Pre-processing input text: improving pronunciation for the fluent Dutch text-to-speech synthesizer
To improve pronunciation of the Fluent Dutch Text-To-Speech Synthesiser, two pre-processors were built that try to detect problematic cases in input texts and solve these automatically if possible. One pre-processor examines the pronounceability of surnames and company names by checking whether their initial and final two-letter combinations can be handled by the grapheme-to-phoneme rules of the Fluency TTS system, and correcting those automatically when and if possible. Also, common disambiguous abbreviations are properly expanded. The second pre-processor tries to realise pronounceable forms... Mehr ...
Verfasser: | |
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Dokumenttyp: | conference contribution |
Erscheinungsdatum: | 1998 |
Verlag/Hrsg.: |
Institute of Phonetic Sciences
University of Amsterdam Amsterdam |
Sprache: | unknown |
Permalink: | https://search.fid-benelux.de/Record/base-27061318 |
Datenquelle: | BASE; Originalkatalog |
Powered By: | BASE |
Link(s) : | http://hdl.handle.net/11245/1.423852 |
To improve pronunciation of the Fluent Dutch Text-To-Speech Synthesiser, two pre-processors were built that try to detect problematic cases in input texts and solve these automatically if possible. One pre-processor examines the pronounceability of surnames and company names by checking whether their initial and final two-letter combinations can be handled by the grapheme-to-phoneme rules of the Fluency TTS system, and correcting those automatically when and if possible. Also, common disambiguous abbreviations are properly expanded. The second pre-processor tries to realise pronounceable forms for numbers that do not have a straightforward pronunciation. Structural and contextual information is used in an attempt to determine to what category a number belongs, and each number is expanded according to the pronunciation conventions of its category. It can be said that these pre-processors are a useful aid in offline pronounceability examination (for names) and improvement of performance at run-time (for numbers), although ambiguity and redundancy in the input text illustrate the need for semantic and syntactic parsing to approach human text interpretation skills.