Google Crowdsourced Speech Corpora and Related Open-Source Resources for Low-Resource Languages and Dialects: An Overview
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Abstract (arXiv)
This paper presents an overview of a program designed to address the growing need for developing freely available speech resources for under-represented languages. At present we have released 38 datasets for building text-to-speech and automatic speech recognition applications for languages and dialects of South and Southeast Asia, Africa, Europe and South America. The paper describes the methodology used for developing such corpora and presents some of our findings that could benefit under-represented language communities.
Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). First posted on arXiv 14 Oct 2020.
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Citing papers per year: 2022: 1; 2023: 0; 2024: 3; 2025: 0; 2026: 1.
5 papers.
- 2024USAT: A Universal Speaker-Adaptive Text-to-Speech Approachcited by 6
- 2024Remastering Divide and Remaster: A Cinematic Audio Source Separation Dataset with Multilingual Supportcited by 5
- 2024ELAICHI: Enhancing Low-resource TTS by Addressing Infrequent and Low-frequency Character Bigramscited by 2
- 2022A Discriminative Hierarchical PLDA-based Model for Spoken Language Recognitioncited by 1
- 2026Voice of India: A Large-Scale Benchmark for Real-World Speech Recognition in Indiacited by 0
- 2026Voice of India: A Large-Scale Benchmark for Real-World Speech Recognition in India21 Apr 2026
- 2024ELAICHI: Enhancing Low-resource TTS by Addressing Infrequent and Low-frequency Character Bigrams23 Oct 2024
- 2024Remastering Divide and Remaster: A Cinematic Audio Source Separation Dataset with Multilingual Support9 Jul 2024
- 2024USAT: A Universal Speaker-Adaptive Text-to-Speech Approach28 Apr 2024
- 2022A Discriminative Hierarchical PLDA-based Model for Spoken Language Recognition4 Jan 2022