Two uses for syllables in a speech recognition system
Many acoustic and phonetic studies attest to the value of the syllable as a unit of linguistic description. Phenomena of coarticulation and assimilation often occur within a syllable, and the acoustic realisation of some phenomes also correlate with their position in a syllable. For example, stops are more often released at the beginning of a syllable than at the end, and the clear allophone of 'I' is also more often found at the beginning than the dark allophone. Despite the prevalence of such studies, there have been relatively few attempts to apply this knowledge in a speech recognition system. This is what is attempted here. The matter is investigated by modifying the CSTR speech recogniser, which is not based on syllables. It is a modular system, with a separate front end and back end. The front end uses hidden Markov models to produce a phoneme lattice, and the back end uses a dynamic programming algorithm to construct words out of the lattice. Syllable information is incorporated in both the front and the back end. Because the system is modular, the effects of incorporating syllables can be studied independently. The experiments in the front end centre on the choice of a set of allophones that correlate
Blokland, Robert Arthur
Two uses for syllables in a speech recognition system. Many acoustic and phonetic studies attest to the value of the syllable as a unit of linguistic description. Phenomena of coarticulation and assimilation often occur within a syllable, and the acoustic realisation of some phenomes also correlate with their position in a syllable. For example, stops are more often released at the beginning of a syllable than at the end, and the clear allophone of 'I' is also more often found at the beginning than the dark allophone. Despite the prevalence of such studies, there have been relatively few attempts to apply this knowledge in a speech recognition system. This is what is attempted here. The matter is investigated by modifying the CSTR speech recogniser, which is not based on syllables. It is a modular system, with a separate front end and back end. The front end uses hidden Markov models to produce a phoneme lattice, and the back end uses a dynamic programming algorithm to construct words out of the lattice. Syllable information is incorporated in both the front and the back end. Because the system is modular, the effects of incorporating syllables can be studied independently. The experiments in the front end centre on the choice of a set of allophones that correlate
syllable speech_recognition system many acoustic phonetic_study attest value syllable unit linguistic_description phenomena assimilation often occur_within syllable acoustic realisation also correlate position syllable example stop often release begin syllable end clear also often find begin dark despite prevalence study relatively attempts apply knowledge speech_recognition system attempt here matter investigate modify speech recogniser base syllable modular system separate front end back end front end use hidden model produce phoneme back end dynamic program algorithm construct word syllable information incorporate front back end system modular effect incorporate syllable study independently front end centre choice set correlate