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We present an open-source speech corpus for the Kazakh language. The Kazakhspeech corpus (KSC) contains around 332 hours of transcribed audio comprisingover 153,000 utterances spoken by participants from different regions and agegroups, as well as both genders. It was carefully inspected by native Kazakhspeakers to ensure high quality. The KSC is the largest publicly availabledatabase developed to advance various Kazakh speech and language processingapplications. In this paper, we first describe the data collection andpreprocessing procedures followed by a description of the databasespecifications. We also share our experience and challenges faced during thedatabase construction, which might benefit other researchers planning to builda speech corpus for a low-resource language. To demonstrate the reliability ofthe database, we performed preliminary speech recognition experiments. Theexperimental results imply that the quality of audio and transcripts ispromising (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 alsoreleased an ESPnet recipe for our speech recognition models.

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