tailieunhanh - Báo cáo khoa học: "AN EXPERT SYSTEM FOR THE PRODUCTION OF PHONEME STRINGS FROM UNMARKED ENGLISH TEXT USING MACHINE-INDUCED RULES"

The speech synthesis group at the ComputerBased Education Research Laboratory (CERL) of the University of Illinois at Urbana-Champalgn is developing a diphone speech synthesis system based on pltch-adaptive short-tlme Fourier transforms. This system accepts the phonemic specification of an utterance along with pitch, time, and amplitude warping functions in order to produce high quality speech output from stored dlphone templates. | AN EXPERT SYSTEM FOR THE PRODUCTION OF PHONEME STRINGS FROM UNMARKED ENGLISH TEXT USING MACHINE-INDUCED RULES Alberto Maria Segre University of Illinois at Urbana-Champaign Coordinated Science Laboratory 1101 w. Springfield Urbana IL 61801 . Bruce Arne Sherwood University of Illinois at Urbana-Champaign Computer-based Education Research Laboratory 103 s. Mathews Urbana IL 61801 . Wayne B. Dickerson University of Illinois at Urbana-Champaign English as a Second Language Foreign Language Building 707 s7 Mathews Urbana IL 61801 . ABSTRACT The speech synthesis group at the ComputerBased Education Research Laboratory CERL of the University of Illinois at Urbana-Champaign is developing a diphone speech synthesis system based on pitch-adaptive short-time Fourier transforms. This system accepts the phonemic specification of an utterance along with pitch time and amplitude warping functions in order to produce high quality speech output from stored diphone templates. This paper describes the operation of a program which operates as a front end for the diphone speech synthesis system. The UTTER for Unmarked Text Transcription by Expert Rule system maps English text onto a phoneme string which Is then used as an input to the diphone speech synthesis system. The program Is a twotiered Expert System which operates first on the word level and then on the vowel or consonant cluster level. The system s knowledge about pronunciation is organized In two decision trees automatically generated by an induction algorithm on a dynamically specified training set of examples. In that they are often unable to cope with a letter pattern that maps onto more than one phoneme pattern. Extreme cases are those words which although differing in pronunciation share orthographic representations an analogous problem exists in speech recognition where words which share phonemic representations differ in orthographic representation and therefore possibly in semantic interpretation . A .