Or you could use Soniox Real-time (supports 60 languages) which natively supports endpoint detection - the model is trained to figure out when a user's turn ended. This always works better than VAD.

https://soniox.com/docs/stt/rt/endpoint-detection

Soniox also wins the independent benchmarks done by Daily, the company behind Pipecat.

https://www.daily.co/blog/benchmarking-stt-for-voice-agents/

You can try a demo on the home page:

https://soniox.com/

Disclaimer: I used to work for Soniox

Edit: I commented too soon. I only saw VAD and immediately thought of Soniox which was the first service to implement real time endpoint detection last year.

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nicktikhonov 3 hours ago | parent [-]

If you read the post, you'll see that I used Deepgram's Flux. It also does endpointing and is a higher-level abstraction than VAD.

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lukax 3 hours ago | parent [-]

Sorry, I commented too soon. Did you also try Soniox? Why did you decide to use Deepgram's Flux (English only)?

	▲	nicktikhonov 3 hours ago \| parent [-]
		I didn't try Soniox, but I made a note to check it out! I chose Flux because I was already using Deepgram for STT and just happened to discover it when I was doing research. It would definitely be a good follow-up to try out all the different endpointing solutions to see what would shave off additional latency and feel most natural. Another good follow-up would be to try PersonaPlex, Nvidia's new model that would completely replace this architecture with a single model that does everything: https://research.nvidia.com/labs/adlr/personaplex/