tailieunhanh - Báo cáo khoa học: "Automatically Identifying Problematic Dialogues in DARPA Communicator Dialogue Systems"

Spoken dialogue systems promise efficient and natural access to information services from any phone. Recently, spoken dialogue systems for widely used applications such as email, travel information, and customer care have moved from research labs into commercial use. These applications can receive millions of calls a month. This huge amount of spoken dialogue data has led to a need for fully automatic methods for selecting a subset of caller dialogues that are most likely to be useful for further system improvement, to be stored, transcribed and further analyzed. . | Proceedings of the 40th Annual Meeting of the Association for Computational Linguistics ACL Philadelphia July 2002 pp. 384-391. What s the Trouble Automatically Identifying Problematic Dialogues in DARPA Communicator Dialogue Systems Helen Wright Hastie Rashmi Prasad Marilyn Walker AT T Labs - Research 180 Park Ave Florham Park . 07932 . hhastie rjprasad walker@ Abstract Spoken dialogue systems promise efficient and natural access to information services from any phone. Recently spoken dialogue systems for widely used applications such as email travel information and customer care have moved from research labs into commercial use. These applications can receive millions of calls a month. This huge amount of spoken dialogue data has led to a need for fully automatic methods for selecting a subset of caller dialogues that are most likely to be useful for further system improvement to be stored transcribed and further analyzed. This paper reports results on automatically training a Problematic Dialogue Identifier to classify problematic human-computer dialogues using a corpus of 1242 DARPA Communicator dialogues in the travel planning domain. We show that using fully automatic features we can identify classes of problematic dialogues with accuracies from 67 to 89 . 1 Introduction Spoken dialogue systems promise efficient and natural access to a large variety of information services from any phone. Deployed systems and research prototypes exist for applications such as personal email and calendars travel and restaurant information personal banking and customer care. Within the last few years several spoken dialogue systems for widely used applications have moved from research labs into commercial use Baggia et al. 1998 Gorin et al. 1997 . These applications can receive millions of calls a month. There is a strong requirement for automatic methods to identify and extract dialogues that provide training data for further system development. As a .

• Báo cáo khoa học
• Automatically Identifying
• Problematic Dialogues
• DARPA Communicator Dialogue Systems
• 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