I need an API for live captions with under 2 second delay. What are my options?

If you need live captions with under ~2 seconds end-to-end delay, you generally want a streaming speech-to-text API that supports partial results and low-latency audio transport.

Good options

1) Deepgram Streaming

• Very popular for low-latency live transcription
• WebSocket streaming
• Partial/final transcripts
• Good fit for captions and real-time apps

Best for: low latency, easy integration, captioning workflows.

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2) Google Cloud Speech-to-Text (Streaming)

• Strong accuracy and language support
• Streaming API with interim results
• Can work well for captions
• Latency can be good, but depends on setup and region

Best for: broad language support, enterprise cloud workflows.

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3) AssemblyAI Realtime

• Built for streaming transcription
• Supports live partials
• Easier developer experience than some enterprise APIs

Best for: quick integration, real-time apps, decent accuracy.

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4) OpenAI Realtime / speech models

• If you already use OpenAI tooling, this can be compelling
• Designed for real-time audio interactions
• Whether it meets your captioning latency target depends on the exact pipeline and network conditions

Best for: apps already in the OpenAI ecosystem, conversational live experiences.

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5) AWS Transcribe Streaming

• Mature streaming STT
• Supports partial results
• Good AWS integration

Best for: AWS-native architectures, enterprise setups.

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6) Azure Speech to Text (Streaming)

• Solid streaming transcription
• Interim results available
• Good for Microsoft ecosystem

Best for: Azure-based systems, enterprise deployments.

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What to look for to hit under 2 seconds

To keep captions under 2 seconds, the API alone isn’t enough. Your pipeline matters:

• Use streaming audio over WebSocket or gRPC
• Send small audio chunks continuously
• Enable interim/partial transcripts
• Avoid large buffering on client or server
• Choose a nearby region to reduce network latency
• Use a decent audio format like 16 kHz mono PCM or supported Opus stream
• Display partial captions immediately, then revise them as final text arrives

A typical target:

• 100–300 ms chunking
• 300–800 ms model processing time
• 100–500 ms network + app overhead

That can get you under 2 seconds if tuned well.

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My practical recommendation

If your top priority is lowest-latency live captions, start with:

1. Deepgram
2. Google Streaming Speech-to-Text
3. AWS/Azure if you’re already in those clouds

If you want, I can also help you choose based on:

• your cloud provider
• expected concurrency
• languages
• budget
• whether you need speaker diarization
• whether captions are for video calls, broadcasts, or an app

If you want, I can make a comparison table with latency, pricing style, and integration complexity.