The field of speech processing has undergone a transformative shift with the advent of deep
learning. The use of multiple processing layers has enabled the creation of models capable …

Recent advancements in deep learning (DL) have posed a significant challenge for
automatic speech recognition (ASR). ASR relies on extensive training datasets, including …

We present NusaCrowd, a collaborative initiative to collect and unify existing resources for
Indonesian languages, including opening access to previously non-public resources …

Scaling sequence length has become a critical demand in the era of large language models.
However, existing methods struggle with either computational complexity or model …

Large Language Models (LLMs) have demonstrated remarkable capabilities in important
tasks such as natural language understanding and language generation, and thus have the …

Transformer model architectures have garnered immense interest lately due to their
effectiveness across a range of domains like language, vision, and reinforcement learning …

Transfer learning has recently become the dominant paradigm of machine learning. Pre-
trained models fine-tuned for downstream tasks achieve better performance with fewer …

Automatic speech recognition (ASR) has recently become an important challenge when
using deep learning (DL). It requires large-scale training datasets and high computational …

Large Language Models (LLMs) have attracted extensive attention due to their remarkable
performance across various tasks. However, the substantial computational and memory …

Generating speech-consistent body and gesture movements is a long-standing problem in
virtual avatar creation. Previous studies often synthesize pose movement in a holistic …