SottoVoce: An Ultrasound Imaging-Based Silent Speech Interaction Using Deep Neural Networks
arXiv:2303.01758 · doi:10.1145/3290605.3300376
Abstract
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.
ACM CHI 2019 paper
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- WESPER: Zero-shot and Realtime Whisper to Normal Voice Conversion for Whisper-based Speech Interactions
- Towards a Better Understanding of Social Acceptability
- 3D Convolutional Neural Networks for Ultrasound-Based Silent Speech Interfaces
- DualVoice: Speech Interaction that Discriminates between Normal and Whispered Voice Input
- WhisperMask: A Noise Suppressive Mask-Type Microphone for Whisper Speech