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VAD.INFERENCE_DONE events are not getting fired, w...
# ask-ai
l
VAD.INFERENCE_DONE events are not getting fired, which leads to voice assistant interrupting the user.
t
Thanks for reaching out, Deepak. I'm an AI assistant and I'm here to help. Give me a moment while I research this topic.
The issue with 
VAD.INFERENCE_DONE
events not firing could be due to several factors. Here are some steps to troubleshoot and resolve the problem: 1. VAD Configuration: Ensure the Voice Activity Detection (VAD) is properly initialized and configured with the correct sample rate and parameters. 2. Event Handling: Verify that the 
on_vad_inference_done
callback is registered in the 
RecognitionHooks
. Without this, the event won't be handled. 3. Silence Thresholds: Adjust parameters like 
min_silence_duration
and 
activation_threshold
to ensure they match the audio input characteristics. 4. Turn Detection Mode: Ensure the mode is set to 
vad
or 
stt
. Modes like 
manual
or 
realtime_llm
may ignore some VAD events. 5. Audio Input: Confirm that audio is being correctly fed into the VAD stream. Without audio, the VAD cannot process data. 6. Event Emission: Check the implementation of the 
VADStream
class to ensure events are emitted correctly. 7. Buffering and Latency: Investigate any buffering or latency issues that might delay or prevent event emission. If you need further assistance with any of these steps, let me know, and I can provide more detailed guidance.
l
for most of the conversations, its fired properly. For few of them its not
t
Sometimes, the 
VAD.INFERENCE_DONE
events might not fire consistently, and this can happen for a few reasons: 1. Audio Input Variations: Differences in audio quality, sample rates, or frame synchronization can make the events a bit unpredictable. 2. System Load: If your system is really busy or inference takes longer than usual, events might get delayed or even skipped. 3. Buffer Management: If the audio data buffer gets too full or isn’t handled properly, some events could be missed. 4. Configuration Settings: Sometimes tweaking parameters like 
min_speech_duration
and 
min_silence_duration
helps things line up better with your audio. 5. Threshold-based Detection: When audio signals hover around detection thresholds, the results can jump around a bit. 6. Concurrency Issues: Async operations or race conditions in how VAD runs might cause some inconsistencies. Here are a few things you can try to smooth things out: • Take another look at your VAD settings and adjust them to fit your audio input more closely. • Keep an eye on system performance to make sure inference isn’t getting slowed down by heavy load. • Double-check how your buffers are managed and make sure audio frames are handled correctly. • See if certain conversations have unique audio traits that might be causing the hiccups. If you want, I’m here to help with any specific tweaks or dig deeper into the issue together. Sources: tests/test_vad.py | agents/src/pipeline/pipeline_agent.ts
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