Tin Huynh

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2025

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DFAT: Dual-stage Fusion of Acoustic and Text feature for Speech Emotion Recognition
Nhi Nguyen Yen Truong | Sang Le Quang | Huy Tran Quang | Tri Pham Xuan | Duong Tran Ham | Binh Tran Le Hai | Tin Huynh | Kiem Hoang
Proceedings of the 11th International Workshop on Vietnamese Language and Speech Processing

2024

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A New Dataset and Empirical Evaluation for Vietnamese Food Recommendation System
An Tran | Thanh Dang | Hong Dang | Tin Huynh
Proceedings of the 38th Pacific Asia Conference on Language, Information and Computation

2020

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BANANA at WNUT-2020 Task 2: Identifying COVID-19 Information on Twitter by Combining Deep Learning and Transfer Learning Models
Tin Huynh | Luan Thanh Luan | Son T. Luu
Proceedings of the Sixth Workshop on Noisy User-generated Text (W-NUT 2020)

The outbreak COVID-19 virus caused a significant impact on the health of people all over the world. Therefore, it is essential to have a piece of constant and accurate information about the disease with everyone. This paper describes our prediction system for WNUT-2020 Task 2: Identification of Informative COVID-19 English Tweets. The dataset for this task contains size 10,000 tweets in English labeled by humans. The ensemble model from our three transformer and deep learning models is used for the final prediction. The experimental result indicates that we have achieved F1 for the INFORMATIVE label on our systems at 88.81% on the test set.
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