Noise suppression method by jointly using bone- and air-conducted speech signals

When applying speech recognition to actual circumstances such as inspection and maintenance operations in industrial factories to recording and reporting routines at construction sites where handwriting is difficult, some countermeasure methods for surrounding noise are indispensable. In this study, a signal processing method to remove the noise for actual speech signal is proposed by jointly using the measured data of bone- and air-conducted speech signals. More specifically, by introducing Bayes' theorem based on an orthogonal expansion expression of probability distribution, a new type of noise removal method is proposed. The effectiveness of the proposed method is confirmed by applying it to bone- and air-conducted speech measured in real environments under the existence of surrounding noise.