#Hi,Testing a hindi AI voice agent. following issues. 1. Skips the initial introduction/questions
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AI-generated Answer for niranjan_20946
Thanks for the detailed report. Here are the specific ElevenLabs settings and docs-backed steps to address each point:
- Intro skipping
- Set a clear First message and keep it short; this is the first thing your agent will speak on every call. You can also override it per call if needed. (elevenlabs.io)
- Temporarily disable Interruptions during the introduction so background sounds or early speech don’t cut the intro off. Re‑enable after the intro if you want barge‑in. (elevenlabs.io)
- If you’re receiving inbound calls via Twilio, use the Twilio personalization webhook to inject caller context (e.g., name) so the intro is personalized and explicit about the call purpose. (elevenlabs.io)
- Background noise and non‑verbal sounds being misinterpreted
- Reduce false barge‑ins by disabling Interruptions or limiting them to after the intro; tune Turn Timeout so the agent waits a bit longer before reprompting in noisy environments. (elevenlabs.io)
- In your system prompt, add an instruction to ask for clarification when unsure and to ignore non‑speech events; see the Prompting guide’s “Goal” and “Guardrails” patterns. (elevenlabs.io)
- ElevenLabs STT (Scribe v1) can tag non‑speech audio events (e.g., laughter/applause) in transcripts; use post‑call transcripts to verify where mis-triggers occur and refine prompts/timeouts. (elevenlabs.io)
- Comprehension issues (e.g., age not captured)
- In the system prompt, specify explicit collection steps and confirmation (e.g., “Ask for age in digits, then repeat back to confirm”). This is the recommended way to enforce structured flows. (elevenlabs.io)
- Increase Turn Timeout slightly to allow users time to respond before the agent reprompts or ends that step. (elevenlabs.io)
- Survey flow ends too early or lacks probing
- Add the End call system tool only with strict conditions (e.g., “Call may end only after all survey questions are asked and confirmations completed”). (elevenlabs.io)
- Use the Prompting guide’s “Goal” section to list each survey step and required confirmations so the LLM follows the full path and probes on incomplete answers. (elevenlabs.io)
- Keep Interruptions off while asking critical scripted questions to avoid premature transitions. (elevenlabs.io)
- Low response/short call duration
- Enable Voicemail detection to avoid wasting attempts on voicemail and to optionally leave a concise message; this improves effective connect rates. (elevenlabs.io)
- Personalize opens via Twilio personalization (e.g., “Hi <Name>, calling about <Topic>”) or via per‑call overrides of first_message/system_prompt to increase engagement. (elevenlabs.io)
- Use the Agents Dashboard analytics and Language Breakdown to monitor call
hey curious what LLM model you're using and seeing these issues?
AI-generated Answer for mikegreen7585
Short answer: It depends on what you selected for your agent.
- ElevenLabs Agents lets you choose the LLM. You can pick models from OpenAI, Anthropic, or Google, or connect your own custom LLM/server. (help.elevenlabs.io, elevenlabs.io)
- If you haven’t supplied your own keys and selected a provider, ElevenLabs uses its own internal credentials for popular models like OpenAI. (elevenlabs.io)
- To confirm which model your agent is using, open your agent and check the LLM selection in the agent’s configuration (Customization > LLM). (elevenlabs.io)
- You can swap models at any time; the platform is designed to work with “an LLM of your choice.” (elevenlabs.io)
If you share the LLM currently set for your Hindi agent, I can point you to model-specific tuning steps.
Sources:
What can I create with ElevenLabs Agents (formerly Conversational AI) – ElevenLabs
Large Language Models (LLMs) | ElevenLabs Documentation
Integrate your own model | ElevenLabs Documentation
Large Language Models (LLMs) | ElevenLabs Documentation
Introducing Conversational AI | ElevenLabs
gpt 4.1