whisper.cpp

Time : 2026-04-13

Introduction

What is whisper.cpp?

whisper.cpp is an efficient, lightweight automatic speech recognition (ASR) library developed by ggerganov, the creator of the ggml tensor library. It is a C++ port of OpenAI's Whisper speech recognition model. Its main advantage is that it runs efficiently on ordinary consumer-grade CPUs without requiring expensive GPUs or complex deep learning environments.

Key Features:

  1. Pure CPU Inference : whisper.cpp is deeply optimized for CPU execution, supporting x86 and ARM architectures, with special optimizations for Apple Silicon (M1/M2/M3) chips, achieving very fast inference speeds.

  2. No External Dependencies : The project is implemented in pure C/C++ and does not rely on large deep learning frameworks like PyTorch or TensorFlow, making compilation and deployment extremely lightweight.

  3. Multiple Model Sizes : Supports all model sizes of OpenAI Whisper (tiny / base / small / medium / large), allowing users to choose between accuracy and speed based on their needs.

  4. High Recognition Accuracy : Maintains the high accuracy of the original Whisper models while significantly lowering the hardware requirements, running smoothly even on embedded devices like the Raspberry Pi.

  5. Rich Output Formats : Supports output in plain text, timestamped subtitle formats (SRT, VTT), JSON, and more, making it easy to integrate into various applications.

  6. Real-Time Inference Support : Some versions and derivative projects support real-time microphone input, enabling use cases like live captioning and voice assistants.

Typical Use Cases:

  • Local speech-to-text (offline, privacy-preserving)
  • Automatic subtitle generation for videos
  • Meeting and lecture transcription
  • Speech recognition on embedded devices (Raspberry Pi, NAS, etc.)
  • Backend ASR engine for other applications

Example Usage:

Project Repository: https://github.com/ggerganov/whisper.cpp

With its lightweight, efficient, and cross-platform design, whisper.cpp has become a popular choice for local offline speech recognition.

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Github:https://github.com/ggml-org/whisper.cpp

Direct Download: bf065638-3417-4e90-a8bc-72aaf2eaf2b2

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Reference tutorial

Method to generate video subtitles with whisper.cpp Windows version:

You need to convert the audio/video into a specific format using ffmpeg for conversion:

ffmpeg -i "input.mp4" -ar 16000 -ac 1 -c:a pcm_s16le audio.wav

Here, the -i parameter specifies the path of the input video.

You need to download the gguf format whisper model here: https://huggingface.co/ggerganov/whisper.cpp , for example, the ggml-medium.en-q8_0.bin model.

After downloading, extracting, and switching to the whisper.cpp directory, enter the following command to generate subtitles in srt format:

whisper-cli.exe -m "/path/to/ggml-medium.en-q8_0.bin" -f "/path/to/audio.wav" -osrt

Here, the -m parameter specifies the location of the whisper model you downloaded, the -f parameter specifies the location of the audio to be recognized, and -osrt indicates outputting an srt subtitle file.