Adaptation for Soft Whisper Recognition Using a Throat Microphone

This paper describes various adaptation methods applied to recognizing soft whisper recorded with a throat microphone. Since the amount of adaptation data is small and the testing data is very different from the training data, a series of adaptation methods is necessary. The adaptation methods include: maximum likelihood linear regression, feature-space adaptation, and re-training with downsampling, sigmoidal low-pass filter, or linear multivariate regression. With these adaptation methods, the word error rate improves from 99.3% to 32.9%.