This paper measures and analyzes the overuse of epanorthosis, a rhetorical figure, in large language models and proposes techniques to mitigate it.

A multimodal Mixture-of-Experts framework was developed for asthma detection using vocal biomarkers and clinical data, achieving better performance than unimodal and bimodal approaches.

The authors present ZONOS2 8B, a TTS model with improved naturalness, prosody, and voice cloning fidelity, achieved through scaling, data expansion, and simplification.

AccLock proposes a passive, zero-involvement user authentication system that uses unique biometric features from in-ear accelerometers (BCG signals) to achieve secure and unobtrusive identity verifica…

Introduces AlphaOracle, a human-workflow-inspired framework for deciphering undeciphered oracle bone script characters using a large digitized corpus, reducing analysis time and agreeing with expert i…

This paper introduces Svarna, a free, open-source web-based corpus workbench for modern Greek, integrating five databases and providing various tools for analysis.

This paper proposes EscFOA, a framework that uses geometry-aware spatial audio to enhance immersive educational environments for visually impaired learners, outperforming conventional audio methods.

The paper introduces FAM-Bench, a novel multimodal benchmark designed to test advanced, condition-aware reasoning for food-as-medicine applications.

The paper introduces CaReCoS, a benchmark for multimodal reasoning over medical acoustic spectrograms, and evaluates the performance of vision and omni models, finding a maximum accuracy of 51.2%.

The paper introduces SPEARBench, a benchmark for evaluating naturalness in speech-to-speech language models using a multidimensional protocol.

This paper proposes a novel pretraining method for Acoustic-to-Articulatory Inversion (AAI) using Phoneme Labels, Articulatory Feature Labels, and Critical-articulator Labels, improving performance an…

The paper introduces REST-ASMR, a novel multimodal dataset combining PPG and behavioral responses to ASMR and nature videos, and demonstrates that a deep learning model can accurately predict ASMR tin…

This paper investigates neural activity during five auditory conditions using EEG recordings from a 5-year-old participant, revealing condition-specific modulation of neural oscillatory activity and d…

The study investigates the limitations of Phonetic Foundation Models (PFMs) for Speech-to-IPA transcription using Grapheme-to-Phoneme (G2P) labels and proposes a new approach based on continuous Artic…

The paper proposes a simulation-trained variable impedance control framework for wearable exoskeletons that safely and effectively augments human physical capabilities across multiple tasks.

The paper introduces GigaSpeechBench, a comprehensive multilingual and multidimensional ASR & AST benchmark with 680 hours of human-annotated speech, featuring 12 low-resource languages, 6 Chinese dia…

AutoForest is an end-to-end system that automatically generates publication-ready forest plots directly from biomedical papers, streamlining the labor-intensive process of meta-analysis.

The paper introduces a reliability-oriented framework, IndicBERT-HPA, for multilingual orthopedic decision support from clinical narratives, achieving high performance and significantly improving reli…