i4Ds/whisper-prep

Data preparation utility for the finetuning of OpenAI's Whisper model.

38
/ 100
Emerging

This tool helps AI engineers, machine learning practitioners, and data scientists prepare audio and transcript data for training speech-to-text models like OpenAI's Whisper. It takes raw audio files, sentence-level datasets, or existing SRT/VTT transcripts and outputs meticulously segmented, cleaned, and formatted datasets ready for model fine-tuning. This ensures high-quality training data, leading to better performing transcription models.

Use this if you need to create a high-quality, normalized dataset of audio and text for training an automatic speech recognition (ASR) model, especially when working with varied raw audio sources or sentence-level datasets.

Not ideal if you simply need to transcribe a single audio file or process a small number of transcripts without the intent of training or fine-tuning a machine learning model.

speech-to-text-training audio-data-preparation machine-learning-engineering natural-language-processing dataset-curation
No Package No Dependents
Maintenance 10 / 25
Adoption 5 / 25
Maturity 16 / 25
Community 7 / 25

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Stars

11

Forks

1

Language

Python

License

MIT

Last pushed

Mar 03, 2026

Commits (30d)

0

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/voice-ai/i4Ds/whisper-prep"

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