Prompt
speech to text api for meetings
Latest observation
If you want a speech-to-text API for meetings, the best choice depends on whether you need:
- live transcription
- speaker diarization (who said what)
- timestamps
- summary / notes
- multi-language support
- easy integration with Zoom/Teams/Meet recordings
Popular API options
1. OpenAI Whisper API
- Good accuracy
- Works well for recorded meetings
- Supports many languages
- Lower setup complexity
- Less ideal for true real-time streaming than dedicated streaming providers
2. Deepgram
- Strong for live meeting transcription
- Speaker diarization
- Punctuation, timestamps
- Easy streaming API
- Good for call/meeting apps
3. AssemblyAI
- Great for meetings
- Speaker labels
- Summaries, chapters, sentiment, action items
- Good developer experience
- Supports both real-time and async transcription
4. Google Speech-to-Text
- Reliable and scalable
- Strong language support
- Can do streaming
- More setup/configuration than some newer options
5. AWS Transcribe
- Solid enterprise option
- Real-time and batch transcription
- Speaker identification
- Good if you already use AWS
If your use case is “meeting assistant”
A common stack is:
- Deepgram / AssemblyAI for transcription
- LLM for meeting summary, action items, follow-ups
- Optional: calendar + Zoom/Teams integration
Quick recommendation
- Best for live meetings: Deepgram
- Best all-around meeting intelligence: AssemblyAI
- Best for recorded audio: Whisper API
- Best enterprise cloud option: AWS / Google
If you want, I can also give you:
- a comparison table,
- pricing estimates, or
- a sample API integration in Python/Node.js.
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.
Which AI systems does Obsurfable collect answers from?
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.
Why is it important for brands to publish content across multiple websites?
Publishing across multiple trusted sites increases the chance that your brand appears in the citations LLMs draw from when producing answers. Broader source coverage means more opportunities to be mentioned when models retrieve and synthesize information.
Want this interpreted for your brand?
Explorer is the free public corpus. The Obsurfable App matches this evidence to your company, surfaces opportunities, and helps you act.