在 🤗 Transformers 中使用 n-gram 提升 Wav2Vec2 語音識別效能
Original: Boosting Wav2Vec2 with n-grams in 🤗 Transformers
This technical blog post from Hugging Face introduces how combining n-gram language models (LMs) can significantly improve the performance…
Hugging Face 推出整合 pyctcdecode 的新功能，讓開發者能輕鬆將 n-gram 語言模型與 Wav2Vec2 結合。 此方法能有效修正 Wav2Vec2 在 CTC 解碼時產生的拼寫錯誤，顯著降低語音識別的字錯率（WER）。 本指南提供完整的實作步驟，展示如何載入預訓練語言模型並應用於多語系的語音識別任務。
This technical blog post from Hugging Face introduces how combining n-gram language models (LMs) can significantly improve the performance of Wav2Vec2 automatic speech recognition (ASR) models.
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