Automatic pitch accent prediction for text-to-speech synthesis

Read, Ian and Cox, Stephen J. (2007) Automatic pitch accent prediction for text-to-speech synthesis. In: 8th Annual Conference of the International Speech Communication Association (Interspeech 2007), 2007-08-27 - 2007-08-31.

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Abstract

Determining pitch accents in a sentence is a key task for a text-to-speech (TTS) system. We describe some methods for pitch accent assignment which make use of features that contain information about a complete phrase or sentence, in contrast to most previous work which has focused on using features local to a syllable or word. Pitch accent prediction is performed using three different techniques: N-gram models of syllable sequences, dynamic programming to match sequences of features, and decision trees. Using a C4.5 decision tree trained on a wide range of features, most notably each word's orthographic form and information extracted from the syntactic parse of the sentence, our feature set achieved a balanced error rate of 46.6%. This compares with the feature set used in [11] which had a balanced error rate of 55.55%.

Item Type:	Conference or Workshop Item (Paper)
Faculty \ School:	Faculty of Science > School of Computing Sciences
UEA Research Groups:	Faculty of Science > Research Groups > Visual Computing and Signal Processing Faculty of Science > Research Groups > Smart Emerging Technologies (former - to 2025)
Depositing User:	Vishal Gautam
Date Deposited:	18 May 2011 12:54
Last Modified:	22 Apr 2023 02:44
URI:	https://ueaeprints.uea.ac.uk/id/eprint/21641
DOI:

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