Improving pronunciation by analogy for text-to-speech applications
R.I. Damper, Yannick Marchand · ePrints Soton (University of Southampton) · 1998
This paper extends previous work on pronunciation by analogy (PbA) in several directions. PbA is a data-driven method for converting letters to sound, with potential application to next-generation text-to-speech systems. We experiment with a range of methods for matching letter patterns in input words to those in the system dictionary when building a pronunciation lattice. We give preliminary consideration to deriving lexical stress for input words. Common errors are analysed: these mostly involve vowel letters and phonemes. An output is not necessarily guaranteed in PbA -- the so-called silence problem. We report on a simple but effective strategy for silence avoidance. Finally, we introduce the idea of using different strategies in combination to improve performance. 1. INTRODUCTION Modern text-to-speech (TTS) systems use look-up in a large dictionary as the primary strategy to determine the pronunciation of input words. However, it is not possible to list exhaustively all the word...