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Computer Science > Computation and Language

Title: ÌròyìnSpeech: A multi-purpose Yorùbá Speech Corpus

Abstract: We introduce \`{I}r\`{o}y\`{i}nSpeech, a new corpus influenced by the desire to increase the amount of high quality, contemporary Yor\`{u}b\'{a} speech data, which can be used for both Text-to-Speech (TTS) and Automatic Speech Recognition (ASR) tasks. We curated about 23000 text sentences from news and creative writing domains with the open license CC-BY-4.0. To encourage a participatory approach to data creation, we provide 5000 curated sentences to the Mozilla Common Voice platform to crowd-source the recording and validation of Yor\`{u}b\'{a} speech data. In total, we created about 42 hours of speech data recorded by 80 volunteers in-house, and 6 hours of validated recordings on Mozilla Common Voice platform. Our TTS evaluation suggests that a high-fidelity, general domain, single-speaker Yor\`{u}b\'{a} voice is possible with as little as 5 hours of speech. Similarly, for ASR we obtained a baseline word error rate (WER) of 23.8.
Comments: Accepted to LREC-COLING 2024
Subjects: Computation and Language (cs.CL); Sound (cs.SD); Audio and Speech Processing (eess.AS)
Cite as: arXiv:2307.16071 [cs.CL]
  (or arXiv:2307.16071v2 [cs.CL] for this version)

Submission history

From: David Adelani [view email]
[v1] Sat, 29 Jul 2023 20:42:50 GMT (18kb)
[v2] Wed, 27 Mar 2024 08:56:01 GMT (822kb,D)

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