mlsanityData to 7 Oct 2026

SottoVoce: An Ultrasound Imaging-Based Silent Speech Interaction Using Deep Neural Networks

arXiv 2303.01758 ↗First posted 3 Mar 2023cs.HC cs.LG cs.SDcited by 5

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Abstract (arXiv)

The availability of digital devices operated by voice is expanding rapidly. However, the applications of voice interfaces are still restricted. For example, speaking in public places becomes an annoyance to the surrounding people, and secret information should not be uttered. Environmental noise may reduce the accuracy of speech recognition. To address these limitations, a system to detect a user's unvoiced utterance is proposed. From internal information observed by an ultrasonic imaging sensor attached to the underside of the jaw, our proposed system recognizes the utterance contents without the user's uttering voice. Our proposed deep neural network model is used to obtain acoustic features from a sequence of ultrasound images. We confirmed that audio signals generated by our system can control the existing smart speakers. We also observed that a user can adjust their oral movement to learn and improve the accuracy of their voice recognition.

Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Builds on 5 of its 59 references that are in the map. First posted on arXiv 3 Mar 2023.

Builds on

5 of 59 references.

References · 5

  1. 2014Adam: A Method for Stochastic Optimizationcited by 36,960
  2. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,604
  3. 2017Improved Speech Reconstruction from Silent Videocited by 26
  4. 2016Lipreading with Long Short-Term Memorycited by 14
  5. 2017Updating the silent speech challenge benchmark with deep learningcited by 7

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 1; 2024: 1; 2025: 1; 2026: 2.

5 papers.