ClArTTS: An Open-Source Classical Arabic Text-to-Speech Corpus

Ajinkya Kulkarni; Atharva Kulkarni; Sara Abedalmon em Mohammad Shatnawi; Hanan Aldarmaki

doi:10.21437/Interspeech.2023-2224

ClArTTS: An Open-Source Classical Arabic Text-to-Speech Corpus

Ajinkya Kulkarni, Atharva Kulkarni, Sara Abedalmon em Mohammad Shatnawi, Hanan Aldarmaki

Research output: Contribution to journal › Conference article › peer-review

2 Citations (Scopus)

Abstract

We present a Classical Arabic Text-to-Speech (ClArTTS) corpus to facilitate the development of end-to-end TTS systems for the Arabic language. The speech is extracted from a LibriVox audiobook, which is then processed, segmented, and manually transcribed and annotated. The ClArTTS corpus contains about 12 hours of speech from a single male speaker sampled at 40100 Hz. In this paper, we describe the process of corpus creation, details of corpus statistics, and a comparison with existing resources. Furthermore, we develop two TTS systems based on Grad-TTS and Glow-TTS and illustrate the performance of the resulting systems via subjective and objective evaluations. The ClArTTS corpus is publicly available at www.clartts.com for research purposes, along with the baseline TTS systems and an interactive demo.

Original language	English
Pages (from-to)	5511-5515
Number of pages	5
Journal	Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH
Volume	2023-August
DOIs	https://doi.org/10.21437/Interspeech.2023-2224
Publication status	Published - 2023
Externally published	Yes
Event	24th International Speech Communication Association, Interspeech 2023 - Dublin, Ireland Duration: Aug 20 2023 → Aug 24 2023

Keywords

arabic speech corpus
corpus creation
text-to-speech

ASJC Scopus subject areas

Language and Linguistics
Human-Computer Interaction
Signal Processing
Software
Modelling and Simulation

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10.21437/Interspeech.2023-2224

Cite this

ClArTTS: An Open-Source Classical Arabic Text-to-Speech Corpus. / Kulkarni, Ajinkya; Kulkarni, Atharva; Shatnawi, Sara Abedalmon em Mohammad et al.
In: Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH, Vol. 2023-August, 2023, p. 5511-5515.

Research output: Contribution to journal › Conference article › peer-review

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title = "ClArTTS: An Open-Source Classical Arabic Text-to-Speech Corpus",

abstract = "We present a Classical Arabic Text-to-Speech (ClArTTS) corpus to facilitate the development of end-to-end TTS systems for the Arabic language. The speech is extracted from a LibriVox audiobook, which is then processed, segmented, and manually transcribed and annotated. The ClArTTS corpus contains about 12 hours of speech from a single male speaker sampled at 40100 Hz. In this paper, we describe the process of corpus creation, details of corpus statistics, and a comparison with existing resources. Furthermore, we develop two TTS systems based on Grad-TTS and Glow-TTS and illustrate the performance of the resulting systems via subjective and objective evaluations. The ClArTTS corpus is publicly available at www.clartts.com for research purposes, along with the baseline TTS systems and an interactive demo.",

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author = "Ajinkya Kulkarni and Atharva Kulkarni and Shatnawi, {Sara Abedalmon em Mohammad} and Hanan Aldarmaki",

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AU - Kulkarni, Ajinkya

AU - Kulkarni, Atharva

AU - Shatnawi, Sara Abedalmon em Mohammad

AU - Aldarmaki, Hanan

PY - 2023

Y1 - 2023

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AB - We present a Classical Arabic Text-to-Speech (ClArTTS) corpus to facilitate the development of end-to-end TTS systems for the Arabic language. The speech is extracted from a LibriVox audiobook, which is then processed, segmented, and manually transcribed and annotated. The ClArTTS corpus contains about 12 hours of speech from a single male speaker sampled at 40100 Hz. In this paper, we describe the process of corpus creation, details of corpus statistics, and a comparison with existing resources. Furthermore, we develop two TTS systems based on Grad-TTS and Glow-TTS and illustrate the performance of the resulting systems via subjective and objective evaluations. The ClArTTS corpus is publicly available at www.clartts.com for research purposes, along with the baseline TTS systems and an interactive demo.

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ER -

ClArTTS: An Open-Source Classical Arabic Text-to-Speech Corpus

Abstract

Keywords

ASJC Scopus subject areas

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