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<@U07FRRZH2GN> Is there any way to detect user sil...
# ask-ai
f
@icy-policeman-64898 Is there any way to detect user silence between conversation?
t
Thanks for reaching out, Abhishek. I'm an AI assistant and I'm here to help. Give me a moment while I research this topic.
Yes, there are ways to detect user silence between conversations. Here are a few methods: • Simple Silence Detection with Timer: You can use a timer to monitor the time since the user last spoke. If the silence exceeds a predefined threshold, you can trigger an action. For example, you can use a script like the one below:
Copy code
import asyncio
import time

SILENCE_THRESHOLD = 5  # seconds

async def entrypoint(ctx: JobContext):
    user_last_spoke_time = time.time()
    
    async def monitor_interaction():
        while True:
            if time.time() - user_last_spoke_time > SILENCE_THRESHOLD:
                <http://logger.info|logger.info>("silent for too long! disconnecting")
                try:
                    await ctx.room.disconnect()
                except Exception as e:
                    logger.exception("Error while ending call")
            await asyncio.sleep(1)
• Voice Activity Detection (VAD): This method uses models like Silero VAD to detect periods of silence in user input and apply heuristics to determine conversational pauses. • End-of-Utterance Detection: This advanced method combines VAD with conversational context to detect sustained silence and evaluate if the user has completed their turn. You can configure parameters like 
min_silence_duration
and 
min_endpointing_delay
for better accuracy. Let me know if you need further details or assistance with implementing any of these methods! Sources: How to detect and handle silence during calls | Turn detection and interruptions | LiveKit Docs | How does end-of-utterance detection work in conversations?
f
is there a parameter called user_last_spoke_time ?
t
Yes, the 
user_last_spoke_time
parameter is used in silence detection mechanisms. It is a timestamp variable that tracks when the user last spoke during a call. Here's how it works: • It is initially set to the current time when the function starts. • It gets updated whenever the user starts speaking (e.g., through an event handler like 
on_user_started_speaking
). • It is compared against the current time in a monitoring loop to determine if the silence threshold has been exceeded. • If the silence persists beyond the defined threshold (e.g., 
SILENCE_THRESHOLD
), an action like disconnecting the call can be triggered. Let me know if you need further clarification or assistance with implementing this! Sources: How to detect and handle silence during calls
f
@icy-policeman-64898 Voice Activity Detection (VAD): This method uses models like Silero VAD to detect periods of silence in user input and apply heuristics to determine conversational pauses. tell me how we can use VAD for silence between user and agent?
t
To use Voice Activity Detection (VAD) for detecting silence between a user and an agent, you can follow these steps: • Detecting Silence: VAD identifies periods of silence in the audio stream. For example, Silero VAD can be used to detect when the user has stopped speaking by monitoring the audio input for a minimum duration of silence. • Turn Detection: VAD is often combined with turn detection mechanisms. When silence exceeds a configured threshold (e.g., 
min_endpointing_delay
), it signals the end of a user's turn, allowing the agent to respond. • Improving Contextual Awareness: While basic VAD detects silence, it may not account for natural pauses in speech. To address this, LiveKit offers a turn detector model that incorporates conversational context, reducing interruptions during natural pauses. • Implementation: Both VoicePipelineAgent and MultimodalAgent in LiveKit use VAD for turn detection. You can configure parameters like 
min_endpointing_delay
to adjust the silence duration required to consider a turn complete. Let me know if you need further details or assistance with implementing VAD for your use case! Sources: Turn detection and interruptions | LiveKit Docs | AI voice agents | LiveKit Docs
f
@icy-policeman-64898 can we monitor user speech and agent speech for the last 10 seconds and then setup something like
t
Currently, I couldn't find specific details on monitoring both user and agent speech for the last 10 seconds. However, it is possible to implement such functionality by maintaining a rolling buffer of audio or speech activity data for both the user and the agent. This buffer can store the last 10 seconds of activity, which can then be analyzed to trigger specific actions based on the detected patterns. If you have a more specific use case or need guidance on implementation, feel free to share, and I’ll assist further!
f
@icy-policeman-64898 are there any atributes which i can use for monitoring speech activity for both user and agent?
t
To monitor speech activity for both the user and the agent, you can use the following attributes and events: • User Speech Activity Events: ◦ `user_started_speaking`: Triggered when the user begins speaking. ◦ `user_stopped_speaking`: Triggered when the user stops speaking. ◦ `user_speech_committed`: Triggered when the user's speech is committed to the chat context. • Agent Speech Activity Events: ◦ `agent_started_speaking`: Triggered when the agent begins speaking. ◦ `agent_stopped_speaking`: Triggered when the agent stops speaking. ◦ `agent_speech_committed`: Triggered when the agent's speech is committed to the chat context. ◦ `agent_speech_interrupted`: Triggered when the agent is interrupted while speaking. You can register callbacks for these events using the 
on()
method. For example:
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@agent.on("user_started_speaking")
def on_user_started_speaking(event):
    # Handle user started speaking event

@agent.on("agent_stopped_speaking")
def on_agent_stopped_speaking(event):
    # Handle agent stopped speaking event
Let me know if you need further assistance with implementing these events! Sources: livekit.agents.pipeline API documentation | VoicePipelineAgent | LiveKit Docs | VoicePipelineAgent | LiveKit Docs
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