venice-audio-transcription

Audio transcription converts spoken meeting recordings into readable text with precise timestamps. You upload audio files via multipart/form-data, select a speech-to-text model, and receive timestamped transcripts suitable for indexing or creating subtitles.

Speech-to-text conversion handles a range of audio formats for transcription. You can submit various common audio files through multipart/form-data upload to generate accurate text transcripts using your chosen model.

Audio transcription supports multiple STT models to handle different language needs and accuracy requirements. You can specify models like 'nvidia/parakeet-tdt-0.6b-v3' during the multipart upload to optimize transcription results.

Audio transcription is OpenAI SDK compatible. You can integrate the speech-to-text endpoint directly into your existing OpenAI workflows by submitting audio files via standard multipart/form-data upload for immediate text conversion.

Timestamped transcripts are generated by submitting voice notes to the transcription endpoint. The speech-to-text process outputs text with timestamps, making it perfect for indexing conversations or creating subtitles from audio sources.

The best way to convert voice notes to text for specific languages is selecting an appropriate STT model. The transcription endpoint supports multiple models tailored for different language needs, ensuring accurate speech-to-text conversion.