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Abstract
This paper first introduces a newly-recorded high quality Romanian speech corpus designed for speech synthesis, called "RSS", along with Romanian front-end text processing modules and HMM-based synthetic voices built from the corpus. All of these are now freely available for academic use in order to promote Romanian speech technology research. The RSS corpus comprises 3500 training sentences and 500 test sentences uttered by a female speaker and was recorded using multiple microphones at 96 kHz sampling frequency in a hemianechoic chamber. The details of the new Romanian text processor we have developed are also given.
Using the database, we then revisit some basic configuration choices of speech synthesis, such as waveform sampling frequency and auditory frequency warping scale, with the aim of improving speaker similarity, which is an acknowledged weakness of current HMM-based speech synthesisers. As we demonstrate using perceptual tests, these configuration choices can make substantial differences to the quality of the synthetic speech. Contrary to common practice in automatic speech recognition, higher waveform sampling frequencies can offer enhanced feature extraction and improved speaker similarity for HMM-based speech synthesis.
Original language | English |
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Pages (from-to) | 442-450 |
Number of pages | 9 |
Journal | Speech Communication |
Volume | 53 |
Issue number | 3 |
DOIs | |
Publication status | Published - Mar 2011 |
Keywords / Materials (for Non-textual outputs)
- Speech synthesis
- HTS
- Romanian
- HMMs
- Sampling frequency
- Auditory scale
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Dive into the research topics of 'The Romanian speech synthesis (RSS) corpus: Building a high quality HMM-based speech synthesis system using a high sampling rate'. Together they form a unique fingerprint.Activities
- 1 Invited talk
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EACL 2014 keynote: Speech synthesis needs YOU!
Simon King (Speaker)
29 Apr 2014Activity: Academic talk or presentation types › Invited talk
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