4 papers
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…
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…