針對特定領域之中英語碼語音辨識系統

Mandarin-English Code-Switching Speech Recognition System for Specific Domain

本文將介紹利用自動語音辨識(Automatic Speech Recognition, ASR)技術處理帶有特定領域的語音內容。我們將以Conformer端到端模型做為系統架構，並利用純中文資料進行初步訓練，再以遷移式學習（Transfer learning）技術對系統以中英語碼轉換(Mandarin-English Code Switching)資料進行一次微調，最後利用帶有特定領域的中英語碼轉換資料對模型進行最終微調，使其在特定領域的語音辨識上達到一定的效果。我們以不同微調方式進行實驗，最終錯誤率從82.0%降到34.8%。

This paper will introduce the use of Automatic Speech Recognition (ASR) technology to process speech content with specific domain. We will use the Conformer end-toend model as the system architecture, and use pure Chinese data for initial training. Next, use the transfer learning technology to fine-tune the system with Mandarin- English code-switching data. Finally, use the Mandarin-English code-switching data with a specific domain makes the final finetuning of the model so that it can achieve a certain effect on speech recognition in a specific domain. Experiments with different fine-tuning methods reduce the final error rate from 82.0% to 34.8%.