whisper.cpp

In this video, I show you how to run OpenAI Whisper locally on your own machine using whisper.cpp — a fast, lightweight C++ implementation of the Whisper speech-to-text model. You will learn how to: - Run OpenAI Whisper locally (offline, no API key) - Use whisper.cpp for fast audio-to-text transcription - Download and use quantized Whisper models - Convert audio to 16-bit format using FFmpeg - Transcribe speech to text with timestamps - Generate word-level (token-level) transcription - Run whisper.cpp as a local speech-to-text server - Use Whisper for local AI and developer applications This setup works fully offline, protects your privacy, and does not require installing or writing C++ code. It is ideal for developers building speech-to-text tools, transcription pipelines, and audio-to-text applications using OpenAI Whisper. Technologies used in this video: - OpenAI Whisper (open-source speech recognition model) - whisper.cpp (fast local Whisper inference) - FFmpeg (audio preprocessing) This tutorial is perfect if you want: - Offline speech recognition - Local audio transcription - Fast and private speech-to-text - Whisper without internet or API costs Links to whisper.cpp, Whisper models, and commands used in this video are provided below: Links: - Whisper CPP Repo: https://github.com/ggml-org/whisper.cpp - Hugging Face Whisper GGML Models: https://huggingface.co/ggerganov/whisper.cpp/tree/main - FFmpeg Website: https://www.ffmpeg.org/ Commands: - Convert Audio to 16-bit: `ffmpeg -i myaudio.wav -ar 16000 -ac 1 -c:a pcm_s16le myaudio16.wav` - Run Whisper: `"whisper/whisper-cli.exe" -m ggml-large-v3-turbo-q8_0.bin -f myaudio16.wav` ("whisper/whisper-cli.exe" is path to executable) - Word Level Transcription: `"whisper/whisper-cli.exe" -m ggml-large-v3-turbo-q8_0.bin -f myaudio16.wav --max-len 1` ⏱️ Video Timestamps: 00:00 Run OpenAI Whisper Locally (Intro) 00:17 Setup & Install Whisper.cpp 02:53 Convert Audio to 16-Bit 03:32 Audio to Text Transcription 04:29 Word-by-Word Transcription 04:51 Running Whisper.cpp as a Server If this video helped you, consider subscribing to the channel for more AI, machine learning, and developer tutorials. BG Music Credit: @TheGreyRoom from Youtube Audio Library #whisper #openai #speechtotext #tts #coding #programming #machinelearning #ai #python #llm #audioprocessing #softwaredevelopment #softwareengineering #gpt #computerscience #datascience #opensource

Compare Whisper.cpp vs Standard Whisper in a head-to-head speed test and accuracy showdown. Discover which AI transcription engine delivers faster performance, lower memory usage, and real-world advantages for developers in 2026.