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Stephen D. Voran

2 accepted papers

2020

Wawenets: A No-Reference Convolutional Waveform-Based Approach to Estimating Narrowband and Wideband Speech Quality

ICASSP 2020accepted

Building on prior work we have developed a no-reference (NR) waveform-based convolutional neural network (CNN) architecture that can accurately estimate speech quality or intelligibility of narrowband and wideband speech segments. These Wideband Audio Waveform Evaluation Networks, or WAWEnets, achie…

Cited by 0SourceScholar
2017

A multiple bandwidth objective speech intelligibility estimator based on articulation index band correlations and attention

ICASSP 2017accepted

We present ABC-MRT16-a new algorithm for objective estimation of speech intelligibility following the Modified Rhyme Test (MRT) paradigm. ABC-MRT16 is simple, effective and robust. When compared to subjective MRT data from 367 diverse conditions that include coding, noise, frame erasures, and much m…

Cited by 0SourceScholar