Eric M. Johnson

West Virginia University | WVU · School of Medicine

Recent years have brought considerable advances to our ability to increase intelligibility through deep-learning-based noise reduction, especially for hearing-impaired (HI) listeners. In this study, intelligibility improvements resulting from a current algorithm are assessed. These benefits are compared to those resulting from the initial demonstra...

Environmental sound recognition is an essential part of the human auditory experience that not only provides a sense of connection to one’s surroundings but also forecasts potential nearby safety hazards. Unfortunately, important environmental sounds can be rendered inaudible or otherwise unrecognizable by modern noise-reduction technology, leading...

The fundamental requirement for real-time operation of a speech-processing algorithm is causality—that it operate without utilizing future time frames. In the present study, the performance of a fully causal deep computational auditory scene analysis algorithm was assessed. Target sentences were isolated from complex interference consisting of an i...

The practical efficacy of deep learning based speaker separation and/or dereverberation hinges on its ability to generalize to conditions not employed during neural network training. The current study was designed to assess the ability to generalize across extremely different training versus test environments. Training and testing were performed us...

Real-time operation is critical for noise reduction in hearing technology. The essential requirement of real-time operation is causality—that an algorithm does not use future time-frame information and, instead, completes its operation by the end of the current time frame. This requirement is extended currently through the concept of “effectively c...

Deep learning based speech separation or noise reduction needs to generalize to voices not encountered during training and to operate under multiple corruptions. The current study provides such a demonstration for hearing-impaired (HI) listeners. Sentence intelligibility was assessed under conditions of a single interfering talker and substantial a...

Purpose This preliminary investigation compared effects of time compression on intelligibility for male versus female talkers. We hypothesized that time compression would have a greater effect for female talkers. Method Sentence materials from four talkers (two males) were time compressed, and original-speed and time-compressed speech materials we...

No PDF available ABSTRACT Recently, deep learning based speech segregation has been shown to improve human speech intelligibility in noisy environments. However, one important factor not yet considered is room reverberation, which characterizes typical daily environments. The combination of reverberation and background noise can severely degrade sp...

No PDF available ABSTRACT For deep learning based speech segregation to have translational significance as a noise-reduction tool, it must perform in a wide variety of acoustic environments. In the current study, performance was examined when target speech was subjected to interference from a single talker and room reverberation. Conditions were co...

Nonnative (L2) English learners are often assumed to exhibit greater speech production variability than native (L1) speakers; however, support for this assumption is primarily limited to secondary observations rather than having been the specific focus of empirical investigations. The present study examined intra-speaker variability associated with...

For deep learning based speech segregation to have translational significance as a noise-reduction tool, it must perform in a wide variety of acoustic environments. In the current study, performance was examined when target speech was subjected to interference from a single talker and room reverberation. Conditions were compared in which an algorit...

Recently, deep learning based speech segregation has been shown to improve human speech intelligibility in noisy environments. However, one important factor not yet considered is room reverberation, which characterizes typical daily environments. The combination of reverberation and background noise can severely degrade speech intelligibility for h...

Previous research has shown that English-speaking learners of Russian, even those with advanced proficiency, often have not acquired the contrast between palatalized and unpalatalized consonants, which is a central feature of the Russian consonant system. The present study examined whether training utilizing electropalatography (EPG) could help a g...

Older adults seeking hearing help often complain of particular difficulty understanding female voices. This contrasts with studies using young listeners with normal hearing in which female talkers have been found to be generally more intelligible than male talkers (e.g., Bradlow et al., 1996). Could some factor in addition to talker gender be causi...