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 journalConference articlepeer-review

2 Citations (Scopus)


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 for research purposes, along with the baseline TTS systems and an interactive demo.

Original languageEnglish
Pages (from-to)5511-5515
Number of pages5
JournalProceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH
Publication statusPublished - 2023
Externally publishedYes
Event24th International Speech Communication Association, Interspeech 2023 - Dublin, Ireland
Duration: Aug 20 2023Aug 24 2023


  • 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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