# SPRING-INX: A Multilingual Indian Language Speech Corpus by SPRING Lab, IIT Madras

arXiv: https://arxiv.org/abs/2310.14654 · HTML: https://mlsanity.com/paper/2310.14654/

## Key facts

- Cited by 11 papers in the map (data through 14 Oct 2026).
- Builds on 2 of its 3 references that are in the map.
- First posted on arXiv 23 Oct 2023.

## Builds on (most cited first, 2 of 2)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [ESPnet: End-to-End Speech Processing Toolkit](https://mlsanity.com/paper/1804.00015/) (2018)

## Built on by (most cited first, 11 of 11)

- [LAHAJA: A Robust Multi-accent Benchmark for Evaluating Hindi ASR Systems](https://mlsanity.com/paper/2408.11440/) (2024)
- [Empowering Low-Resource Language ASR via Large-Scale Pseudo Labeling](https://mlsanity.com/paper/2408.14026/) (2024)
- [NIRANTAR: Continual Learning with New Languages and Domains on Real-world Speech Data](https://mlsanity.com/paper/2507.00534/) (2025)
- [Benchmarking Automatic Speech Recognition for Indian Languages in Agricultural Contexts](https://mlsanity.com/paper/2602.03868/) (2026)
- [Breaking the Script Barrier: Enabling Automatic Alignment for PoS-based ASR Error Analysis in Non-Latin Scripts](https://mlsanity.com/paper/2605.28438/) (2026)
- [Multilingual Multi-Speaker Unit Vocoders: A Systematic Analysis of Discrete Speech Representations](https://mlsanity.com/paper/2606.06740/) (2026)
- [TamilEOT: A Dataset and Model for Semantic End-of-Turn Detection in Tamil Telephone Speech](https://mlsanity.com/paper/2609.05631/) (2026)
- [Model-Agnostic and Language-Agnostic Voice Pipeline Improvement for the Agriculture Domain](https://mlsanity.com/paper/2609.20504/) (2026)
- [Vimarsha: Faithful ASR Evaluation for Indian Languages with Demographic Diversity, In-the-Wild Audio and Spelling Variations](https://mlsanity.com/paper/2609.24199/) (2026)
- [Anuvani-LID: Robust and Calibrated Spoken Language Identification for Indian Languages](https://mlsanity.com/paper/2610.20263/) (2026)
- [Anuvani-Diarization: Zero Shot Speaker Diarization and Annotation Conventions Across 22 Languages](https://mlsanity.com/paper/2610.20327/) (2026)

## Abstract (arXiv)

India is home to a multitude of languages of which 22 languages are recognised by the Indian Constitution as official. Building speech based applications for the Indian population is a difficult problem owing to limited data and the number of languages and accents to accommodate. To encourage the language technology community to build speech based applications in Indian languages, we are open sourcing SPRING-INX data which has about 2000 hours of legally sourced and manually transcribed speech data for ASR system building in Assamese, Bengali, Gujarati, Hindi, Kannada, Malayalam, Marathi, Odia, Punjabi and Tamil. This endeavor is by SPRING Lab , Indian Institute of Technology Madras and is a part of National Language Translation Mission (NLTM), funded by the Indian Ministry of Electronics and Information Technology (MeitY), Government of India. We describe the data collection and data cleaning process along with the data statistics in this paper.