On the phonetic information in ultrasonic microphone signals

We study the phonetic information in the signal from an ultrasonic ldquomicrophonerdquo, a device that emits an ultrasonic wave toward a speaker and receives the reflected, Doppler-shifted signal. This can be used in addition to audio to improve automatic speech recognition. This work is an effort to better understand the ultrasonic signal, and potentially to determine a set of natural sub-word units. We present classification and clustering experiments on CVC and VCV sequences in speaker-dependent and multi-speaker settings. Using a set of ultrasonic spectral features and diagonal Gaussian models, it is possible to distinguish all consonants and most vowels. When clustering the confusion data, the consonant clusters mostly correspond to places and manners of articulation; the vowel data roughly clusters into high, low, and rounded vowels.