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how do I detect end of user speech and send multim...
# ask-ai
n
how do I detect end of user speech and send multimodal data along with the text?
t
Thanks for reaching out, rohit. I'm an AI assistant and I'm here to help. Give me a moment while I research this topic.
To help you detect when a user finishes speaking, you have a couple of great options: Speech-to-Text (STT) or Voice Activity Detection (VAD) systems. Here’s a quick overview: • STT: This will give you an 
END_OF_SPEECH
event once the user stops talking, using silence or endpointing signals from the STT provider. • VAD: This one detects a continuous silence in the audio stream and then emits an 
END_OF_SPEECH
event. When it comes to sending multimodal data along with text, LiveKit has you covered with several helpful features: • You can configure different modalities, like 
text_and_audio
, right in the session setup. • It supports sending transcriptions and useful metadata such as language, confidence scores, and timestamps through the 
send_transcription
method. • Plus, you can use RPC communication to send structured data, like End-of-Utterance (EOU) probabilities, in real-time. If you’re looking to send other types of data—like images or videos—you can do that too! Custom RPC methods or data tracks are perfect for transmitting this information alongside speech. Please feel free to reach out if you’d like more detailed guidance on how to implement any of these features. I’m here to help! Sources: agent/main.py | complex-agents/turn-taking/README.md | livekit-plugins/livekit-plugins-google/livekit/plugins/google/beta/realtime... | agents/src/vad.ts
n
how does the default livekit agent determine when to get a response
t
I'm glad you asked about how the default LiveKit agent decides when to respond! It uses a thoughtful combination of Voice Activity Detection (VAD), Speech-to-Text (STT), and some configurable end-of-speech settings to make sure it catches your cues just right: • It carefully watches for signals from VAD or STT that indicate the end of your utterance and then waits a minimum of 0.4 seconds (
min_endpointing_delay
) after noticing silence before it considers your turn finished. • If you stay silent a bit longer, it patiently waits up to a maximum of 6.0 seconds (
max_endpointing_delay
) before wrapping up your turn and crafting a response. • When using wake words like "hey casa," the agent is tuned to listen for that trigger phrase and then focuses on what you say right after it. These thoughtful steps help the agent respond at just the right moments during your conversation. If you'd like, I’d be happy to share more details or walk you through some examples—just let me know! Sources: livekit-agents/livekit/agents/voice/room_io/room_io.py | home_assistant/homeautomation.py
I don't have the answer you're looking for. You could also try asking your question: • in one of the other Slack channels or • to https://deepwiki.com/livekit/livekit_composite which is trained on all LiveKit source code If you find the answer, please post it here to help others!
n
in livekit, what client callback can we listen to to hook in taking a screenshot and passing it through
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