there some issue happning. I have to speak louder then only it is transcripting

Thanks for reaching out, Sandeep. I'm an AI assistant and I'm here to help. Give me a moment while I research this topic.

these are my current session = AgentSession( vad=ctx.proc.userdata["vad"], _min_interruption_words_=1, userdata=UserData(), _min_endpointing_delay_=0.5, _max_tool_steps_=10, _user_away_timeout_=SILENCE_THRESHOLD )

Hey there! Quick question - could you help me confirm the current value of the vad parameter in your session configuration? I'm wondering if this might be what's behind the issue you're experiencing. Let me know what you see, and we'll figure this out together! 😊

these are my current settings AgentSession( vad=ctx.proc.userdata["vad"], _min_interruption_words_=1, userdata=UserData(), _min_endpointing_delay_=0.5, _max_tool_steps_=10, _user_away_timeout_=SILENCE_THRESHOLD )

Hey there! I'm wondering if you could share the exact value you've set for ctx.proc.userdata["vad"] in your setup. Knowing this might help us figure out if the VAD threshold could be playing a role in what you're experiencing. 😊

proc.userdata["vad"] = silero.VAD.load()

Hey there! 👋 Having trouble with transcription sensitivity? No worries—I've got some friendly tips to help you get your audio settings just right. Think of these settings like fine-tuning a really smart listening buddy. Here's how you can make your transcription system more responsive: 1. activation_threshold (Default: 0.5): - Want to catch those softer whispers? Just lower this value a bit. - Example:

vad = silero.VAD.load(activation_threshold=0.3)

2. min_speech_duration (Default: 0.05): - Catch even the tiniest speech moments by reducing this value. - Example:

vad = silero.VAD.load(min_speech_duration=0.02)

3. min_silence_duration (Default: 0.4): - Make your system react faster when someone stops talking. - Example:

vad = silero.VAD.load(min_silence_duration=0.2)

4. prefix_padding_duration (Default: 0.5): - Trim down those extra milliseconds at the start of speech chunks. 5. sample_rate (Default: 16000): - Boost your audio quality with a higher sample rate. Here's a super-sensitive configuration that might just do the trick:

from livekit.plugins import silero

vad = silero.VAD.load(
    activation_threshold=0.3,        # Lower threshold for quiet speech
    min_speech_duration=0.02,        # Detect very short utterances
    min_silence_duration=0.2,        # Faster end-of-speech detection
    prefix_padding_duration=0.3,     # Less padding for faster processing
    sample_rate=16000,               # Higher sample rate for better quality
    force_cpu=True
)

Pro tip: You can also tweak these settings on the fly using the

update_options()

method:

vad.update_options(
    activation_threshold=0.4,
    min_silence_duration=0.15
)

Play around with these settings—every voice and environment is unique! Find what works best for you, and happy transcribing! 🎙️✨ Sources: livekit-plugins/livekit-plugins-silero/livekit/plugins/silero/vad.py | Silero VAD plugin | LiveKit Docs | main.py

some times it is not able to understand single words sentences like 10 or no or yes

To improve transcription accuracy for single-word sentences like "yes," "no," or "10," I've got some friendly tips that can help you fine-tune your Voice Activity Detection (VAD) settings. Think of these like little adjustments that'll make your audio recognition super precise! 1. Reduce Minimum Speech Duration: - Let's catch those super short utterances by lowering the

min_speech_duration

parameter. - Example:

min_speech_duration=0.02

(default is 0.05). 2. Adjust Silence Detection: - We want to make sure we're not cutting off those quick words, so we'll reduce the

min_silence_duration

parameter. - Example:

min_silence_duration=0.3

(default is 0.4). 3. Lower Activation Threshold: - This helps us pick up even quieter or shorter speech by tweaking the

activation_threshold

parameter. - Example:

activation_threshold=0.3

(default is 0.5). 4. Reduce Prefix Padding: - Let's trim down the padding at the start of speech chunks to focus right on the good stuff. - Example:

prefix_padding_duration=0.2

. 5. Use a Higher Sample Rate: - Pro tip: Set the sample rate to 16kHz for super accurate short utterance detection! Here's a friendly example configuration that'll help you nail those single-word detections:

from livekit.plugins import silero

# Optimized VAD for single-word sentences
vad = silero.VAD.load(
    min_speech_duration=0.02,      # Detect very short speech
    min_silence_duration=0.3,      # Don't wait too long for silence
    prefix_padding_duration=0.2,   # Reduced padding
    activation_threshold=0.3,      # More sensitive detection
    sample_rate=16000              # Higher sample rate for accuracy
)

And hey, if you want to tweak things on the fly, you can use the

update_options()

method:

vad.update_options(
    min_speech_duration=0.02,
    min_silence_duration=0.3,
    activation_threshold=0.3
)

These little adjustments should help you capture those single-word sentences like a pro! Need any more help? I'm right here – just give me a shout! 😊 Sources: Silero VAD plugin | LiveKit Docs | livekit-plugins/livekit-plugins-baseten/livekit/plugins/baseten/stt.py