Combination of standard and throat microphones for robust speech recognition in highly noisy environments

We present a method to combine standard and throat microphone signals for noise-robust speech recognition. Our approach is to extend the probabilistic optimum filter (POF) mapping algorithm to estimate standard microphone clean speech feature vectors from both microphones’ noisy speech feature vectors. We tested the proposed approach in two noisy speech recognition tasks. In the first task we used a large-vocabulary continuous speech recognition system and noisy speech using either artificially added noise or noise recorded in an M1 tank cockpit. In the second task we used a real-time system and noisy speech recorded in a highly noisy environment, inside a HMMWV military vehicle. A noisecanceling microphone and a throat microphone were used in this task. Because of the highly adverse conditions in this second task we propose an extension of the combined microphone approach, which takes into account the level of noise captured by the throat microphone. The combined microphone approach significantly outperforms the single microphone approach in all the recognition experiments.