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Speech production and perception
Problems of automatic speech recognition
Techniques for signal processing
6 other sections not shown
acoustic adjustment window Ainsworth applications auditory automatic speech recognition branching factor cepstrum codebook consists database demisyllables developed digital signal processor digits duration dynamic programming dynamic programming algorithm employed endpoint energy error rate estimated feature vectors filter bank formant frequencies formant transitions frame fricatives function fundamental frequency hidden Markov models hypothesiser input isolated word knowledge sources language lexical linear prediction analysis linear prediction coefficients machine match microphone noise normalisation obtained operation parameters peaks perception performance phoneme plosives possible problem processing processor produced Rabiner recog recognition accuracy recognition rate represented resonator samples score second formant Section segment semantic semivowels sentence sequence shown in Fig Sonagrams speaker speaker-independent spectral spectrum speech signal speech waveform spoken syllables syntactic synthesiser systolic array task technique templates test utterance test word tion vector quantisation vocabulary vocal tract voice voiceless vowels warping waveform word recogniser