# A Crowdsourced Open-Source Kazakh Speech Corpus and Initial Speech Recognition Baseline

arXiv: https://arxiv.org/abs/2009.10334 · HTML: https://mlsanity.com/paper/2009.10334/

## Key facts

- Cited by 14 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 22 Sep 2020.

## Built on by (most cited first, 14 of 14)

- [ZIPA: A family of efficient models for multilingual phone recognition](https://mlsanity.com/paper/2505.23170/) (2025)
- [KazNERD: Kazakh Named Entity Recognition Dataset](https://mlsanity.com/paper/2111.13419/) (2021)
- [POWSM: A Phonetic Open Whisper-Style Speech Foundation Model](https://mlsanity.com/paper/2510.24992/) (2025)
- [KazakhTTS: An Open-Source Kazakh Text-to-Speech Synthesis Dataset](https://mlsanity.com/paper/2104.08459/) (2021)
- [KazakhTTS2: Extending the Open-Source Kazakh TTS Corpus With More Data, Speakers, and Topics](https://mlsanity.com/paper/2201.05771/) (2022)
- [Recent Advancements and Challenges of Turkic Central Asian Language Processing](https://mlsanity.com/paper/2407.05006/) (2024)
- [USC: An Open-Source Uzbek Speech Corpus and Initial Speech Recognition Experiments](https://mlsanity.com/paper/2107.14419/) (2021)
- [A Study of Multilingual End-to-End Speech Recognition for Kazakh, Russian, and English](https://mlsanity.com/paper/2108.01280/) (2021)
- [Multilingual Text-to-Speech Synthesis for Turkic Languages Using Transliteration](https://mlsanity.com/paper/2305.15749/) (2023)
- [How I Built ASR for Endangered Languages with a Spoken Dictionary](https://mlsanity.com/paper/2510.04832/) (2025)
- [Lost in Speech: Trilingual Spoken Hallucination Detection Across Audio and Transcripts](https://mlsanity.com/paper/2608.24707/) (2026)
- [A baseline model for computationally inexpensive speech recognition for Kazakh using the Coqui STT framework](https://mlsanity.com/paper/2107.10637/) (2021)
- [Training Autoregressive Speech Recognition Models with Limited in-domain Supervision](https://mlsanity.com/paper/2210.15135/) (2022)
- [The Faetar Benchmark: Speech Recognition in a Very Under-Resourced Language](https://mlsanity.com/paper/2409.08103/) (2024)

## Abstract (arXiv)

We present an open-source speech corpus for the Kazakh language. The Kazakh speech corpus (KSC) contains around 332 hours of transcribed audio comprising over 153,000 utterances spoken by participants from different regions and age groups, as well as both genders. It was carefully inspected by native Kazakh speakers to ensure high quality. The KSC is the largest publicly available database developed to advance various Kazakh speech and language processing applications. In this paper, we first describe the data collection and preprocessing procedures followed by a description of the database specifications. We also share our experience and challenges faced during the database construction, which might benefit other researchers planning to build a speech corpus for a low-resource language. To demonstrate the reliability of the database, we performed preliminary speech recognition experiments. The experimental results imply that the quality of audio and transcripts is promising (2.8% character error rate and 8.7% word error rate on the test set). To enable experiment reproducibility and ease the corpus usage, we also released an ESPnet recipe for our speech recognition models.