在 🤗 Transformers 中使用 Wav2Vec2 處理超長音檔的自動語音辨識 (ASR)
Original: Making automatic speech recognition work on large files with Wav2Vec2 in 🤗 Transformers
In the field of automatic speech recognition (ASR), Wav2Vec2 is a revolutionary model, but it faces a significant challenge when processing…
傳統 Wav2Vec2 等語音模型因自注意力機制的記憶體複雜度限制，難以直接處理長音檔。Hugging Face 推出分塊（Chunking）與重疊步長（Stride）技術，將長音訊切片處理後無縫拼接。此功能已整合至 Transformers 的 ASR Pipeline 中，開發者只需設定簡單參數即可實現高效且精準的長語音轉文字。
In the field of automatic speech recognition (ASR), Wav2Vec2 is a revolutionary model, but it faces a significant challenge when processing long audio files. Because the Transformer's self-attention mechanism has quadratic (O(N^2)) memory and computational complexity, feeding audio that is tens of minutes or hours long directly into the model quickly leads to out-of-memory (OOM) errors.
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