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

Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics, pages 697–706 April 19 - 23, 2021. ©2021 Association for Computational Linguistics 697 A Crowdsourced Open-Source Kazakh Speech Corpus and Initial Speech Recognition Baseline Yerbolat Khassanov, Saida Mussakhojayeva, Almas Mirzakhmetov, Alen Adiyev, Mukhamet Nurpeiissov and Huseyin Atakan Varol Institute of Smart Systems and Artificial Intelligence (ISSAI), Nazarbayev University, Nur-Sultan, Kazakhstan {yerbolat.khassanov, saida.mussakhojayeva, almas.mirzakhmetov, alen.adiyev, mukhamet.nurpeiissov, ahvarol}@nu.edu.kz Abstract We present an open-source speech corpus for the Kazakh language. The Kazakh speech cor- pus (KSC) contains around 332 hours of tran- scribed audio comprising over 153,000 utter- ances spoken by participants from different re- gions 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 devel- oped to advance various Kazakh speech and language processing applications. In this pa- per, we first describe the data collection and preprocessing procedures followed by a de- scription 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 ex- periments. The experimental results imply that the quality of audio and transcripts is promis- ing (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. 1 Introduction We present an open-source Kazakh speech corpus (KSC) constructed to advance the development of speech and language processing applications for the Kazakh language. Kazakh is an agglutinative language with vowel harmony and belongs to the family of Turkic languages. During the Soviet pe- riod, the Kazakh language was overwhelmed by the Russian language, which caused a decline in Kazakh language usage (Dave, 2007). In the 1990s, it was declared an official language of Kazakhstan, and many initiatives were launched to increase the number of Kazakh speakers. Today, it is spoken by over 10 million people in Kazakhstan and by over 3 million people in other countries1. By introducing the KSC, we aim to accelerate the penetration of the Kazakh language into the Internet of things (IoT) technologies and to promote research in Kazakh speech processing applications. Although several Kazakh speech corpora have been presented (Makhambetov et al., 2013; Shi et al., 2017; Mamyrbayev et al., 2019), there is no generally accepted common corpus. Most of them are either publicly unavailable or contain an insufficient amount of data to train reliable mod- els. Especially, these databases are too small for building recent end-to-end models, which are ex- tremely data hungry (Hannun et al., 2014). Con- sequently, different research groups usually con- duct their experiments on internally collected data, which prevents the reproducibility and comparison of different approaches. To address the aforementioned limitations, we created the KSC, containing around 332 hours of transcribed …

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