Adapting speaker recognition systems to new environments is a widely-used technique improve well-performing model learned from large-scale data towards task-specific small-scale scenarios. However, previous studies focus on single domain adaptation, which neglects more practical scenario where training are collected multiple acoustic domains needed in forensic Audio analysis for offers unique c...

Topic Detection and Tracking (TDT) refers to automatic techniques for locating topically related material in streams of data such as newswire and broadcast news. DARPA-sponsored research has made enormous progress during the past three years, and the tasks have been made progressively more difficult and realistic. Well-designed corpora and objective performance evaluations have enabled this suc...

Based on natural language text analysis, this paper intends to draw a basic framework for the construction of domain knowledge base. Using encyclopedia resources and text information resources on the Web, we focus on the method of constructing domain knowledge base through technologies in natural language text analysis and machine learning. Moreover, an open network platform will be developed, ...

Human annotation of discourse corpora typically results in segmentation hierarchies that vary in their degree of agreement. This paper presents several techniques for unifying multiple discourse annotations into a single hierarchy, deemed a “gold standard” — the segmentation that best captures the underlying linguistic structure of the discourse. It proposes and analyzes methods that consider t...

The generalised, automated reconstruction of the reasoning structures underlying persuasive communication is an enormously challenging task. While this work in argument mining is increasingly informed by the rich tradition of argumentation studies outside the computational field, the rhetorical perspective on argumentation is thus far largely ignored. To explore the application of rhetorical in...

In recent years, Structural Correspondence Learning (SCL) is becoming one of the most promising techniques for sentiment-transfer learning. However, SCL model treats each feature as well as each instance by an equivalent-weight strategy. To address the two issues effectively, we proposed a weighted SCL model (W-SCL), which weights the features as well as the instances. More specifically, W-SCL ...

When can we expect a text-video retrieval system to work effectively on datasets that differ from its training domain? In this work, investigate question through the lens of unsupervised domain adaptation in which objective is match natural language queries and video content presence shift at query-time. Such systems have significant practical applications since they are capable generalising ne...