KazakhTTS: An Open-Source Kazakh Text-to-Speech Synthesis Dataset

• URL: http://arxiv.org/abs/2104.08459v1
• Date: Sat, 17 Apr 2021 05:49:57 GMT
• Title: KazakhTTS: An Open-Source Kazakh Text-to-Speech Synthesis Dataset
• Authors: Saida Mussakhojayeva, Aigerim Janaliyeva, Almas Mirzakhmetov, Yerbolat Khassanov, Huseyin Atakan Varol
• Abstract summary: This paper introduces a high-quality open-source speech synthesis dataset for Kazakh, a low-resource language spoken by over 13 million people worldwide. The dataset consists of about 91 hours of transcribed audio recordings spoken by two professional speakers. It is the first publicly available large-scale dataset developed to promote Kazakh text-to-speech applications in both academia and industry.
• Score: 4.542831770689362
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: This paper introduces a high-quality open-source speech synthesis dataset for Kazakh, a low-resource language spoken by over 13 million people worldwide. The dataset consists of about 91 hours of transcribed audio recordings spoken by two professional speakers (female and male). It is the first publicly available large-scale dataset developed to promote Kazakh text-to-speech (TTS) applications in both academia and industry. In this paper, we share our experience by describing the dataset development procedures and faced challenges, and discuss important future directions. To demonstrate the reliability of our dataset, we built baseline end-to-end TTS models and evaluated them using the subjective mean opinion score (MOS) measure. Evaluation results show that the best TTS models trained on our dataset achieve MOS above 4 for both speakers, which makes them applicable for practical use. The dataset, training recipe, and pretrained TTS models are freely available.

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