A text to speech synthesis system for Maltese
The subject of this thesis covers a considerably varied multidisciplinary area which needs to be addressed to be able to achieve a text-to-speech synthesis system of high quality, in any language. This is the first time that such a system has been built for Maltese, and therefore, there was the additional problem of no computerised sources or corpora. However many problems and much of the system designs are common to all languages. This thesis focuses on two general problems. The first is that of automatic labelling of phonemic data, since this is crucial for the setting up of Maltese speech corpora, which in turn can be used to improve the system. A novel way of achieving such automatic segmentation was investigated. This uses a mixed parameter model with maximum likelihood training of the first derivative of the features across a set of phonetic class boundaries. It was found that this gives good results even for continuous speech provided that a phonemic labelling of the text is available. A second general problem is that of segment concatenation, since the end and beginning of subsequent diphones can have mismatches in amplitude, frequency, phase and spectral envelope. The use of-intermediate frames, build
Micallef, Paul
Computational linguistics; Text to speech system
A text to speech synthesis system for Maltese. The subject of this thesis covers a considerably varied multidisciplinary area which needs to be addressed to be able to achieve a text-to-speech synthesis system of high quality, in any language. This is the first time that such a system has been built for Maltese, and therefore, there was the additional problem of no computerised sources or corpora. However many problems and much of the system designs are common to all languages. This thesis focuses on two general problems. The first is that of automatic labelling of phonemic data, since this is crucial for the setting up of Maltese speech corpora, which in turn can be used to improve the system. A novel way of achieving such automatic segmentation was investigated. This uses a mixed parameter model with maximum likelihood training of the first derivative of the features across a set of phonetic class boundaries. It was found that this gives good results even for continuous speech provided that a phonemic labelling of the text is available. A second general problem is that of segment concatenation, since the end and beginning of subsequent diphones can have mismatches in amplitude, frequency, phase and spectral envelope. The use of-intermediate frames, build
text speech_synthesis system maltese subject cover considerably vary multidisciplinary area need_address able achieve text speech_synthesis system high_quality language first_time system build maltese therefore additional problem computerise source corpus however many problem much system design common language focus_two general problem first automatic label phonemic data since crucial set maltese speech corpus turn use improve system novel_way achieve automatic segmentation investigate mixed parameter model maximum likelihood training first derivative feature across set phonetic class boundary find give_good even continuous speech provide phonemic labelling text available second general problem segment since_end begin subsequent mismatch frequency phase spectral use intermediate frame build