Metadata-Version: 2.1
Name: google-text-to-speech
Version: 0.1.4
Summary: A text-to-speech conversion tool using Google Translate API
Home-page: https://gitlab.com/labsoft-ai/google-translate-tts
Author: Momcilo Krunic
Author-email: momcilo.krunic@labsoft.ai
License: MIT
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
License-File: LICENSE

![img](images/google_translate.png)

# Google Translate TTS

The `google_text_to_speech` package is a Python-based solution designed to provide versatile and user-friendly text-to-speech (TTS) capabilities. Leveraging the Google Translate TTS API, it enables users to convert written text into spoken words in various languages, catering to a wide range of applications.

## Update PyPI 

https://pypi.org/project/google-text-to-speech

1. Delete `dist` folder if exist in project directory
2. Increment version number in `setup.py`
3. Build the package: `python setup.py sdist bdist_wheel`
4. Install Twine: `pip install twine`
5. Upload Package to TestPyPI: `twine upload --repository testpypi dist/*`- Check TestPyPI to see if your package is listed correctly.
6. Upload Package to PyPI: `twine upload dist/*`

NOTE: *These steps [should be automated](https://gitlab.com/labsoft-ai/google-translate-tts/-/issues/3) through [Gitlab actions](.gitlab-ci.yml).*

## Directory tree structure

![dir_tree](images/dir_tree.png)

## Key Features

* **Multiple Language Support:** Utilizes Google's TTS service to offer speech synthesis in numerous languages.
* **Handling of Large Texts:** Splits long texts into sentences to avoid limitations related to URL length and TTS service constraints.
* **Real-Time Audio Playback:** Converts text to speech in real-time, with the capability to play the audio immediately.
* **Concurrency and Resource Management:** Implements threading to manage audio playback and file operations simultaneously, ensuring smooth performance and optimal resource usage.

## Technologies

* **Python:** The module is written in Python, making it versatile and easy to integrate into various applications.
* **External Libraries:** Uses `requests` for API calls and `playsound` for audio playback, along with standard libraries like `re` for text processing.
* **Google Translate TTS API:** Leverages this API for reliable and high-quality text-to-speech conversion.

## Potential Use Cases

* **Language Learning Tools:** Assists in pronunciation and language learning by providing auditory examples.
* **Accessibility Tools:** Helps in creating applications that can read out content to users with visual impairments.
* **Content Consumption:** Enables users to listen to articles, books, or any text content, enhancing the experience of consuming written material.


