8 papers
myMediWhisper: Construction of Burmese Medical Speech Corpus and Whisper Fine-Tuning for Clinical Dialogue ASR
Ye Kyaw Thu, Ye Bhone Lin, Thura Aung +6
Although Whisper models benefit from large-scale multilingual pre-training, their performance on Burmese medical speech remains limited. This work presents a Burmese medical speech…
Comparative Analysis of Liquid Neural Networks and LSTM for Sequential Pattern Recognition: Robustness, Efficiency, and Clinical Utility
Ye Kyaw Thu, Thazin Myint Oo, Thepchai Supnithi
Traditional Recurrent Neural Networks (RNNs) and Long Short-Term Memory (LSTM) units operate on discrete time steps, often failing to capture the fluid temporal dynamics of real-wo…
myMNIST: Benchmark of PETNN, KAN, and Classical Deep Learning Models for Burmese Handwritten Digit Recognition
Ye Kyaw Thu, Thazin Myint Oo, Thepchai Supnithi
We present the first systematic benchmark on a standardized iteration of the publicly available Burmese Handwritten Digit Dataset (BHDD), which we have designated as myMNIST Benchm…
ASR Error Correction in Low-Resource Burmese with Alignment-Enhanced Transformers using Phonetic Features
Ye Bhone Lin, Thura Aung, Ye Kyaw Thu +1
This paper investigates sequence-to-sequence Transformer models for automatic speech recognition (ASR) error correction in low-resource Burmese, focusing on different feature integ…
Enhancing Burmese News Classification with Kolmogorov-Arnold Network Head Fine-tuning
Thura Aung, Eaint Kay Khaing Kyaw, Ye Kyaw Thu +2
In low-resource languages like Burmese, classification tasks often fine-tune only the final classification layer, keeping pre-trained encoder weights frozen. While Multi-Layer Perc…
KAConvText: Novel Approach to Burmese Sentence Classification using Kolmogorov-Arnold Convolution
Ye Kyaw Thu, Thura Aung, Thazin Myint Oo +1
This paper presents the first application of Kolmogorov-Arnold Convolution for Text (KAConvText) in sentence classification, addressing three tasks: imbalanced binary hate speech d…
Reconstructing Syllable Sequences in Abugida Scripts with Incomplete Inputs
Ye Kyaw Thu, Thazin Myint Oo
This paper explores syllable sequence prediction in Abugida languages using Transformer-based models, focusing on six languages: Bengali, Hindi, Khmer, Lao, Myanmar, and Thai, from…
myNER: Contextualized Burmese Named Entity Recognition with Bidirectional LSTM and fastText Embeddings via Joint Training with POS Tagging
Kaung Lwin Thant, Kwankamol Nongpong, Ye Kyaw Thu +3
Named Entity Recognition (NER) involves identifying and categorizing named entities within textual data. Despite its significance, NER research has often overlooked low-resource la…