TAILIEUCHUNG - Báo cáo khoa học: "INSIDE-OUTSIDE REESTIMATION FROM PARTIALLY BRACKETED CORPORA"

The inside-outside algorithm for inferring the parameters of a stochastic context-free grammar is extended to take advantage of constituent information (constituent bracketing) in a partially parsed corpus. Experiments on formal and natural language parsed corpora show that the new algorithm can achieve faster convergence and better modeling of hierarchical structure than the original one. In particular, over 90% test set bracketing accuracy was achieved for grammars inferred by our algorithm from a training set of handparsed part-of-speech strings for sentences in the Air Travel Information System spoken language corpus. Finally, the new algorithm has better time complexity than. | INSIDE-OUTSIDE REESTIMATION FROM PARTIALLY BRACKETED CORPORA Fernando Pereira 2D-447 AT T Bell Laboratories PO Box 636 600 Mountain Ave Murray Hill NJ 07974-0636 Yves Schabes Dept of Computer and Information Science University of Pennsylvania Philadelphia PA 19104-6389 ABSTRACT The inside-outside algorithm for inferring the parameters of a stochastic context-free grammar is extended to take advantage of constituent information constituent bracketing in a partially parsed corpus. Experiments on formal and natural language parsed corpora show that the new algorithm can achieve faster convergence and better modeling of hierarchical structure than the original one. In particular over 90 test set bracketing accuracy was achieved for grammars inferred by our algorithm from a training set of hand-parsed part-of-speech strings for sentences in the Air Travel Information System spoken language corpus. Finally the new algorithm has better time complexity than the original one when sufficient bracketing is provided. 1. MOTIVATION The most successful stochastic language models have been based on finite-state descriptions such as n-grams or hidden Markov models HMMs Jelinek et al. 1992 . However finite-state models cannot represent the hierarchical structure of natural language and are thus ill-suited to tasks in which that structure is essential such as language understanding or translation. It is then natural to consider stochastic versions of more powerful grammar formalisms and their grammatical inference problems. For instance Baker 1979 generalized the parameter estimation methods for HMMs to stochastic context-free grammars SCFGs Booth 1969 as the inside-outside algorithm. Unfortunately the application of SCFGs and the original inside-outside algorithm to natural-language modeling has been so far inconclusive Lari and Young 1990 Jelinek et al. 1990 Lari and Young 1991 . Several reasons can be adduced for the .

• Báo cáo khoa học
• INSIDE OUTSIDE REESTIMATION
• PARTIALLY BRACKETED CORPORA
• Fernando Pereira
• 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