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Tool to make high quality text to speech (tts) corpus from audio + text books.
First it transcribes audio with whisper ASR, saving all word level timestamps, then it alligns this transcription with original text, if distance is very small we consider it as match and add it to the dataset.
First, you should install several system dependancies:
On deb linux:
sudo apt install ffmpeg pandoc
on MacOSX:
brew install ffmpeg pandoc libmagic
Then you can install narizaka
:
pip install narizaka
or if you want to use the latest development version:
pip install git+https://github.com/patriotyk/narizaka.git
Also if you plan to modify sources:
git clone https://github.com/patriotyk/narizaka.git
pip install -e narizaka/
Flag -e
means that you can edit source files in the directory where you have cloned this project and they will be reflected when you run command narizaka
Every tagged commit on the main
branch, automatically generates and pushes image to the docker hub. So you can also pull this images:
docker pull patriotyk/narizaka:latest
Application as input accepts directory that contains audio data, it can be folder or subfolder of audio files, or just one audio file and there also should be one text file tat represents this audio.
This text file, can be any document that accepts pandoc
application.
Example:
narizaka test_data/farshrutka
Or
narizaka test_data
to process all books.
This repository contains test_data
that includes two audio and text books that you can use for testing.
FAQs
Tool to make high quality text to speech (tts) corpus from audio + text books.
We found that narizaka demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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