mirror of
https://github.com/thorstenMueller/Thorsten-Voice.git
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136 lines
6.6 KiB
Markdown
136 lines
6.6 KiB
Markdown
# Introduction
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Many smart voice assistants like Amazon Alexa, Google Home, Apple Siri and Microsoft Cortana use cloud services to offer their (base) functionality.
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As some people have privacy concerns using these services there are some (open source) projects trying to build offline and/or privacy aware alternatives.
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But speech recognition and text synthesis still requires cloud services for providing these in a decent quality.
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# MyCroft AI
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> https://mycroft.ai/
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MyCroft is a company developing an opensource voice assistant with a very nice and active community. But the stt/tts parts are still cloud based (eg. google services), even if requests are anonymized by a mycroft proxy in between. But integration with locally hosted services such as deepspeech (stt) or mimic/tacotron (tts) is possible.
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# Mozilla
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Mozilla works on these really important aspects for free and open human machine voice interaction.
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## STT - speech to text
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> https://commonvoice.mozilla.org/
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"STT" needs lots of audio training data by many speakers (women/men/kids) of all ages, dialects and in various audio quality levels. So any voice contribution for common voice project is highly welcome.
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## TTS - text to speech
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> https://github.com/mozilla/tts
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"TTS" needs lots of clean recordings by one speaker to train a model. Mozilla is developing a software stack for proper model training based on tacotron2 papers.
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# And?!
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I want to make the most personal contribution i can give and contribute my personal voice (**german**) for TTS training to the community for free usage.
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## Please read some personal words before downloading the dataset
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I contribute my voice as a person believing in a world where all people are equal. No matter of gender, sexual orientation, religion, skin color and geocoordinates of birth location. A global world where everybody is warmly welcome on any place on this planet and open and free knowledge and education is available to everyone.
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So hopefully my voice is used in this manner to make this world a better place for all of us :-).
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**tl;dr** Please don't use for evil!
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# Dataset "thorsten"
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## Samples of my voice
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To get an impression what my voice sounds to decide if it fits to your project i published some sample recordings, so no need to download complete dataset first.
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* [Das Teilen eines Benutzerkontos ist strengstens untersagt.](./samples/original_recording/recorded_sample_01.wav )
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* [Der Prophet spricht stets in Gleichnissen.](./samples/original_recording/recorded_sample_02.wav )
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* [Bitte schmeißt euren Müll nicht einfach in die Walachei.](./samples/original_recording/recorded_sample_03.wav )
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* [So etwas würde mir nie in den Sinn kommen.](./samples/original_recording/recorded_sample_04.wav )
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* [Sie klettert auf einen Stein und nimmt eine Denkerpose ein.](./samples/original_recording/recorded_sample_05.wav )
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* [Jede gute Küchenwaage hat eine Tara-Funktion.](./samples/original_recording/recorded_sample_06.wav )
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* [Jeden Gedanken kannst du hier loswerden.](./samples/original_recording/recorded_sample_07.wav )
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## Dataset information
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* ljspeech-1.1 structure
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* 22.668 recorded phrases (wav files)
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* more than 23 hours of pure audio
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* samplerate 22.050Hz
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* mono
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* normalized to -24dB
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* phrase length (min/avg/max): 2 / 52 / 180 chars
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* no silence at beginning/ending
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* avg spoken chars per second: 14
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* sentences with question mark: 2.780
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* sentences with exclamation mark: 1.840
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![text length vs. mean audio duration](./img/thorsten-de---datasetAnalysis1.png)
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![text length vs. median audio duration](./img/thorsten-de---datasetAnalysis2.png)
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![text length vs. STD](./img/thorsten-de---datasetAnalysis3.png)
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![text length vs. number instances](./img/thorsten-de---datasetAnalysis4.png)
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![signal noise ratio](./img/thorsten-de---datasetAnalysis5.png)
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![bokeh](./img/thorsten-de---datasetAnalysis6.png)
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## Dataset evolution
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As described in the pdf document ([evolution of thorsten dataset](./EvolutionOfThorstenDataset.pdf)) this dataset consists of three recording phases.
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* phase1: Recorded with a cheap usb microphone
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* phase2: Recorded with a good microphone
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* phase3: Recorded with same good microphone but longer phrases (> 100 chars)
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If you wanna use just a dataset subset (phase1 and/or phase2 and/or phase3) you can see which files belong to which recording phase in [recording quality](./RecordingQuality.csv) csv file.
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## Download information
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> Download size: 2,7GB
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Version | Description | Date | Link
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------------ | ------------- | ------------- | -------------
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thorsten-de-v01 | Initial version | 2020-06-28 | [Google Drive Download v01](https://drive.google.com/file/d/1yKJM1LAOQpRVojKunD9r8WN_p5KzBxjc/view?usp=sharing)
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thorsten-de-v02 | normalized to -24dB and split metadata.csv into shuffeled metadata_train.csv and metadata_val.csv | 2020-08-22 | [Google Drive Download v02](https://drive.google.com/file/d/1mGWfG0s2V2TEg-AI2m85tze1m4pyeM7b/view?usp=sharing)
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# Trained tacotron2 model "thorsten"
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If you trained a model on "thorsten" dataset please file an issue with some information on it. Sharing a trained model is highly appreciated.
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## Trained models (TODO)
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Folder | Date | Link | Description
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------------ | ------------- | ------------- | -------------
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thorsten-taco2-ddc-v0.1 | to do | to do | to do
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# Feel free to file an issue if you ...
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* have improvements on dataset
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* use my TTS voice in your project(s)
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* want to share your trained "thorsten" model
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* get to know about any abuse usage of my voice
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# Special thanks
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I want to thank all open source communities for providing great projects.
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Just to name some nice guys who joined me on this tts-roadtrip:
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* eltocino (https://github.com/el-tocino/)
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* erogol (https://github.com/erogol/)
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* gras64 (https://github.com/gras64/)
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* krisgesling (https://github.com/krisgesling/)
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* nmstoker (https://github.com/nmstoker)
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* othiele (https://discourse.mozilla.org/u/othiele/summary)
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* repodiac (https://github.com/repodiac)
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And last but not least i want to say a huge thank you to a special guy who supported me on this journey right from the beginning. Not just with nice words, but with his time, audio optimization knowhow and finally his gpu computing power.
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Without his amazing support this dataset (in it's current way) would not exists.
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Thank you Dominik (@domcross / https://github.com/domcross/)
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# Links
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* https://discourse.mozilla.org/t/contributing-my-german-voice-for-tts/48150
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* https://community.mycroft.ai/
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* https://github.com/MycroftAI/mimic-recording-studio
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* https://voice.mozilla.org/
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* https://github.com/mozilla/TTS
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(https://github.com/repodiac/tit-for-tat/tree/master/thorsten-TTS)
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* https://raw.githubusercontent.com/mozilla/voice-web/master/server/data/de/sentence-collector.txt
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We'll hear us in future :-)
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Thorsten
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