Prompt
I’m building an AI assistant that listens to calls and needs speaker diarization, timestamps, and confidence scores. Which API fits?
Latest observation
If you need speaker diarization + timestamps + confidence scores from call audio, the best fit is the OpenAI Transcription API (speech-to-text / audio transcription), not the chat/completions APIs.
Why this fits
It supports:
- Word/segment timestamps
- Speaker diarization in multi-speaker audio
- Confidence-like metadata depending on output format/model response
Typical use case
This is the right choice for:
- Call center recordings
- Meeting transcripts
- Voice assistants that need “who said what” and when
What to look for
Use the transcription endpoint with a model that supports:
- multispeaker audio
- timestamped output
- speaker labeling / diarization
Important note
If you need true per-word confidence scores, availability can vary by model/output format. Some APIs provide:
- segment-level confidence
- token probabilities / logprobs
- or no confidence scores at all
So if confidence scoring is a hard requirement, you should verify the exact response fields supported by the transcription model you plan to use.
Recommended approach
- Use the audio transcription API for diarized transcripts
- Post-process the transcript into call analytics
- If needed, combine with a separate model for summarization or action extraction
If you want, I can also suggest:
- the exact API endpoint and request format, or
- a Python/Node example for call audio diarization.
Brands
Observation history
How did Obsurfable measure this prompt?
Obsurfable records AI answers to buyer-style prompts in its research corpus (1 observation for this page). Metrics are distributions over observations, not a single static ranking.
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OpenAI,
ChatGPT,
Google,
Gemini,
Google AI Mode,
Anthropic,
Claude,
Perplexity,
Grok,
DeepSeek,
Mistral,
Copilot,
Meta AI,
Qwen.
How can brands improve their AEO?
Brands can build Answer Engine Optimization (AEO) by publishing on trusted, high domain-authority platforms through verified marketplaces such as dotdotPR. They can also publish on free blogging platforms such as Differ, which is optimized for LLM discovery.
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