛杉矶分校电气工程、语言学和言语与听力科学的跨学科活动。它将在具有技术和科学意义的重要跨学科活动中培训本科生和研究生。这个探索性的项目将分析和发现在日常生活中引入变异性的情况下，说话者内部和之间的语音源是如何变化的。该项目旨在解决三个问题：1)单个说话者的语音源在录音会话和演讲任务中是否存在显著差异？2)双语说话者在说英语时是否表现出或多或少的说话者内部差异？以及3)最重要的是，所有这些来源的说话者内部变异性与说话者之间的变异性相比如何？理解这些问题将需要一个高质量的语音数据库，其中包含来自许多说话者的多个语音样本(在这种情况下为200个)，这些样本将被收集并分发给其他研究人员。声学分析将通过生成每个说话者的多维声学简档来显示不同情况下说话者之间和说话者内部的可变性，该多维声学简档指定该说话者的语料库中典型的参数值范围以及偏离该通常简档的可能性。

This EArly Grant for Exploratory Research aims at developing a database and model of voice source variability. A model of voice variations across people and speech tasks could improve the naturalness of speech synthesis systems. In addition, understanding what aspects of the voice, if any, are speaker-specific, should aid in developing better speaker identification and verification algorithms. Knowing how much a person could change his or her voice quality without compromising their vocal identity, could also inform medical rehab applications. A better understanding of the human voice will, thus, be of significant impact scientifically, and for engineering and medical applications. The project has strong outreach and dissemination programs and fosters interdisciplinary activities in Electrical Engineering, Linguistics, and Speech and Hearing Science at UCLA. It will train undergraduate and graduate students in important cross-disciplinary activities of technological and scientific significance. This exploratory project will analyze and discover how the voice source varies within and across talkers under circumstances that introduce variability in everyday life situations. The project aims to address three questions: 1) Does an individual talker's voice source vary significantly across recording sessions and speech tasks?, 2) Do bilingual talkers show more or less intra-talker variation when speaking in English?, and 3) Most importantly, how does intra-talker variability from all these sources compare with inter-talker variability? Understanding these issues will require a high-quality speech database with multiple voice samples from many talkers (in this case 200) which will be collected and distributed to other researchers. Acoustic analyses will reveal inter- and intra-talker variability in the voice source across different situations by generating a multi-dimensional acoustic profile of each talker that specifies the range of parameter values that are typical in the corpus for that talker, and the likelihood of deviations from that usual profile.