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- W4376456840 abstract "Text-to-Speech (TTS) synthesis for low-resource languages is an attractive research issue in academia and industry nowadays. Mongolian is the official language of the Inner Mongolia Autonomous Region and a representative low-resource language spoken by over 10 million people worldwide. However, there is a relative lack of open-source datasets for Mongolian TTS. Therefore, we make public an open-source multi-speaker Mongolian TTS dataset, named MnTTS2, for the benefit of related researchers. In this work, we prepare the transcription from various topics and invite three professional Mongolian announcers to form a three-speaker TTS dataset, in which each announcer records 10 h of speeches in Mongolian, resulting 30 h in total. Furthermore, we build the baseline system based on the state-of-the-art FastSpeech2 model and HiFi-GAN vocoder. The experimental results suggest that the constructed MnTTS2 dataset is sufficient to build robust multi-speaker TTS models for real-world applications. The MnTTS2 dataset, training recipe, and pretrained models are released at: https://github.com/ssmlkl/MnTTS2 ." @default.
- W4376456840 created "2023-05-14" @default.
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- W4376456840 date "2023-01-01" @default.
- W4376456840 modified "2023-10-13" @default.
- W4376456840 title "MnTTS2: An Open-Source Multi-speaker Mongolian Text-to-Speech Synthesis Dataset" @default.
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- W4376456840 doi "https://doi.org/10.1007/978-981-99-2401-1_28" @default.
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