Batch vs Real-Time Transcription: Which Do You Actually Need?

Not all transcription is created equal. When you need to convert speech to text, you have two fundamentally different approaches: batch transcription (processing pre-recorded files) and real-time transcription (converting speech as it happens). Choosing the wrong one can cost you money, accuracy, or both.

What's the Difference?

Batch transcription processes complete audio files after recording. You upload a file, wait for processing, and receive a transcript. Processing typically takes 10-25% of the audio duration—a one-hour recording might be ready in 6-15 minutes.

Real-time transcription converts speech to text as it happens, with text appearing within milliseconds of speaking. Instead of uploading files, you stream audio directly to the transcription service.

The technical distinction matters: batch processing can analyze the entire recording at once, using context from later in the audio to improve earlier transcriptions. Real-time systems must make decisions immediately, processing small chunks without knowing what comes next.

When to Use Batch Transcription

Batch transcription is the better choice for most pre-recorded content:

• Podcasts and interviews: Upload your recording, get back a polished transcript with speaker labels and timestamps
• Meeting recordings: Process Zoom or Teams recordings after the fact for searchable archives
• Video content: Generate subtitles and captions for YouTube, courses, or marketing videos
• Research: Transcribe interview recordings for qualitative analysis
• Call center archives: Process historical recordings for quality assurance or compliance

Key advantages:

• Higher accuracy (15-30% better than real-time in many cases)
• Better speaker diarization
• More reliable punctuation and formatting
• Lower cost per minute with most providers

When to Use Real-Time Transcription

Real-time transcription is essential when you need text as speech happens:

• Live captions: Accessibility for webinars, virtual events, and broadcasts
• Voice assistants: Responding to spoken commands immediately
• Contact center AI: Providing real-time suggestions to agents during calls
• Live meeting notes: Seeing transcripts during the meeting, not after
• Voice agents: AI systems that need to understand and respond to users instantly

Key requirements:

• Sub-500ms latency for natural conversation flow
• 1-3 second delay acceptable for live captioning
• Streaming audio connection (WebSocket or similar)

Accuracy Comparison

Batch transcription typically produces more accurate results. When the transcription system has access to the complete recording, it can:

• Use context from later sentences to resolve ambiguous words
• Apply more computationally expensive models
• Better identify speaker changes
• Handle overlapping speech more effectively

Real-time systems sacrifice some accuracy for speed. They process audio in small chunks (often 30 seconds or less) without knowledge of what comes next. Studies show streaming transcription can have 15-30% higher word error rates compared to batch processing on the same audio.

That said, accuracy gaps are narrowing. Modern real-time models like Deepgram Nova-3 and AssemblyAI's Universal-Streaming have significantly improved, and for clean audio with clear speakers, the difference may be negligible.

Cost Considerations

Pricing varies significantly by provider and approach:

Some providers charge 30-80% more for real-time transcription due to the infrastructure required for streaming. Others price both approaches identically.

Cost optimization tip: If you're transcribing recordings (not live audio), always use batch. Many teams unknowingly use real-time for everything "for simplicity" and pay significantly more than necessary.

The Hybrid Approach

Many organizations use both approaches strategically:

• Real-time during meetings: Live captions for accessibility and note-taking
• Batch after meetings: Reprocess the recording for higher-accuracy archives
• Real-time for urgent content: When you need immediate turnaround
• Batch for bulk processing: Historical archives, large content libraries

One practical example: a contact center might use real-time transcription during calls to power AI assistance tools, then batch process the complete recording overnight for quality assurance—capturing the benefits of both approaches.

Making the Right Choice

Choose batch transcription when:

• You're working with recordings (not live audio)
• Accuracy matters more than immediate availability
• You're processing large volumes of content
• Cost efficiency is a priority
• You need reliable speaker diarization

Choose real-time transcription when:

• You need text during the live event
• You're building voice-interactive applications
• Accessibility requires live captions
• Response time under a few seconds is critical

Consider both when:

• You want live visibility plus high-accuracy archives
• You're optimizing for both user experience and cost

Conclusion

For most people transcribing recordings—podcasts, interviews, meetings, videos—batch transcription is the clear choice. It's more accurate, often cheaper, and produces cleaner results with better speaker identification.

Real-time transcription serves a different purpose: when you genuinely need text as speech happens. Live captions, voice assistants, and real-time meeting notes all require the streaming approach.

If you're transcribing pre-recorded audio and don't need instant results, Scriby offers straightforward batch transcription with speaker diarization. Upload your file, get your transcript with speakers identified, and pay only for what you use—no subscriptions or streaming complexity required.