Whisper.cpp: How to Use OpenAI’s Whisper Model in C/C++ for Efficient Speech Recognition

Author(s): Md Monsur ali

Originally published on Towards AI.

OpenAI’s Whisper in C/C++ for Accurate, High-Speed Transcription Without Internet — Step-by-Step Tutorial

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In the fast-evolving field of artificial intelligence and machine learning, the Whisper model developed by OpenAI has been a game-changer for automatic speech recognition. Designed to provide highly accurate transcription, translation, and multilingual speech recognition from the start, Whisper was a strong tool for developers working with speech-related applications. The original model, however, is implemented in Python, whereas many developers like to work with more lightweight, efficient, and portable implementations in their systems. Enter Whisper.cpp: an optimized C/C++ version of OpenAI’s model, Whisper, designed for fast, cross-platform performance.

In this post, we will take a closer look at what Whisper.cpp is, its main features, and how it can be used to bring speech recognition into applications such as voice assistants or real-time transcription systems.

Whisper.cpp is the OpenAI Whisper Model implementation in C and C++. It has been made, trying to achieve as much performance and portability as the model itself and aiming at running Whisper on platforms that cannot utilize the original Python model: it will make embedding much simpler in systems with restricted resources, like some embedded… Read the full blog for free on Medium.

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Published via Towards AI