Audio Transcription Pipeline with OpenAI Whisper
Transcribe audio files at scale with Pixeltable and OpenAI Whisper. Automatic batching, error handling, and incremental processing.
The Challenge
Transcribing large volumes of audio requires complex orchestration: file handling, API rate limiting, error retries, parallel processing, and result storage across separate systems.
The Solution
Pixeltable automates the entire transcription workflow. Add audio files to a table, and Whisper transcription runs as a computed column with built-in batching and error handling.
Implementation Guide
Step-by-step walkthrough with code examples
Audio Table
Create a table for audio files with automatic transcription.
1import pixeltable as pxt2from pixeltable.functions import openai34# Audio processing table5audio = pxt.create_table('app.audio', {6 'audio_file': pxt.Audio,7 'title': pxt.String,8 'speaker': pxt.String,9})1011# Automatic Whisper transcription12audio.add_computed_column(13 transcript=openai.transcriptions(14 audio=audio.audio_file,15 model='whisper-1'16 )17)1819# Insert files — transcription runs automatically20audio.insert([21 {'audio_file': '/recordings/meeting_01.mp3',22 'title': 'Team Standup', 'speaker': 'All'},23])
Key Benefits
Real Applications
Prerequisites
Performance
Related Guides
Build an end-to-end video analysis system with Pixeltable. Ingest video, extract frames, run multimodal AI models, generate embeddings, and enable semantic search — all as computed columns on a table.
Replace thousands of lines of orchestration code with declarative computed columns. Pixeltable handles execution, dependencies, caching, and incremental updates automatically.
Build applications that work with images, videos, audio, and documents simultaneously. Pixeltable treats all modalities as first-class column types with automatic cross-modal operations.
Ready to Get Started?
Install Pixeltable and start building in minutes. One pip install, no infrastructure to manage.