arXiv subjects

Seunghyun Oh

Publications and source records attributed to Seunghyun Oh.

4 recordsLinked to original sources

arXiv2026

Fine-grained Soundscape Control for Augmented Hearing

Hearables are becoming ubiquitous, yet their sound controls remain blunt: users can either enable global noise suppression or focus on a single target sound. Real-world acoustic scenes, however, contain many simultaneous sources that users may want to adjust independently. We introduce Aurchestra, the first system to provide fine-grained, real-time soundscape control on resource-constrained hearables. Our system has two key components: (1) a dynamic interface that surfaces only active sound classes and (2) a real-time, on-device multi-output extraction network that generates separate streams for each selected class, achieving robust performance for upto 5 overlapping target sounds, and letting users mix their environment by customizing per-class volumes, much like an audio engineer mixes tracks. We optimize the model architecture for multiple compute-limited platforms and demonstrate real-time performance on 6 ms streaming audio chunks. Across real-world environments in previously unseen indoor and outdoor scenarios, our system enables expressive per-class sound control and achieves substantial improvements in target-class enhancement and interference suppression. Our results show that the world need not be heard as a single, undifferentiated stream: with Aurchestra, the soundscape becomes truly programmable.

cs.SD↗

arXiv2026

OV-Stitcher: A Global Context-Aware Framework for Training-Free Open-Vocabulary Semantic Segmentation

Training-free open-vocabulary semantic segmentation(TF-OVSS) has recently attracted attention for its ability to perform dense prediction by leveraging the pretrained knowledge of large vision and vision-language models, without requiring additional training. However, due to the limited input resolution of these pretrained encoders, existing TF-OVSS methods commonly adopt a sliding-window strategy that processes cropped sub-images independently. While effective for managing high-resolution inputs, this approach prevents global attention over the full image, leading to fragmented feature representations and limited contextual reasoning. We propose OV-Stitcher, a training-free framework that addresses this limitation by stitching fragmented sub-image features directly within the final encoder block. By reconstructing attention representations from fragmented sub-image features, OV-Stitcher enables global attention within the final encoder block, producing coherent context aggregation and spatially consistent, semantically aligned segmentation maps. Extensive evaluations across eight benchmarks demonstrate that OV-Stitcher establishes a scalable and effective solution for open-vocabulary segmentation, achieving a notable improvement in mean Intersection over Union(mIoU) from 48.7 to 50.7 compared with prior training-free baselines.

cs.CV↗

arXiv2025

Reference compositions for bismuth telluride thermoelectric materials for low-temperature power generation

Thermoelectric (TE) technology enables direct heat-to-electricity conversion and is gaining attention as a clean, fuel-saving, and carbon-neutral solution for industrial, automotive, and marine applications. Despite nearly a century of research, apart from successes in deep-space power sources and solid-state cooling modules, the industrialization and commercialization of TE power generation remain limited. Since the new millennium, nanostructured bulk materials have accelerated the discovery of new TE systems. However, due to limited access to high-temperature heat sources, energy harvesting still relies almost exclusively on BiTe-based alloys, which are the only system operating stably near room temperature. Although many BiTe-based compositions have been proposed, concerns over reproducibility, reliability, and lifetime continue to hinder industrial adoption. Here, we aim to develop reference BiTe-based thermoelectric materials through data-driven analysis of Starrydata2, the world's largest thermoelectric database. We identify Bi0.46Sb1.54Te3 and Bi2Te2.7Se0.3 as the most frequently studied ternary compositions. These were synthesized using hot pressing and spark-plasma sintering. Thermoelectric properties were evaluated with respect to the processing method and measurement direction. The results align closely with the median of reported data, confirming the representativeness of the selected compositions. We propose these as reference BiTe materials, accompanied by transparent data and validated benchmarks. Their use can support the standardization of TE legs and modules while accelerating performance evaluation and industrial integration. We further estimated the performance of a thermoelectric module made from the reference composition, which gives the power output of over 2.51 W and an efficiency of 3.58% at a temperature difference of 120 K.

cond-mat.mtrl-sci↗

arXiv2024

Wiedemann-Franz Law and Thermoelectric Inequalities: Effective ZT and Single-leg Efficiency Overestimation

We derive a thermoelectric inequality in thermoelectric conversion between the material figure of merit (ZT) and the module effective ZT using the Constant Seebeck-coefficient Approximation combining with the Wiedemann-Franz law. In a P-N leg-pair module, the effective ZT lies between the individual ZT values of the P- and N-legs. In a single-leg module, however, the effective ZT is less than approximately one-third of the leg's ZT. This reduction results from the need for an external wire to complete the circuit, introducing additional thermal and electrical losses. Multi-dimensional numerical analysis shows that, although structural optimization can mitigate these losses, the system efficiency remains limited to below half of the ideal single-leg material efficiency. Our findings explain the single-leg efficiency overestimation and highlight the importance of optimizing the P-N leg-pair module structure. They also underscore the need for thermoelectric leg-compatibility, particularly with respect to Seebeck coefficients.

physics.app-ph↗