Face masks are mandatory during the COVID-19 pandemic, leading to attenuation of sound energy and loss of visual cues which are important for communication. This study explores how a face mask affects speech performance for individuals with and without hearing loss. Four video recordings (a female speaker with and without a face mask and a male speaker with and without a face mask) were used to examine individuals’ speech performance. The participants completed a listen-and-repeat task while watching four types of video recordings. Acoustic characteristics of speech signals based on mask type (no mask, surgical, and N95) were also examined. The availability of visual cues was beneficial for speech understanding—both groups showed significant improvements in speech perception when they were able to see the speaker without the mask. However, when the speakers were wearing the mask, no statistical significance was observed between no visual cues and visual cues conditions. Findings of the study demonstrate that provision of visual cues is beneficial for speech perception for individuals with normal hearing and hearing impairment. This study adds value to the importance of the use of communication strategies during the pandemic where visual information is lost due to the face mask.

Background and Objectives: Determining the presence or absence of cochlear dead regions (DRs) is essential in clinical practice. This study proposes a machine learning (ML)-based model that applies oversampling techniques for predicting DRs in patients. Materials and Methods: We used recursive partitioning and regression for classification tree (CT) and logistic regression (LR) as prediction models. To overcome the imbalanced nature of the dataset, oversampling techniques to duplicate examples in the minority class or to synthesize new examples from existing examples in the minority class were adopted, namely the synthetic minority oversampling technique (SMOTE). Results: The accuracy results of the 10-fold cross-validation of the LR and CT with the original data were 0.82 (±0.02) and 0.93 (±0.01), respectively. The accuracy results of the 10-fold cross-validation of the LR and CT with the oversampled data were 0.66 (±0.02) and 0.86 (±0.01), respectively. Conclusions: This study is the first to adopt the SMOTE method to assess the role of oversampling methods on audiological datasets and to develop an ML-based model. Considering that the SMOTE method did not improve the model’s performance, a more flexible model or more clinical features may be needed.

Purpose: This study explores the influence of the noise-canceling technology in commercial earphones on sound pressure levels and preferred listening levels in terms of hearing protection. Materials and Methods: Thirty individuals completed puretone audiometry and real-ear measurements to assess sound pressure levels at the level of the eardrum with and without the activation of the noise-canceling function. The Knowles Electronics Manikin for Acoustic Research was used to investigate the acoustic characteristics of two environmental sounds (bus and café). Two types of earphones (wireless and wired canal type) were utilized in the study. Results: For both bus and café noises, in the low-frequency range, sound pressure levels were significantly decreased for all types of earphones when the noise-canceling function was turned on. The same results were observed for the whole frequency range. In terms of preferred listening levels, the wireless canal type and wired canal type earphones showed significant reduction in volume levels. Conclusion: The findings of the study show that for both low- and whole frequency range, the use of noise-canceling function significantly decreases the sound pressure levels of the signal for all styles of earphones, suggesting a potential of the noise-canceling technology in hearing protection.