Towards an Online Text-Based Person Search in Vietnamese Language
Thi-Hoai Phan, Hoang-Son Bui, Tri Trung Kien Le, Thi-Ngoc-Diep Do, Thuy-Binh Nguyen, Hong-Quan Nguyen, Thanh-Hai Tran, Thi Thanh Thuy Pham, Thi‐Lan Le · ACM Transactions on Asian and Low-Resource Language Information Processing · 2025
In recent years, many efforts have been dedicated to text-based person search, thanks to its potential applications in various domains. However, most of these works focus on person search via queries in English and conduct offline evaluations. Despite some promising results for text-based person search in English, several challenges still prevent its widespread use in practical situations when deployed in minor languages. This article extends person search to the Vietnamese language. In terms of linguistics, English and Vietnamese belong to two different language families. In addition to the difference in vocabulary, these two languages also have opposite word structures and syntactic structures. The contributions of the article are twofold. First, based on the network architecture of the ViTAA model [Wang et al. 2020 ], a framework for person search through Vietnamese queries has been developed. In this framework, to take into account specific characteristics of the Vietnamese language, the word-tokenizing, Parts of Speech (PoS) tagging techniques of different natural language processing tools, including Underthesea [UndertheseaNLP 2018 ], SEACoreNLP [Singapore 2021 ], and PhoNLP [Nguyen and Nguyen 2021 ], have been investigated in order to extract language elements from Vietnamese descriptions. Our investigation shows that selecting a suitable preprocessing technique can improve person search performance by 1.28% at R@1. When incorporating these preprocessing techniques with the person search model, the best accuracy was achieved with 27.08%, 51.38%, and 63.00% at rank 1, rank 5, and rank 10 respectively. Second, for the first time, an online evaluation of person search through natural language queries was conducted. A web-based application has been developed to serve online evaluation scenarios with different groups of end-users. An extensive evaluation was conducted with 30 subjects and 115 queries. Upon analyzing the experimental results, open issues and suggestions for future improvements in person search were uncovered.