Real-Time vs Batch Transcription: Choosing the Right Speech-to-Text Architecture

Should your transcription happen as words are spoken, or after recording completes? This architectural choice affects user experience, accuracy, cost, and implementation complexity. Here's how to think through the decision.

Understanding the difference

Real-time (streaming) transcription

Audio is sent continuously as it's captured. Text appears with minimal delay (typically 100-500ms). The system processes chunks incrementally and may revise earlier text as more context arrives.

Use cases: Live captions, voice assistants, real-time note-taking, voice commands

Batch transcription

Complete audio files are uploaded after recording ends. Processing happens asynchronously, and results are returned when ready (seconds to minutes later).

Use cases: Meeting recordings, podcast transcription, video subtitles, archival processing

When to choose real-time

Immediate feedback is essential

If users need to see text as they speak—for verification, live captions, or interactive applications—batch isn't an option.

Short utterances dominate

Voice commands, quick voice notes, and conversational exchanges benefit from instant processing.

Human pacing matters

In live presentations or meetings, captions need to keep up with speakers in real-time. See our WCAG compliance guide for accessibility requirements around live captions.

You need to act on speech immediately

Voice control systems, accessibility tools, and interactive voice response (IVR) all require real-time processing.

When batch makes more sense

Accuracy trumps speed

Batch systems can use larger models, make multiple passes, and apply post-processing that improves accuracy. If quality matters more than immediacy, batch wins.

Audio is already recorded

For existing archives, podcasts, or meetings that will be reviewed later, there's no benefit to real-time processing.

Cost is a constraint

Batch is often cheaper per minute. You can also use spot/preemptible compute for processing.

Volume is unpredictable

Batch processing smooths out demand spikes. Queue recordings during peak times, process during off-peak.

Technical tradeoffs

Accuracy

Real-time systems work with limited context—they don't know what comes next. Batch systems can use full context, improving accuracy on ambiguous passages.

Typical accuracy difference: 2-10% higher WER for real-time vs. batch (same provider). See our WER explainer for what the metric means.

Research comparing STT services confirms these patterns across providers.

Latency

Real-time: 100-500ms typical delay Batch: Seconds to minutes (depends on queue and file length)

Partial results

Real-time systems emit partial results that may change as more audio arrives. Handling this gracefully in UI requires thought.

Error handling

Real-time: Must handle network drops, reconnections, and partial failures gracefully Batch: Simpler—upload fails or succeeds, process completes or fails

Cost

Pricing varies by provider, but real-time often costs more due to infrastructure complexity. Batch can leverage cheaper compute.

Hybrid approaches

Real-time capture, batch refinement

Show users immediate results with real-time transcription. Then re-process in batch for a cleaned-up final transcript.

Progressive transcription

Stream partial results for immediate display, but wait for batch post-processing before using for search/analysis.

Tiered accuracy

Use fast/cheap real-time for general use; offer batch processing for users who need higher accuracy.

Implementation considerations

Buffer management

Real-time requires managing audio buffers, handling network variability, and gracefully recovering from interruptions.

UI for partial results

Displaying text that might change is tricky. Consider:

• Visual distinction for tentative vs. confirmed text
• Smooth animations when text revises
• History of what was said vs. what was recognized

Webhook/polling for batch

Batch results need delivery. Options include:

• Polling for completion
• Webhooks when done
• Long-polling connections

Retry logic

Both approaches need robust handling of failures, but the patterns differ. Real-time needs reconnection; batch needs job retry.

Quick decision guide

Scenario	Architecture
Live captions	Real-time
Voice commands	Real-time
Meeting recording	Batch (or hybrid)
Podcast transcription	Batch
Call center analysis	Batch
Accessibility captions	Real-time
Video subtitles	Batch
Interactive tutoring	Real-time

For meeting recordings specifically, see our guides on speaker diarization and automating meeting notes.

For a comparison of providers across both architectures, see our STT API guide.