LatestMachine LearningWhisper.cpp: How to Use OpenAIs Whisper Model in C/C++ for Efficient Speech Recognition 0 like December 22, 2024Share this postLast Updated on December 24, 2024 by Editorial TeamAuthor(s): Md Monsur ali Originally published on Towards AI. OpenAIs Whisper in C/C++ for Accurate, High-Speed Transcription Without Internet Step-by-Step TutorialThis member-only story is on us. Upgrade to access all of Medium. GitHub | LinkedIn | Medium | Ko-fiSource: https://github.com/ggerganov/whisper.cppIn 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 OpenAIs 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.Join thousands of data leaders on the AI newsletter. Join over 80,000 subscribers and keep up to date with the latest developments in AI. From research to projects and ideas. If you are building an AI startup, an AI-related product, or a service, we invite you to consider becoming asponsor. Published via Towards AITowards AI - Medium Share this post