arXiv subjects

Duy Vo

Publications and source records attributed to Duy Vo.

3 recordsLinked to original sources

arXiv2026

SETEAB: Multiscale approach with Squeeze-and-Excitation Temporal Enhanced Aware Block for Speech Emotion Recognition

This paper proposes a novel lightweight multiscale architecture for speech emotion recognition (SER) with three key innovations. First, a depthwise convolution-based subsampling module is introduced to reduce model size and computation while preserving salient emotional cues. Second, a Squeeze-and-Excitation block is integrated to enhance channel-wise recalibration and improve representation robustness. Third, a new Temporal Enhanced Aware Block is designed to strengthen temporal dependency modeling and produce more discriminative emotion-aware features. The proposed model is explicitly designed to jointly improve compactness, recognition performance, and generalizability. Experiments on benchmark SER datasets show that our method achieves higher accuracy with reduced computational complexity, while also delivering stronger cross-corpus performance than most recent advanced networks for SER.

eess.AS↗

arXiv2026

ViP-VL: Vietnamese Self-supervised Speech Pretraining Model with Vector-Quantization Learning

We present ViP-VL, an efficient Vietnamese Self-supervised speech Pretraining model leveraging Vector-quantization Learning. To bridge the gap between high-resolution audio and efficient processing, ViP-VL incorporates Acoustic Stacking and Receptive Field Alignment to enable a synchronized 8x subsampling rate within the ChunkFormer architecture, while further enhancing representation robustness through a specialized Mask Selection Strategy during pretraining on the BEST-RQ framework. Pretrained on 17,000 hours of unlabeled Vietnamese speech, our model establishes new state-of-the-art results across four major downstream tasks: Automatic Speech Recognition, Speech Emotion Recognition, Dialect Classification, and Speaker Verification. To facilitate future research and the development of high-performance Vietnamese speech technologies, we publicly release our pretrained weights and implementation at github.com/khanld/chunkformer.

cs.SD↗

arXiv2026

Statistical Firefly Algorithm for Truss Topology Optimization

This study proposes an algorithm titled a statistical firefly algorithm (SFA) for truss topology optimization. In the proposed algorithm, historical results of fireflies' motions are used in hypothesis testing to limit the motions of fireflies that are suggested by current information exchanges between fireflies only to those that are potentially useful. Hypothesis testing is applied to the mechanism of an ordinary firefly algorithm (FA) without changing its structure. As a result, the implementation of the proposed algorithm is simple and straightforward. Limiting the motions of fireflies to those that are potential useful results in reduction of firefly evaluations, and, subsequently, reduction of computational efforts. To test the validity and efficiency of the proposed algorithm, it is used to solve several truss topology optimization problems, including some benchmark problems. It is found that the added statistical strategy in the SFA significantly enhances the performance of the original FA in terms of computational efforts while still maintains the quality of the obtained results.

cs.NE↗