van Niekerk, Daniel R;
Xu, Anqi;
Gerazov, Branislav;
Krug, Paul K;
Birkholz, Peter;
Halliday, Lorna;
Prom-on, Santitham;
(2023)
Simulating vocal learning of spoken language: Beyond imitation.
Speech Communication
, 147
pp. 51-62.
10.1016/j.specom.2023.01.003.
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Abstract
Computational approaches have an important role to play in understanding the complex process of speech acquisition, in general, and have recently been popular in studies of vocal learning in particular. In this article we suggest that two significant problems associated with imitative vocal learning of spoken language, the speaker normalisation and phonological correspondence problems, can be addressed by linguistically grounded auditory perception. In particular, we show how the articulation of consonant-vowel syllables may be learnt from auditory percepts that can represent either individual utterances by speakers with different vocal tract characteristics or ideal phonetic realisations. The result is an optimisation-based implementation of vocal exploration – incorporating semantic, auditory, and articulatory signals – that can serve as a basis for simulating vocal learning beyond imitation.
Type: | Article |
---|---|
Title: | Simulating vocal learning of spoken language: Beyond imitation |
Open access status: | An open access version is available from UCL Discovery |
DOI: | 10.1016/j.specom.2023.01.003 |
Publisher version: | https://doi.org/10.1016/j.specom.2023.01.003 |
Language: | English |
Additional information: | Copyright © 2023 The Author(s). This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
Keywords: | Speech production, Articulatory speech synthesis, Speech acquisition, Computational phonetics, Early vocal learning, Canonical babbling |
UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
URI: | https://discovery.ucl.ac.uk/id/eprint/10163859 |
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