Courtroom Transcription: A Deep Learning Approach to Legal Terminology and Speaker Identification
學年 112
學期 2
發表日期 2024-07-09
作品名稱 Courtroom Transcription: A Deep Learning Approach to Legal Terminology and Speaker Identification
作品名稱（其他語言）
著者 Syu-Jhih Jhang; Hsiang-Chuan Chang; Qiao-yun Zhang; Chih-Yung Chang
作品所屬單位
出版者
會議名稱 IEEE ICCE-TW
會議地點 Taichung; Taiwan
摘要 This study develops a deep learning with natural language processing. It focuses on overcoming the limitations of current speech recognition tools, which struggle with legal terminology and identifying different courtroom speakers. By combining advanced audio processing, role identification, and error correction techniques, including a Bert-based model and an N-gram model, the research aims to automate the transcription process more efficiently. This method not only promises to enhance the accuracy of capturing court proceedings but also aims to revolutionize the transcription practices by reducing manual effort and increasing the reliability of legal documents.
關鍵字 Speech Recognition; Legal Terminology; Deep Learning; Role Identification; Error Correction
語言 zh_TW
收錄於
會議性質 國內
校內研討會地點 無
研討會時間 20240709~20240711
通訊作者
國別 TWN
公開徵稿
出版型式
出處
相關連結

機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/126360 )

SDGS 尊嚴就業與經濟發展,產業創新與基礎設施