From Audio/Video to Text with Escribano Transcriptions

Several factors influence automated transcription quality, including audio quality, participant clarity, terminology used, and more. It's a good practice to try various models to find the best balance between results, cost, and turnaround time. For more details, visit our Blog.

To start, no automated transcription is 100% accurate. Client needs vary; while some require highly accurate transcriptions for third-party deliverables, others use transcriptions as reference. The most expensive model might not be the best fit. Our Original transcription often meets clients' needs. The Optimized model improves automated transcriptions with better speaker separation, grammar, and spelling, offering a professional 'curated' result. Human Curation, while more accurate, involves higher costs and is recommended only when necessary.

Escribano allows bulk file upload. Alternatively, we can work with a Custom Gateway to process files from your origin, or generate a 'Batch' option for offline uploading to our system.

Diarization (speaker separation) may struggle if participants speak infrequently or briefly, use one-word responses, or have similar voices. Background noise, simultaneous speaking, or echo can affect diarization as well.

For better speaker recognition, ensure each speaker talks for at least 30 seconds uninterrupted. Avoid very short responses like 'Yes', 'Right', or 'Sounds good'. Cross-talk avoidance can also help. Recording quality and devices play vital roles.

Accuracy depends on factors like audio quality, speaker count, and audio length. Ensuring each speaker talks for at least 30 seconds and avoiding brief responses can enhance accuracy. However, no model is perfect, especially in challenging scenarios.