Speech Signal Extraction Method Based on Bayesian Estimation Using Air- and Bone-Conduction Sound in Speech Confusion

With the recent development of digital information technology, speech information recognition system has improved dramatically and is being applied in a wide range of fields. In order to improve the system efficiency, countermeasures measures against noise from the surrounding environment have become an important issue. In the previous study, we derived an algorithm to estimate speech signals by using air-conducted speech signal mixed with noise as observation and bone-conducted speech signal. In this research, we propose an algorithm to obtain more accurate estimation results by using not only air-conducted speech signal mixed with noise but also bone-conducted speech signal as observation values. The effectiveness of the proposed method was confirmed experimentally by applying it to mixed speech signals actually measured in surrounding noisy environment.