narizaka

Name	narizaka JSON
Version	1.0.3 JSON
	download
home_page
Summary	Tool to make high quality text to speech (tts) corpus from audio + text books.
upload_time	2023-10-30 18:37:09
maintainer
docs_url	None
author
requires_python	>=3.8
license	MIT
keywords	tts text-to-speech audio corpus
VCS
bugtrack_url
requirements	No requirements were recorded.
Travis-CI	No Travis.
coveralls test coverage	No coveralls.

            # Narizaka
Tool to make high quality text to speech (tts) corpus from audio + text books.

## How it works
First it splits audio files in to small segments 5-15 seconds, then it iterates over each segment
and transcribes with whisper ASR and alligns this transcription with original text, if distance is very small we consider it as match and add it to the dataset.


## Installation
```
pip install narizaka
```

Or 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`

## How to use

Application accepts two inputs. First one, it is audio data, that can be folder of audio files, or just one audio file.
And text, that can be any document that accepts `pandoc` application.
Example:
```
narizaka -a test_data/farshrutka -t test_data/Farshrutka.fb2
```
This repository contains `test_data` that includes audio and text books that you can use for testing.

            

Raw data

            {
    "_id": null,
    "home_page": "",
    "name": "narizaka",
    "maintainer": "",
    "docs_url": null,
    "requires_python": ">=3.8",
    "maintainer_email": "",
    "keywords": "tts,text-to-speech,audio corpus",
    "author": "",
    "author_email": "Serhiy Stetskovych <patriotyk+narizaka@gmail.com>",
    "download_url": "https://files.pythonhosted.org/packages/50/25/05103641dd1f87fcd9289ccf5a13624b59dbc3aafca53e14f0aad7ac2eda/narizaka-1.0.3.tar.gz",
    "platform": null,
    "description": "# Narizaka\nTool to make high quality text to speech (tts) corpus from audio + text books.\n\n## How it works\nFirst it splits audio files in to small segments 5-15 seconds, then it iterates over each segment\nand transcribes with whisper ASR and alligns this transcription with original text, if distance is very small we consider it as match and add it to the dataset.\n\n\n## Installation\n```\npip install narizaka\n```\n\nOr if you plan to modify sources:\n\n```\ngit clone https://github.com/patriotyk/narizaka.git\npip install -e narizaka/\n```\nFlag `-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`\n\n## How to use\n\nApplication accepts two inputs. First one, it is audio data, that can be folder of audio files, or just one audio file.\nAnd text, that can be any document that accepts `pandoc` application.\nExample:\n```\nnarizaka -a test_data/farshrutka -t test_data/Farshrutka.fb2\n```\nThis repository contains `test_data` that includes audio and text books that you can use for testing.\n",
    "bugtrack_url": null,
    "license": "MIT",
    "summary": "Tool to make high quality text to speech (tts) corpus from audio + text books.",
    "version": "1.0.3",
    "project_urls": {
        "Bug Tracker": "https://github.com/patriotyk/narizaka/issues",
        "Homepage": "https://github.com/patriotyk/narizaka"
    },
    "split_keywords": [
        "tts",
        "text-to-speech",
        "audio corpus"
    ],
    "urls": [
        {
            "comment_text": "",
            "digests": {
                "blake2b_256": "7d10053da09e71183b07c18571584fddee8afc28bb2884390cbaccb6d548bae4",
                "md5": "0d8d35c693e4d20e2c062ba7250b4089",
                "sha256": "eab0783107c6524fd39da5a7c8dc2890f4953f8c95e6565e71d7812fd723211c"
            },
            "downloads": -1,
            "filename": "narizaka-1.0.3-py3-none-any.whl",
            "has_sig": false,
            "md5_digest": "0d8d35c693e4d20e2c062ba7250b4089",
            "packagetype": "bdist_wheel",
            "python_version": "py3",
            "requires_python": ">=3.8",
            "size": 8772,
            "upload_time": "2023-10-30T18:37:07",
            "upload_time_iso_8601": "2023-10-30T18:37:07.865017Z",
            "url": "https://files.pythonhosted.org/packages/7d/10/053da09e71183b07c18571584fddee8afc28bb2884390cbaccb6d548bae4/narizaka-1.0.3-py3-none-any.whl",
            "yanked": false,
            "yanked_reason": null
        },
        {
            "comment_text": "",
            "digests": {
                "blake2b_256": "502505103641dd1f87fcd9289ccf5a13624b59dbc3aafca53e14f0aad7ac2eda",
                "md5": "9e9cb4b97e4490ac91f8a9a336316189",
                "sha256": "0b341c6f18c42f01bdb17167e65081c21a2e3a54c6998ebc5cc43407312b5333"
            },
            "downloads": -1,
            "filename": "narizaka-1.0.3.tar.gz",
            "has_sig": false,
            "md5_digest": "9e9cb4b97e4490ac91f8a9a336316189",
            "packagetype": "sdist",
            "python_version": "source",
            "requires_python": ">=3.8",
            "size": 9227,
            "upload_time": "2023-10-30T18:37:09",
            "upload_time_iso_8601": "2023-10-30T18:37:09.662984Z",
            "url": "https://files.pythonhosted.org/packages/50/25/05103641dd1f87fcd9289ccf5a13624b59dbc3aafca53e14f0aad7ac2eda/narizaka-1.0.3.tar.gz",
            "yanked": false,
            "yanked_reason": null
        }
    ],
    "upload_time": "2023-10-30 18:37:09",
    "github": true,
    "gitlab": false,
    "bitbucket": false,
    "codeberg": false,
    "github_user": "patriotyk",
    "github_project": "narizaka",
    "travis_ci": false,
    "coveralls": false,
    "github_actions": true,
    "requirements": [],
    "lcname": "narizaka"
}