Pusadee Seresangtakul

F0 modeling for isarn speech synthesis using deep neural networks and syllable-level feature representation

Pusadee Seresangtakul, Pongsathon Janyoi, Pongsathon Janyoi, 2020, Int. Arab J. Inf. Technol..

Tonal Contour Generation for Isarn Speech Synthesis Using Deep Learning and Sampling-Based F0 Representation

Pusadee Seresangtakul, Pongsathon Janyoi, Pongsathon Janyoi, 2020, Applied Sciences.

Sentiment Analysis for Thai Language in Hotel Domain Using Machine Learning Algorithms

Nattawat Khamphakdee, Pusadee Seresangtakul, 2021, Acta Informatica Pragensia.

Synthesis of Polysyllabic Sequences of Thai Tones Using a Generative Model of Fundamental Frequency Contours

Tomio Takara, Pusadee Seresangtakul, T. Takara, 2005 .

ESAP plus: a web-based server for EST-SSR marker development

S. Tongsima, J. Ponsawat, C. Akkasaeng, 2016, BMC Genomics.

Thai finger-spelling sign language recognition using global and local features with SVM

Pusadee Seresangtakul, Thongpan Pariwat, Pusadee Seresangtakul, 2017, 2017 9th International Conference on Knowledge and Smart Technology (KST).

Python Code Smell Detection Using Machine Learning

Chitsutha Soomlek, Pusadee Seresangtakul, Natthida Vatanapakorn, 2022, 2022 26th International Computer Science and Engineering Conference (ICSEC).

Multi-Class Text Classification on Khmer News Using Ensemble Method in Machine Learning Algorithms

Chitsutha Soomlek, Pusadee Seresangtakul, Raksmey Phann, 2023, Acta Informatica Pragensia.

An Efficient Deep Learning for Thai Sentiment Analysis

Nattawat Khamphakdee, Pusadee Seresangtakul, 2023, Data.

An approach to Lao-English rule based machine translation

Pusadee Seresangtakul, Arounyadeth Srithirath, Pusadee Seresangtakul, 2015, 2015 7th International Conference on Knowledge and Smart Technology (KST).

Isarn Dharma Word Segmentation Using a Statistical Approach with Named Entity Recognition

Pusadee Seresangtakul, Sittichai Somsap, Pusadee Seresangtakul, 2020, ACM Trans. Asian Low Resour. Lang. Inf. Process..

Fit Buddy: A Mobile Application for Fitness Tracking Using the Always-On Low-Power Sensor

Kasidit Wijitsopon, Chavalit Panichayanubal, Pusadee Seresangtakul, 2015 .