microsoft / microsoft/onnxruntime-inference-examples
Help for improvisation in ort-example
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- C++
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Description
Hello, thank you very much for this wonderful repo. I really appreciate your effort. I tried the ort-whisper example of JavaScript and it works flawlessly. While I made more to do this in real time rather than uploading audio files for transcription it works but I discovered that there was a delay in the transcribing process. Could someone maybe explain why? or suggest how to improve.
model I'm using openai/whisper-tiny.en
Contributor guide
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First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start with the ort-whisper JavaScript example and compare its file-upload flow with the real-time transcription approach described in the issue. Measure where the delay occurs, then document or implement a practical improvement and verify that real-time transcription responds with lower latency.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- javascript
- Domain
- audio-video-rtc, machine-learning
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100