TOWARDS MORE INTELLIGIBLE PHYSIOLOGICAL MICROPHONE SPEECH: A PROBABILISTIC TRANSFORMATION APPROACH

The non-acoustic physiological microphone (PMIC) has been shown to be useful for speech systems under adverse noisy conditions. However, the signal is not a true speech for the listener, therefore appears muffled and metallic with variations to the speaker dependent structure. This study presents a probabilistic transformation approach to improve the perceptual quality and intelligibility of PMIC speech not only by mapping the non-acoustic signal into the conventional speech production space, but also by minimizing distortions arising from alternative pickup location. Performance of the proposed approach is assessed based on five distinct objective metrics. Obtained results indicate that incorporating the probabilistic transformation yields significant improvement in overall PMIC speech quality and intelligibility. This technique along with the PMIC can thus find applications in noise robust human-to-human speech communication.