#Speech recognition

This project enhances podcast accessibility through AI-generated transcripts and chapter segmentation. With features like speech-to-text, topic-based chaptering, and subtitle support, it facilitates easy navigation and search. Developed using Open AI and Google APIs, it leverages React, Python, and Flask for sophisticated backend and frontend interaction, demonstrating its innovative capability despite Spotify API's access limits.

Jarvis is an open-source, intelligent voice-command assistant designed to recognize human speech and execute a variety of commands. Compatible with Ubuntu 20.04 and Python 3.8, it offers skills such as opening web pages, playing music, managing volume, and reporting weather conditions. Users can customize its responses, switch input modes between text and speech, and configure the assistant's name. Integration with APIs like OpenWeatherMap and WolframAlpha ensures dynamic information retrieval. The setup process includes downloading the repository, configuring API keys, and starting the assistant with a simple command. Jarvis supports new skill integration, keeps command history in MongoDB for an enhanced user experience, and is licensed under MIT, encouraging community-driven development and easy contribution.

The repository provides a comprehensive framework for third-party libraries to integrate with Hugging Face through custom Docker environments. Utilizing a starter template from `docker_images/common`, libraries can add functionalities and leverage Hugging Face's hardware. It elaborates on the processes of container customization, model testing, Docker caching optimization, and necessary validations, outlining available tasks such as speech recognition and text generation for standardizing API integrations.