Non-Acoustic Speech Sensing System Based on Flexible Piezoelectric

Speech is one of the most important biological signals to complement human-human and human-computer interaction. Traditional speech datasets were collected by air microphones, but using these datasets in noisy environments such as factories is practically challenging. Therefore, speech recognition in noisy environments poses higher requirements. The non-acoustic speech dataset plays a significant role in robust speech recognition under high background noise. Existing datasets suffered from dull sound, low intelligibility and poor recognition accuracy due to hardware and computer technology limitations. This paper presents a non-acoustic speech sensing system based on flexible piezoelectric. The system collected vibration signals from the jaws of six males and five females, and the corpus contained ten different control commands at 90 dB of background noise. The dataset is reliable with high intelligibility and capable of achieving 93.7% recognition accuracy by calculation. With the aforementioned benefits, this dataset is an essential tool for studying human-computer interaction in high-noise environments, analyzing human acoustic properties, and aiding medical rehabilitation.