Any other model other than the turn detection model that supports more languauges ? and can be used with livkit

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

but if we integrate stt like deepgram and assembly ai or azure stt or elveln labs stt how would be configure the agent so the interruption is done and turn detection is good ?

Thanks for reaching out! Could you please let me know which STT provider you're planning to use (like Deepgram, AssemblyAI, Azure STT, or Eleven Labs)? Also, it would be helpful to understand if you’re looking for some guidance on setting up the agent to handle real-time interruptions or if you’re aiming to improve the accuracy of turn detection. I’m here to help you every step of the way!

ddepgram

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!

class TTS(tts.TTS): def __init__( self, *, voice_id: str = DEFAULT_VOICE_ID, voice_settings: NotGivenOr[VoiceSettings] = NOT_GIVEN, model: TTSModels | str = "eleven_turbo_v2_5", encoding: NotGivenOr[TTSEncoding] = NOT_GIVEN, api_key: NotGivenOr[str] = NOT_GIVEN, base_url: NotGivenOr[str] = NOT_GIVEN, streaming_latency: NotGivenOr[int] = NOT_GIVEN, inactivity_timeout: int = WS_INACTIVITY_TIMEOUT, auto_mode: NotGivenOr[bool] = NOT_GIVEN, word_tokenizer: NotGivenOr[tokenize.WordTokenizer | tokenize.SentenceTokenizer] = NOT_GIVEN, enable_ssml_parsing: bool = False, chunk_length_schedule: NotGivenOr[list[int]] = NOT_GIVEN, # range is [50, 500] http_session: aiohttp.ClientSession | None = None, language: NotGivenOr[str] = NOT_GIVEN, sync_alignment: bool = True, ) -> None: why is there * ? can we pass fields that are actually not defiend here ?