Speech Processing and Acoustics

This course looks at a variety of topics relating to Speech Processing and Acoustics. These include the human vocal and auditory systems, the characteristics of speech signals (phonemes, prosody), IPA notation, the Lossless tube model of speech production, time and frequency domain representations of speech, window characteristics and time/frequency resolution tradeoffs. It also looks at the properties of digital filters, mean log response, resonance gain and bandwidth relations, bandwidth expansion transformation, all-pass filter characteristics, autocorrelation and covariance linear prediction of speech, optimality criteria in time and frequency domains, alternate LPC parametrisation, speech coding like: PCM, ADPCM, CELP, speech synthesis, language processing, prosody, diaphone and formant synthesis, time domain pitch and speech modification, speech recognition including the hidden Markov models and associated recognition and training algorithms, dynamic programming, language modelling, large vocabulary recognition and acoustic preprocessing for speech recognition