Quản lý Lưu lượng Đối thoại Dựa trên Kiến thức cho Robot Xã hội và Các Đại lý Đối thoại

Springer Science and Business Media LLC - Tập 14 - Trang 1273-1293 - 2022
Lucrezia Grassi1, Carmine Tommaso Recchiuto1, Antonio Sgorbissa1
1DIBRIS, University of Genoa, Genova, Italy

Tóm tắt

Bài báo đề xuất một hệ thống cho cuộc trò chuyện dựa trên kiến thức được thiết kế dành cho Robot Xã hội và các đại lý đối thoại khác. Hệ thống được đề xuất dựa vào một Ontology (mô hình ngữ nghĩa) để mô tả tất cả các khái niệm có thể là chủ đề cuộc trò chuyện liên quan cũng như mối quan hệ lẫn nhau của chúng. Bài báo tập trung vào thuật toán Quản lý Đối thoại, thuật toán này lựa chọn chủ đề trò chuyện phù hợp nhất dựa trên đầu vào của người dùng. Hơn nữa, bài báo thảo luận về các chiến lược nhằm đảm bảo lưu lượng trò chuyện được duy trì, phản ánh có chiều sâu hơn ý định của người dùng để dẫn dắt cuộc trò chuyện theo những hướng cụ thể, đồng thời tránh những phản ứng hoàn toàn thụ động đối với những gì người dùng nói. Để đo lường chất lượng của cuộc trò chuyện, bài báo báo cáo các thử nghiệm được thực hiện với 100 người tham gia được tuyển dụng, so sánh năm đại lý đối thoại: (i) một đại lý quản lý lưu lượng đối thoại chỉ dựa vào việc phát hiện từ khóa trong lời nói, (ii) một đại lý vừa dựa vào việc phát hiện từ khóa vừa vào tính năng Phân loại Nội dung của Google Cloud Natural Language, (iii) một đại lý chọn chủ đề cuộc trò chuyện ngẫu nhiên, (iv) một người thật giả vờ là chatbot, và (v) một trong những chatbot nổi tiếng nhất thế giới: Replika. Cảm nhận chủ quan của người tham gia được đo lường bằng công cụ SASSI (Đánh giá Chủ quan về Giao diện Hệ thống Giọng nói), cũng như bằng một khảo sát tùy chỉnh để đo lường cảm nhận chủ quan về tính mạch lạc.

Từ khóa


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