RI: Medium: Collaborative Research: The Effect of Subglottal Resonances on Machine and Human Speaker Normalization

该奖项是根据2009年美国复苏和再投资法案（公法111-5）资助的。尽管不同的说话者说话的声音差异很大，但人类通常能够快速而轻松地相互理解。人类将这种变异映射到一组音素上的机制已经被研究了50多年。这种“说话人归一化”问题通常被认为是根据一个特定说话人的共振峰频率与一组参考共振峰进行归一化。在这个项目中，探索了一种新的说话人归一化方法，其中不是共振峰而是声门下共振（sgr）归一化。先前的研究表明，sgr定义了一组频带，在这些频带内共振峰可能会发生变化，但仍保持相同的音素元音质量。因此，标准化sgr（及相关频段）可以有效地减少形成峰的可变性。在这个项目中，SGR归一化对英语和西班牙语的成人和儿童自动语音识别（ASR）性能的影响进行了评估。同时，研究了在多说话人的情况下对人类语音感知的影响。研究结果有望改善ASR的表现，并阐明人类语音产生和感知。该项目将产生语音数据库（包括SGR声学的直接记录）和ASR工具，这对于人工耳蜗和多语言ASR的语音产生、感知、说话人识别和语音处理算法的研究至关重要。工程、语言学、言语与听觉、心理学等学科的合作，促进了多学科的学习环境。出版物、结果、数据库和工具将分发给研究界。

This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5).Despite large acoustic differences in the speech of various talkers, humans are generally able to understand each other quickly and easily. The mechanisms by which humans map such variability onto a set of phonemes has been the subject of research for more than 50 years. This "speaker normalization" problem has generally been thought of in terms of normalizing the formant frequencies of a particular speaker with a reference set of formants. In this project, a novel approach to speaker normalization is explored, in which not formants but subglottal resonances(SGRs) are normalized. SGRs have previously been shown to define a set of frequency bands within which formants may vary, yet retaining the same phonemic vowel quality. Normalizing SGRs (and associated frequency bands) therefore reduces formant variability in an effective way. In this project, effects of SGR normalization on automatic speech recognition(ASR) performance are evaluated for both adult and child speakers of English and Spanish. In parallel, effects on human speech perception in multi-talker conditions are explored. Results are expected to improve ASR performance and shed light on human speech production and perception. The project will result in speech databases (including direct recordings of SGR acoustics) and ASR tools, which are critically useful for research in speech production, perception, speaker identification, and speech processing algorithms for cochlear implants and multi-lingual ASR. The collaboration in Engineering, Linguistics, Speech & Hearing, and Psychology facilitates a multidisciplinary learning environment.Publications, results, databases, and tools will be disseminated to the research community.