Speech characterization from a rough spectral analysis
J. Lienard · 2005
Tracking and identifying the formants in order to perform speech recognition is a time-consuming, error full and speaker-dependent operation. It is proposed to characterize the speech short-term spectrum with a reduced number of parameters (4 to 7) computed from a rough spectral analysis. These parameters permit a correct classification of the steady-state French speech sounds (vowels, including nasals, and unvoiced fricatives) pronounced by different speakers. A word recognition experiment based on the same parameters gives good results with words differing from each other by one phoneme only (single speaker, one learning pass).