Gradio WebUI for creators and developers, featuring key TTS (Edge-TTS, kokoro) and zero-shot Voice Cloning (E2 & F5-TTS, CosyVoice), with Whisper audio processing, YouTube download, Demucs vocal isolation, and multilingual translation.

Using OpenAI's Whisper to automatically generate YouTube subtitles

Easily take an entire YouTube playlist and turn it into high quality transcripts using Whisper.

🔉 Youtube Videos Transcription with OpenAI's Whisper

Youtube GPT: OpenAI Whisper + Embedding + Davinci

A Gradio app that transcribes YouTube videos using audio extraction and OpenAI’s Whisper model.

AI-powered YouTube video dubbing pipeline. Automatically transcribes (Whisper), translates (Google), and generates neural dubbing (Edge-TTS) with smart audio-video synchronization and background music preservation.

Download YouTube video (or supply your own) and generate dual languange subtitles with OpenAI Whisper and translation API (GPT) 下载 YouTube 视频（或提供您自己的视频）并使用 Whisper 和翻译API (GPT) 生成双语字幕

Summarises podcasts from Youtube or Spotify using the new Whisper and GPT3 chat APIs from OpenAI

🎥 Youtube Video Summarizer and Question Answering App Using Whisper and Langchain

Insanely Fast Transcription: A Python-based utility for rapid audio transcription from YouTube videos or local files. Leverages GPU acceleration (CUDA/MPS) and the Whisper large-v3 model for blazing-fast, accurate transcriptions. Optimized for both Mac and NVIDIA systems.

GUI for Faster‑Whisper‑XXL transcription tool: download YouTube audio, transcribe local files, manage models, and export multiple formats with themes and auto yt‑dlp updates.

Gradio WebUI for whisper, faster-whisper, whisper-timestamped. Supports YouTube Downloader, Vocal Remover and Transcription.

YouTube Shorts videos generator using ChatGPT, Bing, GTTS, OpenAI's Whisper, MoviePy and Python

YouTube Video Summarization App built using open source LLM and Framework like Llama 2, Haystack, Whisper, and Streamlit. This app smoothly runs on CPU as Llama 2 model is in GGUF format loaded through Llama.cpp.

This project extracts audio from YouTube videos, converts speech to text using OpenAI Whisper, and summarizes the content using transformer-based NLP models to save time and improve content accessibility.

Multi-model video-to-text by combining embeddings from Flan-T5 + CLIP + Whisper + SceneGraph. The 'backbone LLM' is pre-trained from scratch on YouTube (YT-1B dataset).

CmdF is a terminal app that allows you to search and seek through YouTube videos using the power of whisper.cpp and fuzzy string matching.

一个集成 AI 转写功能的多平台视频处理工具，支持 YouTube、TikTok/抖音、Bilibili、Twitter 和寇享/koushare，提供 Chrome 插件，并基于 OpenAI Whisper 实现音视频转写。

YTWS is a simple CLI tool that downloads YouTube videos and creates subtitles quickly. It uses yt-dlp for downloading and faster-whisper for transcribing, making it easy and efficient to use.

Search YouTube transcripts from the terminal. No download, no API key, no whisper.

YouTube video summarization using Whisper audio transcription and GPT-based summaries.

YouTube 字幕下載與 Whisper AI 轉錄工具

FastAPI + Streamlit interface for OpenAI Whisper-large-v3 with youtube-to-mp3

A Chrome(ium) extension to replace YouTube's auto-captions with Whisper-generated ones

YouTube Video Summarization App built using open source LLM and Framework like Llama 2, Haystack, Whisper, and Streamlit. This app smoothly runs on CPU as Llama 2 model is in GGUF format loaded through Llama.cpp.

Create Youtube SRT with WhisperX using Google Colab

A caption generator where you input a youtube shorts/Tik Tok 9:16 video, and the whisper api generates captions and openCV displays them. Whispers accuracy depends on GPU power. Will implement interface to edit text position and style.

Multi-source transcript merging inspired by textual criticism — LLM adjudicates multiple Whisper, YouTube captions & external transcripts for higher quality. Includes speaker diarization and summarization.

AI-powered Auto-Clipper: automatically detects highlight segments from YouTube channels, Twitch/Kick live streams (via audience-retention data, chat spikes and timestamped comments), clips them with FFmpeg, generates subtitles using Whisper, and uploads them to a target YouTube channel. Includes a FastAPI + Celery backend, React + Tailwind frontend