Prompt

speech to text API for developers

Artificial Intelligence / AI Platforms1 observationLast seen Oct 8, 2026

Latest observation

Oct 8, 2026OpenAI APIWeb search: off

If you’re looking for a speech-to-text API for developers, here are some of the most common options, depending on your needs:

Popular Speech-to-Text APIs

  1. OpenAI Whisper API

    • Strong transcription quality
    • Good for many languages and accents
    • Easy to integrate via API
  2. Google Cloud Speech-to-Text

    • Real-time streaming support
    • Good accuracy and scalability
    • Useful for enterprise apps
  3. AWS Transcribe

    • Works well with AWS services
    • Supports real-time and batch transcription
    • Good for call analytics and media workflows
  4. Microsoft Azure Speech to Text

    • Strong enterprise tooling
    • Supports custom speech models
    • Good for real-time and batch use
  5. AssemblyAI

    • Developer-friendly API
    • Features like diarization, summaries, and sentiment
    • Easy to start with
  6. Deepgram

    • Fast, low-latency transcription
    • Good for streaming and voice apps
    • Often used in real-time products

If you want to build with OpenAI

A simple transcription workflow usually looks like:

  1. Record audio in your app
  2. Send the audio file to the API
  3. Receive text transcription
  4. Display or process the text

Example use cases

  • Meeting transcription
  • Voice notes
  • Call center analytics
  • Accessibility tools
  • Voice commands

If you want, I can also give you:

  • a comparison table
  • code examples in Python/JavaScript
  • or help you choose the best API for your use case

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?

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