12 citations · 12 across the 7 of their papers we have counts for
4 papers · 1 filter
DiffVQE2: An Efficient Low-delay Diffusion Model for Acoustic Echo and Noise Control
Haljan Lugo, Ernst Seidel, Pejman Mowlaee +2
Hands-free communication devices and speakerphones are inherently affected by acoustic echo and background noise. To mitigate these impairments, end-to-end discriminatively trained…
Perceptually Better, Semantically Worse: Measuring Speech Enhancement Impact on LLM-Based Voice Systems
Randy Frans Fela, Pejman Mowlaee
Speech enhancement (SE) is commonly applied as a preprocessing step in spoken AI pipelines under the assumption that better audio quality improves downstream task performance. Whet…
Knowledge Distillation for Efficient Acoustic Echo Control
Ernst Seidel, Pejman Mowlaee, Tim Fingscheidt
In recent years, many efforts have been made to supersede classical acoustic echo control (AEC) algorithms with more powerful machine-learned approaches. While surpassing the perfo…
DiffVQE: Hybrid Diffusion Voice Quality Enhancement Under Acoustic Echo and Noise
Haljan Lugo, Ernst Seidel, Pejman Mowlaee +2
Acoustic echo and background noise pose challenges on speech enhancement in hands-free systems and speakerphones. Discriminatively trained end-to-end methods represent a powerful s…