TAILIEUCHUNG - Báo cáo khoa học: "Sentiment Vector Space Model for Lyric-based Song Sentiment Classification"

Lyric-based song sentiment classification seeks to assign songs appropriate sentiment labels such as light-hearted and heavy-hearted. Four problems render vector space model (VSM)-based text classification approach ineffective: 1) Many words within song lyrics actually contribute little to sentiment; 2) Nouns and verbs used to express sentiment are ambiguous; 3) Negations and modifiers around the sentiment keywords make particular contributions to sentiment; | Sentiment Vector Space Model for Lyric-based Song Sentiment Classification Yunqing Xia Center for Speech and language Tech. RIIT Tsinghua University Beijing 100084 China yqxia@ Kam-Fai Wong Dept. of SE eM The Chinese University of Hong Kong Shatin Hong Kong kfwong@ Linlin Wang State Key Lab of Intelligent Tech. and Sys. Dept. of CST Tsinghua University Beijing 100084 China wangll0 7 @ Mingxing Xu Dept. of CST Tsinghua University Beijing 100084 China xumx@ Abstract Lyric-based song sentiment classification seeks to assign songs appropriate sentiment labels such as light-hearted and heavy-hearted. Four problems render vector space model VSM -based text classification approach ineffective 1 Many words within song lyrics actually contribute little to sentiment 2 Nouns and verbs used to express sentiment are ambiguous 3 Negations and modifiers around the sentiment keywords make particular contributions to sentiment 4 Song lyric is usually very short. To address these problems the sentiment vector space model s-VSM is proposed to represent song lyric document. The preliminary experiments prove that the s-VSM model outperforms the VSM model in the lyric-based song sentiment classification task. 1 Introduction Song sentiment classification nowadays becomes a hot research topic due largely to the increasing demand of ubiquitous song access especially via mobile phone. In their music phone W910i Sony and Ericsson provide Sense Me component to catch owner s mood and play songs accordingly. Song sentiment classification is the key technology for song recommendation. Many research works have been reported to achieve this goal using audio sig nal Knees et al. 2007 . But research efforts on lyric-based song classification are very few. Preliminary experiments show that VSM-based text classification method Joachims 2002 is ineffective in song sentiment classification see Section 5 due to the following four reasons.

• Báo cáo khoa học
• Sentiment Vector Space Model
• Lyric based Song Sentiment Classification
• Yunqing Xia
• báo cáo khoa học
• báo cáo 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 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