Search Results for author:
Found 37 papers, 19 papers with code
Continual Learning in Machine Speech Chain Using Gradient Episodic Memory
Continual learning for automatic speech recognition (ASR) systems poses a challenge, especially with the need to avoid catastrophic forgetting while maintaining performance on previously learned tasks.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
DriveThru: a Document Extraction Platform and Benchmark Datasets for Indonesian Local Language Archives
However, most of these efforts have been focused on creating manual resources thus difficult to scale to more languages.
Optical Character Recognition
Optical Character Recognition (OCR)
WorldCuisines: A Massive-Scale Benchmark for Multilingual and Multicultural Visual Question Answering on Global Cuisines
This benchmark includes a visual question answering (VQA) dataset with text-image pairs across 30 languages and dialects, spanning 9 language families and featuring over 1 million data points, making it the largest multicultural VQA benchmark to date.
Enhancing Indonesian Automatic Speech Recognition: Evaluating Multilingual Models with Diverse Speech Variabilities
Currently, Indonesian data is dominated by read, formal, and clean speech, leading to a scarcity of Indonesian data with other speech variabilities.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
Towards Efficient and Robust VQA-NLE Data Generation with Large Vision-Language Models
Natural Language Explanation (NLE) aims to elucidate the decision-making process by providing detailed, human-friendly explanations in natural language.
SEACrowd: A Multilingual Multimodal Data Hub and Benchmark Suite for Southeast Asian Languages
Southeast Asia (SEA) is a region rich in linguistic diversity and cultural variety, with over 1, 300 indigenous languages and a population of 671 million people.
MLKV: Multi-Layer Key-Value Heads for Memory Efficient Transformer Decoding
Auto-regressive inference of transformers benefit greatly from Key-Value (KV) caching, but can lead to major memory bottlenecks as model size, batch size, and sequence length grow at scale.
Cendol: Open Instruction-tuned Generative Large Language Models for Indonesian Languages
To bridge this quality gap, we introduce Cendol, a collection of Indonesian LLMs encompassing both decoder-only and encoder-decoder architectures across a range of model sizes.
Could We Have Had Better Multilingual LLMs If English Was Not the Central Language?
Large Language Models (LLMs) demonstrate strong machine translation capabilities on languages they are trained on.
LinguAlchemy: Fusing Typological and Geographical Elements for Unseen Language Generalization
Pretrained language models (PLMs) have become remarkably adept at task and language generalization.
IndoRobusta: Towards Robustness Against Diverse Code-Mixed Indonesian Local Languages
Significant progress has been made on Indonesian NLP.
The Obscure Limitation of Modular Multilingual Language Models
We expose the limitation of modular multilingual language models (MLMs) in multilingual inference scenarios with unknown languages.
Indo LEGO-ABSA: A Multitask Generative Aspect Based Sentiment Analysis for Indonesian Language
Therefore, this research aims to implement the multitask learning and prompting approach in aspect-based sentiment analysis for Bahasa Indonesia using generative pre-trained language models.
Aspect-Based Sentiment Analysis
Aspect Sentiment Triplet Extraction
+3
Replicable Benchmarking of Neural Machine Translation (NMT) on Low-Resource Local Languages in Indonesia
Neural machine translation (NMT) for low-resource local languages in Indonesia faces significant challenges, including the need for a representative benchmark and limited data availability.
IndoToD: A Multi-Domain Indonesian Benchmark For End-to-End Task-Oriented Dialogue Systems
Task-oriented dialogue (ToD) systems have been mostly created for high-resource languages, such as English and Chinese.
Domain-Specific Language Model Post-Training for Indonesian Financial NLP
In this paper, we construct an Indonesian self-supervised financial corpus, Indonesian financial sentiment analysis dataset, Indonesian financial topic classification dataset, and release a family of BERT models for financial NLP.
QASiNa: Religious Domain Question Answering using Sirah Nabawiyah
This concludes Chat GPT is unsuitable for question answering task in religious domain especially for Islamic religion.
Low-Resource Clickbait Spoiling for Indonesian via Question Answering
Clickbait spoiling aims to generate a short text to satisfy the curiosity induced by a clickbait post.
NusaWrites: Constructing High-Quality Corpora for Underrepresented and Extremely Low-Resource Languages
We compare the effectiveness of online scraping, human translation, and paragraph writing by native speakers in constructing datasets.
NusaCrowd: Open Source Initiative for Indonesian NLP Resources
We present NusaCrowd, a collaborative initiative to collect and unify existing resources for Indonesian languages, including opening access to previously non-public resources.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
Sequential Labelling and DNABERT For Splice Site Prediction in Homo Sapiens DNA
Recent predictions are carried out with models trained on sequence with fixed splice site location which eliminates possibility of multiple splice sites existence in single sequence.
NusaCrowd: A Call for Open and Reproducible NLP Research in Indonesian Languages
At the center of the underlying issues that halt Indonesian natural language processing (NLP) research advancement, we find data scarcity.
Speech Artifact Removal from EEG Recordings of Spoken Word Production with Tensor Decomposition
Research about brain activities involving spoken word production is considerably underdeveloped because of the undiscovered characteristics of speech artifacts, which contaminate electroencephalogram (EEG) signals and prevent the inspection of the underlying cognitive processes.
A Comparative Study on Language Models for Task-Oriented Dialogue Systems
The recent development of language models has shown promising results by achieving state-of-the-art performance on various natural language tasks by fine-tuning pretrained models.
IndoNLG: Benchmark and Resources for Evaluating Indonesian Natural Language Generation
Natural language generation (NLG) benchmarks provide an important avenue to measure progress and develop better NLG systems.
Sequence-to-Sequence Learning for Indonesian Automatic Question Generator
Research in automatic question generator (AQG) has been conducted for more than 10 years, mainly focused on factoid question.
Improving Joint Layer RNN based Keyphrase Extraction by Using Syntactical Features
Since JRNN in general requires a large amount of data as the training examples and creating those examples is expensive, we used a data augmentation method to increase the number of training examples.
Combining Word and Character Vector Representation on Neural Machine Translation
This paper describes combinations of word vector representation and character vector representation in English-Indonesian neural machine translation (NMT).
Improving Bi-LSTM Performance for Indonesian Sentiment Analysis Using Paragraph Vector
Meanwhile, in the problem scope of Indonesian sentiment analysis, phrases that express the sentiment of a document might not appear in the first or last part of the document that can lead to incorrect sentiment classification.
Improving Indonesian Text Classification Using Multilingual Language Model
Using the feature-based approach, we observe its performance on various data sizes and total added English data.
Coreference Resolution System for Indonesian Text with Mention Pair Method and Singleton Exclusion using Convolutional Neural Network
In this paper, we propose a new coreference resolution system for Indonesian text with mention pair method that uses deep neural network to learn the relations of the two mentions.
IndoNLU: Benchmark and Resources for Evaluating Indonesian Natural Language Understanding
Although Indonesian is known to be the fourth most frequently used language over the internet, the research progress on this language in the natural language processing (NLP) is slow-moving due to a lack of available resources.
Investigating Bi-LSTM and CRF with POS Tag Embedding for Indonesian Named Entity Tagger
The second is the usage of part of speech (POS) tag embedding input layer.
Indonesian Social Media Sentiment Analysis With Sarcasm Detection
Sarcasm is considered one of the most difficult problem in sentiment analysis.
