#It

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daring oxide
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To improve interruption detection, we could rely on Deepgram interim results. Specifically, if Deepgram returns a non-empty string for the given audio, we can consider it a valid interruption. This approach might provide a more accurate way to determine when a user is genuinely interrupting

onyx epochBOT
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Hi @daring oxide. I'm kapa.ai, your friendly support bot. I will try to answer your question by searching through the knowledge base. :wave:

broken lilyBOT
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Hey there! This channel allows you to ask Kapa.ai for assistance. But it looks like you haven't connected your Discord profile to your Deepgram account yet. You can do so at https://community.deepgram.com - by doing so, you'll be able to ask questions in #1115960287183511643 if you need human assistance!

onyx epochBOT
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Based on the knowledge sources provided, I don't have enough specific information to fully confirm or recommend using Deepgram's interim results for interruption detection in the way you've described. However, I can provide some relevant information about Deepgram's interim results feature that may be helpful:

Deepgram's interim results feature does provide preliminary transcripts during real-time streaming, which could potentially be used to detect when audio input is occurring. According to the Interim Results documentation, interim results are preliminary results provided during the real-time streaming process which can help with speech detection.

However, it's important to note a few things:

  1. Interim results are not enabled by default. You would need to explicitly enable this feature by setting interim_results=true in your API request.

  2. The accuracy of interim results may be lower than final results, as Deepgram continues to improve and correct transcriptions as more audio is processed.

  3. Deepgram does not currently offer a specific "interruption detection" feature. As mentioned in the migration best practices, interruption is "Not currently analyzed" by Deepgram.

While your approach of using non-empty strings from interim results to detect interruptions could potentially work, it's important to consider that this method might also pick up background noise or other non-interruption sounds. You might need to implement additional logic or filtering to distinguish between actual interruptions and other audio inputs.

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If interruption detection is a critical feature for your application, you may want to reach out to Deepgram's support team for more specific guidance or to discuss if there are any upcoming features that might better suit your needs.

Note: you can ask me a follow up question by @ mentioning me again :speech_balloon: