TSHC-DTS: A Two Stages Semi-supervised Dialogue Topic Segmentation Based on Siamese Transformers and Hierarchical Clustering
學年 113
學期 1
發表日期 2024-12-19
作品名稱 TSHC-DTS: A Two Stages Semi-supervised Dialogue Topic Segmentation Based on Siamese Transformers and Hierarchical Clustering
作品名稱（其他語言）
著者 Yuan-Lin Liang
作品所屬單位
出版者
會議名稱 RAAI 2024
會議地點 Singapore
摘要 Dialogue segmentation is one of the fundamental tasks in natural language processing that involves partitioning a dialogue into coherent segments or topics. Previous methods often explore only the surface level of contextual features such as lexical features. The proposed method in this paper is a two stage approach to dialogue segmentation. The first stage uses a Hierarchical Clustering algorithm to group semantically similar utterances based on the embeddings. The second stage uses a Siamese Transformer to calculate the similarity between the utterance pairs in each group. The proposed method can detect both broad and subtle transitions within the dialogue. The experimental results demonstrate that the proposed method effectively identifies segment boundaries compared with other methods.
關鍵字 dialogue segmentation, semi-supervised learning, Siamese transformers, topic hierarchical clustering
語言 en
收錄於
會議性質 國際
校內研討會地點 無
研討會時間 20241219~20241221
通訊作者
國別 SGP
公開徵稿
出版型式
出處
SDGS 優質教育,產業創新與基礎設施