Event driven speech enhancement

A composite noise suppression algorithm is described in which the current speech event under analysis dictates which enhancement technique is to be used. Large temporal and spectral variations in speech have continued to inhibit satisfactory performance of single algorithm approaches to speech enhancement. This study examines the improvements which result from matching the restoration approach to the speech event. This study considers speech enhancement for speech recognition systems. Performance was measured according to the degree of improved phonemic separability as a function of the type of preproeessing. Phonemic separation is measured using an Itakura distance between phonetically marked templates and phonetically marked unknown speech. Results show that preprocessing the unknown noisy speech at a 10 aB signal-to-noise ratio reduces the percentage of false acceptances from 75% to 25% relative to the number measured using clean speech.