TAILIEUCHUNG - Báo cáo khoa học: "Multi-Engine Machine Translation with Voted Language Model"

The paper describes a particular approach to multiengine machine translation (MEMT), where we make use of voted language models to selectively combine translation outputs from multiple off-theshelf MT systems. Experiments are done using large corpora from three distinct domains. The study found that the use of voted language models leads to an improved performance of MEMT systems. | Multi-Engine Machine Translation with Voted Language Model Tadashi Nomoto National Institute of Japanese Literature 1-16-10 Yutaka Shinagawa Tokyo 142-8585 Japan nomoto@ Abstract The paper describes a particular approach to multiengine machine translation MEMT where we make use of voted language models to selectively combine translation outputs from multiple off-the-shelf MT systems. Experiments are done using large corpora from three distinct domains. The study found that the use of voted language models leads to an improved performance of MEMT systems. 1 Introduction As the Internet grows an increasing number of commercial MT systems are getting on line ready to serve anyone anywhere on the earth. An interesting question we might ponder is whether it is not possible to aggregate the vast number of MT systems available on the Internet into one super MT which surpasses in performance any of those MTs that comprise the system. And this is what we will be concerned with in the paper with somewhat watered-down settings. People in the speech community pursued the idea of combining off-the-shelf ASRs automatic speech recognizers into a super ASR for some time and found that the idea works Fiscus 1997 Schwenk and Gauvain 2000 Utsuro et al. 2003 . In IR information retrieval we find some efforts going under the name of distributed IR or meta-search to selectively fuse outputs from multiple search engines on the Internet Callan et al. 2003 . So it would be curious to see whether we could do the same with MTs. Now back in machine translation we do find some work addressing such concern Frederking and Nirenburg 1994 develop a multi-engine MT or MEMT architecture which operates by combining outputs from three different engines based on the knowledge it has about inner workings of each of the component engines. Brown and Fred-erking 1995 is a continuation of Frederking and Nirenburg 1994 with an addition of a ngrambased mechanism for a candidate selection. Nomoto 2003 .

• Báo cáo khoa học
• Multi Engine Machine Translation
• Voted Language Model
• Tadashi Nomoto
• báo cáo khoa học
• mô hình ngôn ngữ
• xử lý ngôn ngữ tự nhiên
• Bài giảng Xử lý ngôn ngữ tự nhiên
• Ngôn ngữ tự nhiên
• Kỹ thuật lập trình
• Xử lý nhập nhằng ngữ nghĩa
• Xử lý ngữ nghĩa
• Xử lý ngôn ngữ
• Natural Language Processing
• Ngôn ngữ lập trình
• Nhập nhằng cấu trúc
• Tri thức về ngôn ngữ
• Mô hình n gram
• Dịch máy
• Phương pháp dịch máy
• Hiểu ngôn ngữ
• Phân tích ngữ nghĩa
• Phân loại tin tự động
• Biểu diễn vị từ
• Thuộc tính về sự kiện
• Thuộc tính về sự kiện
• Mô hình ngôn ngữ Google Book N grams
• Mô hình ngôn ngữ KenLM
• Phương pháp làm mịn
• Tách từ tiếng Việt
• Gán nhãn từ loại
• Phân tích cú pháp
• Nghĩa từ vựng
• Phân giải nhập nhằng từ
• Phân loại văn bản
• Lexical chain
• Phản hồi thông tin
• Bài toán PTCP
• Cấu trúc ngữ pháp
• Phân tích cú pháp xác suất
• CKY kết hợp xác suất
• Văn phạm phi ngữ cảnh xác suất
• Hình thái học