Please use this identifier to cite or link to this item: https://repository.cihe.edu.hk/jspui/handle/cihe/3809
DC FieldValueLanguage
dc.contributor.authorChan, Anthony Hing-Hungen_US
dc.contributor.authorSiu, Wan Chien_US
dc.contributor.authorChan, Sin Waien_US
dc.contributor.authorChan, Cheuk Yiu-
dc.contributor.authorHui, Chun Chuen-
dc.date.accessioned2023-05-25T08:11:11Z-
dc.date.available2023-05-25T08:11:11Z-
dc.date.issued2022-
dc.identifier.urihttps://repository.cihe.edu.hk/jspui/handle/cihe/3809-
dc.description.abstractWe watch soccer games because of the excitement, the skill of players, the brand name of soccer teams, etc. However, contribution of the commentary is also indispensable. At this stage of our technology development, it is good to have automatic commentary to be provided by our computer. This paper is on the production of soccer commentary automatically making use of hi-tech and deep learning. There are many aspects on the production. However, we just concentrate on the production of key commentaries. We make use of spatial-temporal representation with 2 stages of operations to design our transformer network. This involves Temporal-Grouped Attention that dynamically separates and groups all channels together for the advantage of extracting temporal domain features, Local-Global Mixed Attention that enforces the model to find relationship between local and global feature representations in one attention structure, and Selective Feature Aggregation to intelligently select the final weights between the two attention networks. Our results provides key commentaries in line with other state-of-the-art approaches but with high potential to be further developed to real-time commentary system.en_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.titleTo start automatic commentary of soccer game with mixed spatial and temporal attentionen_US
dc.typeconference proceedingsen_US
dc.relation.publicationProceedings of the 2022 IEEE Region 10 Conference (TENCON)en_US
dc.identifier.doi10.1109/TENCON55691.2022.9978078-
dc.contributor.affiliationSchool of Computing and Information Sciencesen_US
dc.contributor.affiliationSchool of Computing and Information Sciencesen_US
dc.contributor.affiliationSchool of Humanities and Languagesen_US
dc.relation.isbn9781665450959en_US
dc.description.startpage191en_US
dc.description.endpage196en_US
dc.cihe.affiliatedYes-
item.grantfulltextnone-
item.fulltextNo Fulltext-
item.languageiso639-1en-
item.openairetypeconference proceedings-
item.openairecristypehttp://purl.org/coar/resource_type/c_5794-
item.cerifentitytypePublications-
crisitem.author.deptSchool of Computing and Information Sciences-
crisitem.author.deptSchool of Computing and Information Sciences-
crisitem.author.deptSchool of Humanities and Languages-
crisitem.author.deptSchool of Computing and Information Sciences-
crisitem.author.deptSchool of Computing and Information Sciences-
crisitem.author.orcid0000-0001-7479-0787-
crisitem.author.orcid0000-0001-8280-0367-
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