Thorsten-Voice/README.md
2020-09-23 18:05:38 +02:00

6.6 KiB

Introduction

Many smart voice assistants like Amazon Alexa, Google Home, Apple Siri and Microsoft Cortana use cloud services to offer their (base) functionality.

As some people have privacy concerns using these services there are some (open source) projects trying to build offline and/or privacy aware alternatives.

But speech recognition and text synthesis still requires cloud services for providing these in a decent quality.

MyCroft AI

https://mycroft.ai/

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.

Mozilla

Mozilla works on these really important aspects for free and open human machine voice interaction.

STT - speech to text

https://commonvoice.mozilla.org/

"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.

TTS - text to speech

https://github.com/mozilla/tts

"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.

And?!

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.

Please read some personal words before downloading the dataset

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.

So hopefully my voice is used in this manner to make this world a better place for all of us :-).

tl;dr Please don't use for evil!

Dataset "thorsten"

Samples of my voice

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.

Dataset information

  • ljspeech-1.1 structure
  • 22.668 recorded phrases (wav files)
  • more than 23 hours of pure audio
  • samplerate 22.050Hz
  • mono
  • normalized to -24dB
  • phrase length (min/avg/max): 2 / 52 / 180 chars
  • no silence at beginning/ending
  • avg spoken chars per second: 14
  • sentences with question mark: 2.780
  • sentences with exclamation mark: 1.840

text length vs. mean audio duration text length vs. median audio duration text length vs. STD text length vs. number instances signal noise ratio bokeh

Dataset evolution

As decribed in the pdf document (evolution of thorsten dataset) this dataset consists of three recording phases.

  • phase1: Recorded with a cheap usb microphone
  • phase2: Recorded with a good microphone
  • phase3: Recorded with same good microphone but longer phrases (> 100 chars)

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 csv file.

Download information

Download size: 2,7GB

Version Description Date Link
thorsten-de-v01 Initial version 2020-06-28 Google Drive Download v01
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

Trained tacotron2 model "thorsten"

If you trained a model on "thorsten" dataset please file an issue with some information on it. Sharing a trained model is highly appreciated.

Trained models (TODO)

Folder Date Link Description
thorsten-taco2-ddc-v0.1 to do to do to do

Feel free to file an issue if you ...

  • have improvements on dataset
  • use my TTS voice in your project(s)
  • want to share your trained "thorsten" model
  • get to know about any abuse usage of my voice

Special thanks

I want to thank all open source communities for providing great projects.

Just to name some nice guys who joined me on this tts-roadtrip:

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.

Without his amazing support this dataset (in it's current way) would not exists.

Thank you Dominik (@domcross / https://github.com/domcross/)

Links

We'll hear us in future :-)

Thorsten