A semantic tagging tool for spoken dialogue corpus
نویسندگان
چکیده
In this paper, we report our semantic tagging tool for spoken dialogue corpus. This tagging tool can acquire analysis rules using Transformation-based Learning (TBL) from small scale training corpus. It can learn dialogue act tagging rules and semantic frame tagging rules. The precisions are 72% in dialogue act tagging and 58% of semantic frame tagging in open test.
منابع مشابه
Development of a Machine Learnable Discourse Tagging Tool
We have developed a discourse level tagging tool for spoken dialogue corpus using machine learning methods. As discourse level information, we focused on dialogue act, relevance and discourse segment. In dialogue act tagging, we have implemented a transformation-based learning procedure and resulted in 70% accuracy in open test. In relevance and discourse segment tagging, we have implemented a ...
متن کاملLayered Speech-Act Annotation for Spoken Dialogue Corpus
This paper describes the design of speech act tags for spoken dialogue corpora and its evaluation. Compared with the tags used for conventional corpus annotation, the proposed speech intention tag is specialized enough to determine system operations. However, detailed information description increases tag types. This causes an ambiguous tag selection. Therefore, we have designed an organization...
متن کاملDialogue Acts Annotation for NICT Kyoto Tour Dialogue Corpus to Construct Statistical Dialogue Systems
This paper introduces a new corpus of consulting dialogues designed for training a dialogue manager that can handle consulting dialogues through spontaneous interactions from the tagged dialogue corpus. We have collected more than 150 hours of consulting dialogues in the tourist guidance domain. This paper outlines our taxonomy of dialogue act (DA) annotation that can describe two aspects of an...
متن کاملSpoken Language Understanding in a Nutrition Dialogue System
Existing approaches for the prevention and treatment of obesity are hampered by the lack of accurate, low-burden methods for self-assessment of food intake, especially for hard-to-reach, low-literate populations. For this reason, we propose a novel approach to diet tracking that utilizes speech understanding and dialogue technology in order to enable efficient self-assessment of energy and nutr...
متن کاملSpoken Language Understanding in a Nutrition ARCVES Dialogue System
Existing approaches for the prevention and treatment of obesity are hampered by the lack of accurate, low-burden methods for self-assessment of food intake, especially for hard-to-reach, low-literate populations. For this reason, we propose a novel approach to diet tracking that utilizes speech understanding and dialogue technology in order to enable efficient self-assessment of energy and nutr...
متن کامل