使用 🤗 Transformers 微調 Whisper 進行多語言語音辨識 (ASR)
Original: Fine-Tune Whisper For Multilingual ASR with 🤗 Transformers
OpenAI's Whisper is a powerful automatic speech recognition (ASR) model. While its zero-shot capabilities are impressive, there remains…
本教學詳細介紹如何使用 Hugging Face 的 `transformers` 庫微調 OpenAI 的 Whisper 語音辨識模型。內容涵蓋從載入 Common Voice 資料集、音訊預處理（重採樣至 16kHz 並轉換為 Log-Mel 聲譜圖）、設定 Tokenizer，到使用 `Seq2SeqTrainer` 進行訓練與評估（以 WER 為指標）的完整流程。這對於想在特定低資源語言或專業領域提升語音轉文字精準度的開發者與研究人員來說，是極具價值的實戰指南。
OpenAI's Whisper is a powerful automatic speech recognition (ASR) model. While its zero-shot capabilities are impressive, there remains significant room for improvement when handling specific low-resource languages, particular accents, or specialized terminology (such as medical or legal domains). This classic fine-tuning guide, officially published by Hugging Face, provides a detailed walkthrough of how to use their ecosystem tools to perform custom training on Whisper.
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