评估移动环境下的语音合成:Facebook、Twitter和RSS的音频呈现

M. Aylett, Yolanda Vazquez-Alvarez, L. Baillie
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引用次数: 4

摘要

本文介绍了对播客服务的评估,该服务使用语音合成技术聚合来自Facebook、Twitter和RSS提要的数据。该服务使用一种新颖的方法来生成语音合成,其中使用XML标记来控制语音合成和最终podcast的声音设计。评估分为两个阶段:1)参与者在台式电脑上听播客,2)参与者一边走路一边听播客。我们的研究结果表明,参与者更喜欢带有声音效果和背景音乐的较短的播客,并受到周围环境噪音的影响。然而,作为该服务一部分的音频广告并没有产生显著的负面影响。另一个发现是,使用多种声音进行内容分割的优势可能已经被听众适应的困难所破坏。这项工作是语音合成提供新方法的一部分,其呈现风格构成了应用程序设计的一部分,并在应用程序上下文中进行评估。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Evaluating speech synthesis in a mobile context: Audio presentation of Facebook, Twitter and RSS
This paper presents an evaluation of a podcast service that aggregates data from Facebook, Twitter and RSS feeds, using speech synthesis. The service uses a novel approach to speech synthesis generation, where XML markup is used to control both the speech synthesis and the sound design of a resulting podcast. A two-phase evaluation was carried out: 1) participants listening to the podcasts on desktop computers, 2) participants listening to the podcasts while walking. Our findings show that participants preferred shorter podcasts with sound effects and background music, and were affected by the surrounding environmental noise. However, audio advertising which is part of the service did not have a significant negative effect. Another finding was that the advantage of using multiple voices for content segmentation may have been undermined by difficulties in listener adaptation. The work is part of a new approach to speech synthesis provision, where its style of rendition forms a part of the application design and it is evaluated within an application context.
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