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76 lines
4.3 KiB
76 lines
4.3 KiB
# TTS Datasets
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<!--
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see https://openslr.org/
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-->
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## Mandarin
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- [CSMSC](https://www.data-baker.com/open_source.html): Chinese Standard Mandarin Speech Copus
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- Duration/h: 12
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- Number of Sentences: 10,000
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- Size: 2.14GB
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- Speaker: 1 female, ages 20 ~30
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- Sample Rate: 48 kHz、16bit
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- Mean Words per Clip: 16
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- [AISHELL-3](http://www.aishelltech.com/aishell_3)
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- Duration/h: 85
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- Number of Sentences: 88,035
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- Size: 17.75GB
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- Speaker: 218
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- Sample Rate: 44.1 kHz、16bit
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## English
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- [LJSpeech](https://keithito.com/LJ-Speech-Dataset/)
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- Duration/h: 24
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- Number of Sentences: 13,100
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- Size: 2.56GB
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- Speaker: 1, age 20 ~30
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- Sample Rate: 22050 Hz、16bit
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- Mean Words per Clip: 17.23
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- [VCTK](https://datashare.ed.ac.uk/handle/10283/3443)
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- Number of Sentences: 44,583
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- Size: 10.94GB
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- Speaker: 110
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- Sample Rate: 48 kHz、16bit
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- Mean Words per Clip: 17.23
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## Japanese
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<!--
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see https://sites.google.com/site/shinnosuketakamichi/publication/corpus
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-->
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- [tri-jek](https://sites.google.com/site/shinnosuketakamichi/research-topics/tri-jek_corpus): Japanese-English-Korean tri-lingual corpus
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- [JSSS-misc](https://sites.google.com/site/shinnosuketakamichi/research-topics/jsss-misc_corpus): misc tasks of JSSS corpus
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- [JTubeSpeech](https://github.com/sarulab-speech/jtubespeech): Corpus of Japanese speech collected from YouTube
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- [J-MAC](https://sites.google.com/site/shinnosuketakamichi/research-topics/j-mac_corpus): Japanese multi-speaker audiobook corpus
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- [J-KAC](https://sites.google.com/site/shinnosuketakamichi/research-topics/j-kac_corpus): Japanese Kamishibai and audiobook corpus
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- [JMD](https://sites.google.com/site/shinnosuketakamichi/research-topics/jmd_corpus): Japanese multi-dialect corpus
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- [JSSS](https://sites.google.com/site/shinnosuketakamichi/research-topics/jsss_corpus): Japanese multi-style (summarization and simplification) corpus
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- [RWCP-SSD-Onomatopoeia](https://www.ksuke.net/dataset/rwcp-ssd-onomatopoeia): onomatopoeic word dataset for environmental sounds
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- [Life-m](https://sites.google.com/site/shinnosuketakamichi/research-topics/life-m_corpus): landmark image-themed music corpus
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- [PJS](https://sites.google.com/site/shinnosuketakamichi/research-topics/pjs_corpus): Phoneme-balanced Japanese singing voice corpus
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- [JVS-MuSiC](https://sites.google.com/site/shinnosuketakamichi/research-topics/jvs_music): Japanese multi-speaker singing-voice corpus
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- [JVS](https://sites.google.com/site/shinnosuketakamichi/research-topics/jvs_corpus): Japanese multi-speaker voice corpus
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- [JSUT-book](https://sites.google.com/site/shinnosuketakamichi/publication/jsut-book): audiobook corpus by a single Japanese speaker
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- [JSUT-vi](https://sites.google.com/site/shinnosuketakamichi/publication/jsut-vi): vocal imitation corpus by a single Japanese speaker
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- [JSUT-song](https://sites.google.com/site/shinnosuketakamichi/publication/jsut-song): singing voice corpus by a single Japanese singer
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- [JSUT](https://sites.google.com/site/shinnosuketakamichi/publication/jsut): a large-scaled corpus of reading-style Japanese speech by a single speaker
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## Emotions
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### English
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- [CREMA-D](https://github.com/CheyneyComputerScience/CREMA-D)
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- [Seen and Unseen emotional style transfer for voice conversion with a new emotional speech dataset](https://kunzhou9646.github.io/controllable-evc/)
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- paper : [Seen and Unseen emotional style transfer for voice conversion with a new emotional speech dataset](https://arxiv.org/abs/2010.14794)
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### Mandarin
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- [EMOVIE Dataset](https://viem-ccy.github.io/EMOVIE/dataset_release )
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- paper: [EMOVIE: A Mandarin Emotion Speech Dataset with a Simple Emotional Text-to-Speech Model](https://arxiv.org/abs/2106.09317)
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- MASC
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- paper: [MASC: A Speech Corpus in Mandarin for Emotion Analysis and Affective Speaker Recognition](https://ieeexplore.ieee.org/document/4013501)
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### English && Mandarin
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- [Emotional Voice Conversion: Theory, Databases and ESD](https://github.com/HLTSingapore/Emotional-Speech-Data)
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- paper: [Emotional Voice Conversion: Theory, Databases and ESD](https://arxiv.org/abs/2105.14762)
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## Music
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- [GiantMIDI-Piano](https://github.com/bytedance/GiantMIDI-Piano)
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- [MAESTRO Dataset](https://magenta.tensorflow.org/datasets/maestro)
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- [tf code](https://www.tensorflow.org/tutorials/audio/music_generation)
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- [Opencpop](https://wenet.org.cn/opencpop/)
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