English

VoiceCoach: Interactive Evidence-based Training for Voice Modulation Skills in Public Speaking

Human-Computer Interaction 2020-10-06 v1 Computation and Language Information Retrieval

Abstract

The modulation of voice properties, such as pitch, volume, and speed, is crucial for delivering a successful public speech. However, it is challenging to master different voice modulation skills. Though many guidelines are available, they are often not practical enough to be applied in different public speaking situations, especially for novice speakers. We present VoiceCoach, an interactive evidence-based approach to facilitate the effective training of voice modulation skills. Specifically, we have analyzed the voice modulation skills from 2623 high-quality speeches (i.e., TED Talks) and use them as the benchmark dataset. Given a voice input, VoiceCoach automatically recommends good voice modulation examples from the dataset based on the similarity of both sentence structures and voice modulation skills. Immediate and quantitative visual feedback is provided to guide further improvement. The expert interviews and the user study provide support for the effectiveness and usability of VoiceCoach.

Keywords

Cite

@article{arxiv.2001.07876,
  title  = {VoiceCoach: Interactive Evidence-based Training for Voice Modulation Skills in Public Speaking},
  author = {Xingbo Wang and Haipeng Zeng and Yong Wang and Aoyu Wu and Zhida Sun and Xiaojuan Ma and Huamin Qu},
  journal= {arXiv preprint arXiv:2001.07876},
  year   = {2020}
}

Comments

Accepted by CHI '20

R2 v1 2026-06-23T13:17:19.792Z