tailieunhanh - Báo cáo khoa học: "A Preference-first Language Processor Integrating the Unification Grammar and Markov Language Model for Speech Recognition-ApplicationS"

A language processor is to find out a most promising sentence hypothesis for a given word lattice obtained from acoustic signal recognition. In this paper a new language processor is proposed, in which unification granunar and Markov language model are integrated in a word lattice parsing algorithm based on an augmented chart, and the island-driven parsing concept is combined with various preference-first parsing strategies defined by different construction principles and decision rules. Test results"show that significant improvements in both correct rate of recognition and computation speed can be achieved . . | A Preference-first Language Processor Integrating the Unification Grammar and Markov Language Model for Speech Recognition Applications Lee-Feng Chien K. J. Chen and Lin-Shan Lee Dept of Computer Science and Information Engineering National Taiwan University Taipei Taiwan Rep. of China Tel 02 362-2444. The Institute of Information Science Academia Sinica Taipei Taiwan Rep. of China. ABSTRACT A language processor is to find out a most promising sentence hypothesis for a given word lattice obtained from acoustic signal recognition. In this paper a new language processor is proposed in which unification grammar and Markov language model are integrated in a word lattice parsing algorithm based on an augmented chart and the island-driven parsing concept is combined with various preference-first parsing sơategies defined by different construction principles and decision rules. Test results show that significant improvements in both correct rate of recognition and computation speed can be achieved . 1. Introduction In many speech recognition applications a word lattice is a partially ordered set of possible word hypotheses obtained from an acoustic signal processor. The purpose of a language processor is then for an input word lattice to find the most promising word sequence or sentence hypothesis as the output Hayes 1986 Tomita 1986 O Shaughnessy 1989 . Conventionally either grammatical or statistical approaches were used in such language processors. However the high degree of ambiguity and large number of noisy word hypotheses in the word lattices usually make the search space huge and correct identification of the output sentence hypothesis difficult and the capabilities of a language processor based on either grammatical or statistical approaches alone were very often limited. Because the features of these two approaches are basically complementary Derouault and Merialdo Derouault 1986 first proposed a unified model to combine them. But in this model these two .

• Báo cáo khoa học
• A Preference first Language
• Processor Integrating the Unification Grammar and Markov Language Model
• Speech Recognition ApplicationS
• 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