Prosodic Preferences of Surface Electromyography-based Subvocal Speech for People With Laryngectomy.

IF 2.5 4区 医学 Q1 AUDIOLOGY & SPEECH-LANGUAGE PATHOLOGY
Laura Raiff, Dea Turashvili, James T Heaton, Gianluca De Luca, Joshua C Kline, Jenny Vojtech
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Abstract

Introduction: People who undergo a total laryngectomy lose their natural voice and depend on alaryngeal technologies for communication. However, these technologies are often difficult to use and lack prosody. Surface electromyographic-based silent speech interfaces are novel communication systems that overcome many of the shortcomings of traditional alaryngeal speech and have the potential to seamlessly incorporate individualized prosody. The purpose of this study was to (1) validate the ability of alaryngeal silent speech to effectively incorporate pitch modulations-a key prosodic element in natural speech-into synthesized speech assessed through listening experiments and (2) determine the key features of these communication devices according to core users.

Methodology: People with laryngectomy (n = 15) and their primary communication partners (n = 5) listened to synthesized sentences with differing prosodic content generated from deep regression neural networks developed in our prior work. Specifically, the fundamental frequency (fo) contour of each sentence was manipulated in four ways: (1) flattened to the average fo, (2) altered to discrete sentence-level classification of muscle activity, (3) altered to continuous mapping of muscle activity, and (4) filtered to emulate speech from an electrolarynx (EL). Listeners ranked the fo contours of each sentence in terms of speech naturalness and the importance of various speech aid features.

Results: Continuous contours rated higher than all other types of contours, and monotonic EL contours rated the lowest. Speech aid features were rated highest to lowest in the following order: sound quality, intelligibility, pitch, delay, volume, hands-free, maintenance, cost, wearability, training, and visibility.

Conclusion: These results will help inform future development of silent speech interfaces and shape priorities of communication devices toward the preferences of their users.

基于表面肌电图的喉切除术患者声下言语的韵律偏好。
引言:接受全喉切除术的人失去了自然的声音,依靠喉部技术进行交流。然而,这些技术往往难以使用且缺乏韵律。基于表面肌电图的无声语音接口是一种新型的通信系统,它克服了传统咽音语音的许多缺点,并且具有无缝结合个性化韵律的潜力。本研究的目的是:(1)通过听力实验验证喉部无声语音有效地将音高调制(自然语音中的关键韵律元素)纳入合成语音的能力;(2)根据核心用户确定这些通信设备的关键特征。方法:接受喉切除术的患者(n = 15)和他们的主要交流伙伴(n = 5)听由我们先前工作中开发的深度回归神经网络生成的具有不同韵律内容的合成句子。具体来说,每个句子的基本频率(fo)轮廓通过四种方式进行处理:(1)平化为平均fo,(2)改变为肌肉活动的离散句子级分类,(3)改变为肌肉活动的连续映射,以及(4)过滤以模拟来自电喉音(EL)的语音。听者根据语音的自然度和各种语音辅助特征的重要性对每个句子的轮廓进行排序。结果:连续型轮廓评分高于其他类型轮廓,单调型轮廓评分最低。语音辅助功能的评分从高到低依次为:音质、可理解性、音调、延迟、音量、免提、维护、成本、可穿戴性、培训和可视性。结论:这些结果将有助于为无声语音界面的未来发展提供信息,并根据用户的偏好塑造通信设备的优先级。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Voice
Journal of Voice 医学-耳鼻喉科学
CiteScore
4.00
自引率
13.60%
发文量
395
审稿时长
59 days
期刊介绍: The Journal of Voice is widely regarded as the world''s premiere journal for voice medicine and research. This peer-reviewed publication is listed in Index Medicus and is indexed by the Institute for Scientific Information. The journal contains articles written by experts throughout the world on all topics in voice sciences, voice medicine and surgery, and speech-language pathologists'' management of voice-related problems. The journal includes clinical articles, clinical research, and laboratory research. Members of the Foundation receive the journal as a benefit of membership.
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