Speakers Talking Foreign Languages in a Multi-lingual TTS System

Hanzlíček, Zdeněk; Vít, Jakub; Řezáčková, Markéta

doi:10.1007/978-3-030-83527-9_42

Cited by 1 publication

(2 citation statements)

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“…The cross-lingual segmentation performance, evaluated without the pause boundaries and the invalid phones, is presented in Table 13. Our experiments have shown that the resulting segmentation can be used for unit selection or neural speech synthesis 63 when excluding invalid phones.…”

Section: F I G U R E 12mentioning

confidence: 97%

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Using LSTM neural networks for cross‐lingual phonetic speech segmentation with an iterative correction procedure

Hanzlíček,

Matoušek,

Vít

2023

Computational Intelligence

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This article describes experiments on speech segmentation using long short‐term memory recurrent neural networks. The main part of the paper deals with multi‐lingual and cross‐lingual segmentation, that is, it is performed on a language different from the one on which the model was trained. The experimental data involves large Czech, English, German, and Russian speech corpora designated for speech synthesis. For optimal multi‐lingual modeling, a compact phonetic alphabet was proposed by sharing and clustering phones of particular languages. Many experiments were performed exploring various experimental conditions and data combinations. We proposed a simple procedure that iteratively adapts the inaccurate default model to the new voice/language. The segmentation accuracy was evaluated by comparison with reference segmentation created by a well‐tuned hidden Markov model‐based framework with additional manual corrections. The resulting segmentation was also employed in a unit selection text‐to‐speech system. The generated speech quality was compared with the reference segmentation by a preference listening test.

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Section: F I G U R E 12mentioning

confidence: 97%

“…We proposed a simple iterative procedure that helps to improve the segmentation accuracy so that it is usable in a concatenative TTS system, for which precise segmentation is very important. 62 The procedure described has recently been utilized in our TTS system 61,63 when adding new voices in new languages.…”

Section: Research Objectivementioning

confidence: 99%