# Google Crowdsourced Speech Corpora and Related Open-Source Resources for Low-Resource Languages and Dialects: An Overview

arXiv: https://arxiv.org/abs/2010.06778 · HTML: https://mlsanity.com/paper/2010.06778/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 14 Oct 2020.

## Built on by (most cited first, 5 of 5)

- [USAT: A Universal Speaker-Adaptive Text-to-Speech Approach](https://mlsanity.com/paper/2404.18094/) (2024)
- [Remastering Divide and Remaster: A Cinematic Audio Source Separation Dataset with Multilingual Support](https://mlsanity.com/paper/2407.07275/) (2024)
- [ELAICHI: Enhancing Low-resource TTS by Addressing Infrequent and Low-frequency Character Bigrams](https://mlsanity.com/paper/2410.17901/) (2024)
- [A Discriminative Hierarchical PLDA-based Model for Spoken Language Recognition](https://mlsanity.com/paper/2201.01364/) (2022)
- [Voice of India: A Large-Scale Benchmark for Real-World Speech Recognition in India](https://mlsanity.com/paper/2604.19151/) (2026)

## 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.