{"repo":"ckaytev/tgisper","free":true,"listed":false,"github":"https://github.com/ckaytev/tgisper","clone":"git clone https://github.com/ckaytev/tgisper.git","description":"Telegram bot with ASR","language":"Python","stars":23,"topics":["automatic-speech-recognition","openai-whisper","speech-recognition","telegram-bot","voice-to-text"],"license":"MIT","category":"machine-learning","readme_excerpt":"tgisper Whisper is a general-purpose speech recognition model. It is trained on a large dataset of diverse audio and is also a multi-task model that can perform multilingual speech recognition as well as speech translation and language identification. For more details: github.com/openai/whisper faster-whisper is a reimplementation of OpenAI's Whisper model using CTranslate2, which is a fast inference engine for Transformer models. For more details: github.com/guillaumekln/faster-whisper Tgisper is a bot for Telegram using a model from OpenAI to convert voice or audio messages to text. It is enough to record a voice message or send it to the bot from another chat and you're done! Usage Available models and languages Setup and run (Development Environment) Install command-line tool ffmpeg : Install poetry with following command: Install packages: Set environment variable: Starting the bot polling: With docker compose:","default_branch":null,"files":null,"tree":[],"storefront":"/r/ckaytev","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/ckaytev/tgisper/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}