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Wav2vec2 Base Timit Demo Colab57
基於facebook/wav2vec2-base微調的語音識別模型，在TIMIT數據集上訓練，詞錯誤率(WER)為0.4593。
Downloads 16
Release Time : 5/1/2022
Model Overview
這是一個用於英語語音識別的自動語音識別(ASR)模型，基於wav2vec2架構微調而成。
Model Features
低詞錯誤率
在評估集上達到0.4593的詞錯誤率(WER)
基於wav2vec2架構
使用facebook/wav2vec2-base作為基礎模型進行微調
端到端訓練
採用端到端的訓練方式，直接學習語音到文本的映射
Model Capabilities
英語語音識別
語音轉文本
Use Cases
語音轉錄
會議記錄轉錄
將英語會議錄音自動轉換為文字記錄
詞錯誤率約46%
語音指令識別
識別英語語音指令並轉換為可執行命令
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