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TTS from zero: Building synthetic voices for new languages (2009)
| Citations: | 4 - 0 self |
BibTeX
@TECHREPORT{Kominek09ttsfrom,
author = {John Kominek and Alexander I. Rudnicky},
title = {TTS from zero: Building synthetic voices for new languages},
institution = {},
year = {2009}
}
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Abstract
A developer wanting to create a speech synthesizer in a new voice for an under-resourced language faces hard problems. These include difficult decisions in defining a phoneme set and a laborious process of accumulating a pronunciation lexicon. Previously this has been handled through involvement of a language technologies expert. By definition, experts are in short supply. The goal of this thesis is to lower barriers facing a non-technical user in building “TTS from Zero. ” Our approach focuses on simplifying the lexicon building task by having the user listen to and select from a list of pronunciation alternatives. The candidate pronunciations are predicted by grapheme-to-phoneme (G2P) rules that are learned incrementally as the user works through the vocabulary. Studies demonstrate success for Iraqi, Hindi, German, and Bulgarian, among others. We compare various word selection strategies that the active learner uses to acquire maximally predictive rules. Incremental G2P learning enables iterative voice building. Beginning with 20 minutes of recordings, a bootstrapped synthesizer provides pronunciation examples for lexical review, which is fed into the next round of training with more recordings to create a larger, better voice... and so
Keyphrases
new language building synthetic voice difficult decision enables iterative voice building active learner user listen lexicon building task candidate pronunciation pronunciation lexicon non-technical user hard problem short supply laborious process next round bootstrapped synthesizer lexical review pronunciation alternative pronunciation example various word selection strategy new voice predictive rule phoneme set incremental g2p under-resourced language speech synthesizer
