Automatic Speech Recognition Pipeline with Whisper model

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Whisper Update

Hello Hailo Community!

We are excited to share that we’ve been working on an automatic speech recognition pipeline based on the Whisper-tiny model, running it on a Raspberry Pi with our Hailo-8/8L AI accelerator.
Given how much interest this topic has generated in the community, we wanted to provide a quick status update.

Our focus so far has been on optimizing performance to make the pipeline faster and more efficient for real-time applications. The attached video showcases some of our initial results, and we’re actively refining the system to improve latency, resource usage, and overall efficiency.

This is not an official release yet, but we plan to share a working application with the Community soon. In addition, we are also evaluating larger Whisper variants to explore the trade-offs between accuracy and performance.

If you have any thoughts, suggestions, or experience with similar optimizations, we’d love to hear from you! Stay tuned for more updates as we continue improving the pipeline!

watch the video

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Hello,
Are you planning to share the project and the source code? If you are, is there any ETA?

Thank you

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@Constantine_Vainstei a Python example using the Whisper-tiny model has been released in the Hailo Application Code Examples repository. Further improvements will be released in the next weeks. Feel free to test it, as well as to join our Community Challenge!

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Very cool - i got this working.
Are there some instructions on how to get/train/convert whisper tiny models for other languages?
Is there a repository that shows how the en hef model was created?

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