Abstract
Joint processing of throat and acoustic microphone recordings has been an attractive tool for robust speech processing. As the throat microphones record the acoustic sounds in the form of vibrations from skin attached sensors, they are more robust and highly correlated with the acoustic speech signal. We investigate the correlation of throat and acoustic microphone recordings. We propose a hidden Markov model (HMM) based structure to estimate acoustic speech features from throat speech features. The HMM based estimator will be used to estimate clean acoustic speech features from noisy throat and acoustic microphone recordings. Experimental results on acoustic speech feature estimation are provided.
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