add tts datasets doc, test=doc

docs/source/tts/tts_datasets.md

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