Model Overview This model is a fine tuned version of OpenAI's Whisper Large v3 model, specifically trained on Air Traffic Control (ATC) communication datasets. The fine tuning process significantly improves transcription accuracy on domain specific aviation communications, achieving a Word Error Rate (WER) of 6.5% on the test set. The model is particularly effective at handling accent variations and ambiguous phrasing often encountered in ATC communications. Base Model : OpenAI Large v3 Fine tuned Model WER : 6.5% Model Description This fine tuned model is optimized to handle short, distinct transmissions between pilots and air traffic controllers. It is fine tuned using data from: ATC ASR Dataset The fine tuned model demonstrates enhanced performance in interpreting various accents, recognizing non standard phraseology, and processing noisy or distorted communications. It is highly suitable for aviation related transcription tasks. Intended Use The fine tuned Whisper model is designed for: Transcribing aviation communication : Providing accurate transcriptions for ATC communications, including accents and variations in English phrasing. Air Traffic Control Systems : Assisting in r…
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