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20202026
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eess.AS2026

Teacher-Free Self-Distilled Consistency Trajectory Learning for Fast Speech Enhancement

Shuubham Ojha, Carol Espy-Wilson

Consistency trajectory models offer a route to fast, high- quality speech enhancement, collapsing the many reverse steps of diffusion-based enhancers into a handful. When instantia…

eess.AS2026

A Variational-Flow Analysis of Diffusion-Based Speech Enhancement under Noise-Power Mismatch

Shuubham Ojha

Diffusion-based speech enhancement architectures that pair a deterministic predictor with a learned score network, exhibit a sharp non-smooth transition (``kink'') in the SI-SDR de…

eess.AS2026

CaReCoS: A Spectrogram based Visual Benchmark for Cardiac, Respiratory and Cough Sounds

Harshit Rajgarhia, Shuubham Ojha, Akhil Pothanapalli +4

Medical acoustic signals such as respiratory sounds, cardiac auscultations, and cough audio carry rich diagnostic information, yet no existing benchmark evaluates multimodal reason…

eess.AS2026

Bridging Self-Supervised Learning and Speech Enhancement: A Wav2Vec2-Conditioned Framework

Shuubham Ojha, Carol Espy-Wilson

Diffusion models show potential for speech enhancement but lack linguistic guidance. We condition a diffusion-based model on wav2vec 2.0 features from noisy input, injected at the…

eess.AS2025

Reverse Attention for Lightweight Speech Enhancement on Edge Devices

Shuubham Ojha, Felix Gervits, Carol Espy-Wilson

This paper introduces a lightweight deep learning model for real-time speech enhancement, designed to operate efficiently on resource-constrained devices. The proposed model levera…