Face mask effects on speaker verification performance in the presence of noise.

Due to its spread via physical contact and the regulations on wearing face masks, COVID-19 has resulted in tough challenges for speaker recognition. Masks may aid in preventing COVID-19 transmission, although the implications of the mask on system performance in a clean environment and with varying levels of background noise are unclear. The face mask has an impact on speech output. The task of comprehending speech while wearing a face mask is made more difficult by the mask's frequency response and radiation qualities, which is vary depending on the material and design of the mask. In this study, we recorded speech while wearing a face mask to see how different masks affected a state-of-the-art text-independent speaker verification system using an i-vector speaker identification system. This research investigates the influence of facial coverings on speaker verification. To address this, we investigated the effect of fabric masks on speaker identification in a cafeteria setting. These results present preliminary speaker recognition rates as well as mask verification trials. The result shows that masks had little to no effect in low background noise, with an EER of 2.4-2.5% in 20 dB SNR for both masks compared to no mask at the same level. In noisy conditions, accuracy was 12.7-13.0% lowers than without a mask with a 5 dB SNR, indicating that while different masks perform similarly in low background noise levels, they become more noticeable in high noise levels.

Modelling Proper and Improper Sitting Posture of Computer Users Using Machine Vision for a Human–Computer Intelligent Interactive System during COVID-19

Featured ApplicationThe study could be used for sitting posture monitoring in a work-from-home setup. This could also be used for rehabilitation purposes of patients who has posture-related problems.Human posture recognition is one of the most challenging tasks due to the variation in human appearance, changes in the background and illumination, additional noise in the frame, and diverse characteristics and amount of data generated. Aside from these, generating a high configuration for recognition of human body parts, occlusion, nearly identical parts of the body, variations of colors due to clothing, and other various factors make this task one of the hardest in computer vision. Therefore, these studies require high-computing devices and machines that could handle the computational load of this task. This study used a small-scale convolutional neural network and a smartphone built-in camera to recognize proper and improper sitting posture in a work-from-home setup. Aside from the recognition of body points, this study also utilized points' distances and angles to help in recognition. Overall, the study was able to develop two objective datasets capturing the left and right side of the participants with the supervision and guidance of licensed physical therapists. The study shows accuracies of 85.18% and 92.07%, and kappas of 0.691 and 0.838, respectively. The system was developed, implemented, and tested in a work-from-home environment.

Acoustic Comfort in Hybrid Learning Spaces: Students Perspective

Acoustic comfort in classrooms has a great impact on the quality of education. In specific, its impact on teaching and learning experience has been widely studied and the results show that acoustic comfort is linked to learning attributes, e.g. enhancing productivity, memorizing and understanding of the taught material, mental welfare, and motivation. In this paper, we assess the acoustic comfort in hybrid classrooms, at the University of Sharjah, after classes have been reconfigured to comply with COVID-19 social distancing protocols. First, we measured the background noise and reverberation times for different types of classrooms used for teaching and learning. The results showed that most classrooms do not comply with international standards. For example, the background noise levels in the selected classrooms were found to range from 43.9-49.6 dB(A), which is higher than the recommended WHO limits. To evaluate the acoustic comfort from the perspective of the students, a survey was conducted to evaluate students' perception on acoustic conditions at the hybrid classrooms. The results showed that the majority of the students surveyed, 88%, felt that noise in classrooms affected their understanding of the material and communications with the instructor and peers. Noise sources were identified to originate from corridors, maintenance work, and construction sites within close proximity to the classrooms. Better designs are highly recommended to improve acoustic comfort to ensure an excellent student experience and the best learning environment. © 2022 Internoise 2022 - 51st International Congress and Exposition on Noise Control Engineering. All rights reserved.

Suppression of Background Noise in Speech Signals with Artificial Neural Networks, Exemplarily Applied to Keyboard Sounds

The importance of remote voice communication has greatly increased during the COVID-19 pandemic. With that comes the problem of degraded speech quality because of background noise. While there can be many unwanted background sounds, this work focuses on dynamically suppressing keyboard sounds in speech signals by utilizing artificial neural networks. Based on the Mel spectrograms as inputs, the neural networks are trained to predict how much power of a frequency inside a time window has to be removed to suppress the keyboard sound. For that goal, we have generated audio signals combined from samples of two publicly available datasets with speaker and keyboard noise recordings. Additionally, we compare three network architectures with different parameter settings as well as an open-source tool RNNoise. The results from the experiments described in this paper show that artificial neural networks can be successfully applied to remove complex background noise from speech signals. Copyright © 2022 by SCITEPRESS - Science and Technology Publications, Lda.

The Influence of Face Masks on Verbal Communication in Persian in the Presence of Background Noise in Healthcare Staff.

Wearing face masks has resulted in verbal communication being more challenging during the COVID-19 pandemic. This study aimed to investigate the effect of face masks on the speech comprehensibility of Persian nurses in healthcare settings. Twenty female nurses from the governmental hospitals randomly participated in an experiment on seven typical commercial face masks at two background noise levels. Nurses' speech intelligibility from a human talker when wearing each face mask was determined based on the speech discrimination score. The vocal effort of nurses wearing each face mask was determined based on the Borg CR10 scale. Based on the linear mixed model, the speech intelligibility of nurses from a human speaker wearing surgical masks, N95 masks, and a shield with face masks were approximately 10%, 20%, and 40-50% lower, respectively, than no-mask conditions (p < 0.01). The background noise decreased the speech intelligibility of nurses by approximately 22% (p < 0.01). The use of a face shield further decreased speech intelligibility up to 30% compared to using a face mask alone (p < 0.01). The vocal efforts of nurses when wearing surgical masks were not significant compared with the baseline vocal efforts (p > 0.05); however, vocal efforts of nurses when wearing N95 and N99 respirators were at an unacceptable level. The face masks had no considerable effect on the speech spectrum below 2.5 kHz; however, they reduced high frequencies by different values. Wearing face masks has a considerable impact on the verbal communication of nurses in Persian. The level of background noise in the healthcare setting can aggravate the effect sizes of face masks on speech comprehensibility.

The dynamics of the first wave of COVID-19 on environment and wildlife– a boon or a bane?

Even though COVID-19 has drastically weighed upon the humankind, still there is a "silver lining" to see in this dark time. Amidst of this pandemic, most of the human activities were restricted to break the chain of infection which resulted the remarkable change in nature. It has been reported that due to halt in air travel, reduction in the use of fossil fuels, way less functioning of vehicles, shutdown of industries has complied the change in air pollution levels and also change in river water quality. Reports also showed the reduction in particulate matter (PM 2.5 and PM 10), greenhouse gases emissions, massive improvement in the Air quality index (AQI), reduction in the NOX and SOX's levelhas clearly stipulated that nature has got it's time to "revive". Even the global carbon emission has reported to reduced reluctantly which is expected to be the biggest such drop since World War II. Despite conducting water-cleansing projects and spending a lot of money, the situation of the water bodies were far better now during first lockdown. Moreover, migration and breeding of the birds and animals have been reported to be restored to normal pattern due to depletion in man-animal conflict. Apart from the positive, negative impacts on the nature are also being experienced. Our review work is highlighting such impacts witnessed during the first wave of COVID-19, like, the significant improvement in air and water quality, reduction in environmental noise, therefore an in turn cleaner and quieter habitat for the wildlife to mate and also to quench their curiosities by their surprising excursions;but there are also some negative aspects as well, like reduction in recycling and the increase in waste, increased poaching and even lone shuttering of zoo animals.

Characterization of Electron Beams from a Dense Plasma Focus

Research was conducted in an effort to study the physics of high-energy electron beams generated in a dense plasma focus (DPF). The effort consisted of both theoretical and experimental approaches. Theoretical calculations were performed using various non-local thermodynamic equilibrium (non-LTE) kinetic models to identify line candidates that would exhibit a measureable degree of polarization. Experiments carried out on Hawk tested different gases in the gas-puff nozzle at varying pressures. A convex crystal spectrometer was benchmarked using different crystals and filters, and was mounted on the Hawk chamber for collection of spectroscopic data. This memorandum summarizes the overall results of the project.

Urban activity monitoring using wireless geophones in Singapore

Urban activities in megacities around the world are not only the most severely impacted by the COVID-19 pandemic, but also the most consequential for the effectiveness of the mitigation measures. Therefore, monitoring and understanding the realtime changes of different sectors of an urban society is vital for policy making and dynamic pandemic management. By analyzing the high-frequency seismic signals, we separate the motor vehicle signal and the runner signal from the environment and background noise. We quantify the impact of the pandemic and its corresponding mitigation measures as traffic flow at nonessential workplaces, essential workplaces, and recreational areas. Enabled by the anonymity of seismic data, our study achieves an unprecedented spatial and temporal resolution that is pivotal to understand the heterogeneity and evolution of pandemic responses in different sectors of an urban society. The rich seismic-derived information provide a unique opportunity for realtime urban activity monitoring and dynamic policy making to ensure a successful pandemic mitigation while minimizing negative impacts on urban lifestyle. © 2021 Society of Exploration Geophysicists First International Meeting for Applied Geoscience & Energy

Short report on the effects of SARS-CoV-2 face protective equipment on verbal communication.

OBJECTIVE: To predict the impact of face personal protective equipment on verbal communication during the SARS-CoV-2 pandemic. DESIGN: We assessed the effect of common types and combinations of face personal protective equipment on speech intelligibility in quiet and in a simulated noisy environment. RESULTS: Wearing face personal protective equipment impairs transmission of middle-to-high voice frequencies and affects speech intelligibility. Surgical masks are responsible for up to 23.3% loss of speech intelligibility in noisy environments. The effects are larger in the condition of advanced face personal protective equipment, accounting for up to 69.0% reduction of speech intelligibility. CONCLUSION: The use of face personal protective equipment causes significant verbal communication issues. Healthcare workers, school-aged children, and people affected by voice and hearing disorders may represent specific at-risk groups for impaired speech intelligibility.

Voice symptoms in teachers during distance teaching: a survey during the COVID-19 pandemic in Finland.

PURPOSE: Due to the coronavirus disease of 2019 (COVID-19), teachers during the pandemic have had to adapt to online teaching at short notice. This study aims to investigate the voice symptoms and their environmental risk factors as well as the work ability associated with distance teaching and to compare these with symptoms in previous contact teaching. METHODS: We conducted a survey of 121 primary and secondary school teachers across Finland. The survey was advertised online through social media and the replies collected from voluntarily participating teachers. RESULTS: During distance teaching vocal symptoms appeared less often than in school with 71% teachers experiencing them in regular teaching and 44% in distance teaching, VHI result decreased from 7.88 in school teaching to 4.58 in distance teaching. Acoustic conditions were reported to be more suitable in distance teaching with 73% of teachers finding them adequate during distance teaching in comparison to 46% for those in regular teaching. Background noise was the most disturbing factor for a teacher's voice in the classroom and in distance teaching and this was even more conspicuous in the classroom. Also, subjectively experienced poor indoor air quality at school influenced the voice negatively. Further, voice problems were associated with increased subjective stress levels and reduced ability to work. CONCLUSION: Distance teaching has affected teachers' voices in a positive way compared with regular teaching. This difference is likely to be due to better acoustics and indoor air quality in distance teaching conditions.

The implications of hearing loss on a medical student: A personal view and learning points for medical educators.

Due to the widening access to medicine scheme, students with disabilities are entering medicine. Hearing-impaired students are an important subcategory of medical students, whose specific learning challenges with respect to medicine are poorly explored in the literature. We feel that this topic is particularly important and relevant given the current covid-19 pandemic, which has led to the widespread use of surgical masks, thereby posing a barrier to hearing, communication and education for hearing-impaired medical students. Therefore, the medical education of these students is of even more paramount importance as the pandemic continues. This personal view details the experiences of a current hearing-impaired medical student in the United Kingdom, with key learning points for medical educators who may require insight into hearing loss and how to tailor their teaching techniques accordingly.