Individual Audio Research Articles

Case Study of Innovative Second Language Learning Activities for Saudi Women Undergraduates Learning English

Gardner described second language (L2) instrumental motivation, where the learning goal is practical application, and Dörnyei described L2 motivation based on the learner’s vision of their future, ideal L2 self. In the Arabic-speaking Kingdom of Saudi Arabia (KSA), Vision 2030, a new countrywide strategic plan, emphasizes English mastery for business and provides new vocational avenues for women. KSA women now have instrumental L2 motivation for occupational purposes but lack models on which to base their future ideal L2 selves. While they face additional barriers to L2 acquisition due to an ineffective L2 learning environment (L2LE), and societal features that dissuade Saudis from interacting with each other in English, educational technology such as the Padlet could be used to surmount those obstacles. This case study presents an innovative, student-centered use of Padlet to teach speaking strategies (SSs) to an L2 female KSA higher education class while avoiding direct L2 dialogue and maintaining L2 motivation (n = 33). Students were provided an instructor-led lesson and offered the choice of either using the Padlet or doing a similar individual audio activity. Thirty students participated in five SS lessons, and by the third lesson, Padlet was the activity of choice, with 97%, 83% and 77%, choosing it over the audio activity for lessons three through five, respectively. Qualitative responses consistently supported that the Padlet was successful at increasing student-centered collaborative applied peer learning in this female KSA higher education classroom without requiring direct interaction in the L2, and keeping L2 motivation levels high.

Reduced complexity for sound zones with subband block adaptive filters and a loudspeaker line array.

Sound zones are used to reproduce individual audio content to multiple people in a room using a set of loudspeakers with controllable input signals. To allow the reproduction of individual audio to dynamically change, e.g., due to moving listeners, changes in the number of listeners, or changing room transfer functions, an adaptive formulation is proposed. This formulation is based on frequency domain block adaptive filters and given room transfer functions. To reduce computational complexity, the system is extended to subband processing without cross-adaptive filters. The computational savings come from recognizing that sound zones consist of part-solutions which are inherently band limited, hence, several subbands can be ignored. To validate the theoretical findings, a 27-channel loudspeaker array was constructed, and measurements were performed in anechoic and reflective environments. The results show that the subband solution performs identically to a full-rate solution but at a reduced computational complexity.

From manual to machine

Abstract This study introduces a groundbreaking automated methodology for measuring ear–voice span (EVS) in simultaneous interpreting (SI). Traditionally, assessing EVS – a critical temporal metric in SI – has been hampered by labour-intensive and time-consuming manual methods that are prone to inconsistency. To overcome these challenges, our research harnesses state-of-the-art natural language processing (NLP) technologies, including automatic speech recognition (ASR), sentence boundary detection (SBD) and cross-lingual alignment, to automate EVS measurement. We deployed a comprehensive array of NLP models and evaluated the automated pipelines on a 20-hour English-to-Portuguese SI corpus which featured 57 varied audio pairings. The findings are encouraging: the most effective model combination achieved a median EVS error of less than 0.1 seconds across the corpus. Moreover, the automated pipelines exhibited a high level of accuracy, strong correlation and substantial agreement with manual measurements when assessing median EVS for individual audio pairs. Despite these satisfactory results, certain challenges persist with some NLP models, indicating clear avenues for future research. This study not only introduces a groundbreaking approach to large-scale EVS measurement but also propels the automation of process analysis in Interpreting Studies.

Measuring the Accuracy of Automatic Speech Recognition Solutions

For d/Deaf and hard of hearing (DHH) people, captioning is an essential accessibility tool. Significant developments in artificial intelligence mean that automatic speech recognition (ASR) is now a part of many popular applications. This makes creating captions easy and broadly available—but transcription needs high levels of accuracy to be accessible. Scientific publications and industry report very low error rates, claiming that artificial intelligence has reached human parity or even outperforms manual transcription. At the same time, the DHH community reports serious issues with the accuracy and reliability of ASR. There seems to be a mismatch between technical innovations and the real-life experience for people who depend on transcription. Independent and comprehensive data is needed to capture the state of ASR. We measured the performance of 11 common ASR services with recordings of Higher Education lectures. We evaluated the influence of technical conditions like streaming, the use of vocabularies, and differences between languages. Our results show that accuracy ranges widely between vendors and for the individual audio samples. We also measured a significant lower quality for streaming ASR, which is used for live events. Our study shows that despite the recent improvements of ASR, common services lack reliability in accuracy.

Wave field synthesis using buckling dielectric elastomer transducers

This work presents a wave field synthesis (WFS) system using a novel loudspeaker concept based on dielectric elastomers. In WFS, large numbers of densely packed, individual audio channels are controlled to recreate arbitrary acoustic scenarios in the listener space, (i.e. listener zones in a room where different audio content can be radiated in different directions from the array, as seen in the supplemental material). Spatial resolution of the system increases with the increasing number of audio channels and with decreasing loudspeaker spacing. This motivates the use of buckling dielectric elastomer transducers (BDETs) as loudspeakers, which feature a simple setup, rendering them extremely thin and lightweight, and which promises ease of manufacture through the low demand on resources. In this work, a WFS system featuring 480 BDET has been developed. The prototype includes software, electronics, and the loudspeaker array. The electronical and mechanical design of the system is presented in detail. A nonlinear model based on the third-order shear deformation theory is applied to the BDET; the BDET is then experimentally assessed and compared to the model. Further, the final loudspeaker array is characterized by directivity measurements in an anechoic room to validate the reproducibility and quality of the setup. The presented technology highlights the structural advantages of smart materials over conventional transducers, which often are too large, heavy, and expensive for such array applications.

EFL Young Learners’ Perceptions About the Benefits and Challenges of Doing Individual Audio Recording Tasks in Their Oral Fluency

This study was conducted to investigate the EFL young learners’ perceptions about the benefits of individual audio recording tasks in their oral fluency and find out their challenges on how to do individual audio recording tasks. Twenty young learners coming from an English center in Vinh Long province took part in the research. Quantitative and qualitative data were collected by using a questionnaire and semi-structured interviews. The findings implicate that young learners highly perceived the benefits of doing individual audio recording tasks in improving their oral fluency, attitude and motivation. However, they encountered some challenges while doing individual audio recording tasks as regards linguistic problems and personal background. Keywords: Audio recording tasks, oral fluency, benefits and challenges of audio recording tasks DOI: 10.7176/JEP/13-30-07 Publication date: October 31 st 2022

Multimodal recognition of frustration during game-play with deep neural networks

Frustration, which is one aspect of the field of emotional recognition, is of particular interest to the video game industry as it provides information concerning each individual player’s level of engagement. The use of non-invasive strategies to estimate this emotion is, therefore, a relevant line of research with a direct application to real-world scenarios. While several proposals regarding the performance of non-invasive frustration recognition can be found in literature, they usually rely on hand-crafted features and rarely exploit the potential inherent to the combination of different sources of information. This work, therefore, presents a new approach that automatically extracts meaningful descriptors from individual audio and video sources of information using Deep Neural Networks (DNN) in order to then combine them, with the objective of detecting frustration in Game-Play scenarios. More precisely, two fusion modalities, namely decision-level and feature-level, are presented and compared with state-of-the-art methods, along with different DNN architectures optimized for each type of data. Experiments performed with a real-world audiovisual benchmarking corpus revealed that the multimodal proposals introduced herein are more suitable than those of a unimodal nature, and that their performance also surpasses that of other state-of-the–art approaches, with error rate improvements of between 40% and 90%.

COMMUNITY-BASED PARTICIPATORY RESEARCH FILMMAKING WITH FORMERLY HOMELESS OLDER ADULTS

This methodological paper discusses the process of co-creating a documentary film with seven formerly homeless older adults, highlighting some of the tensions carrying out community-based participatory research (CBPR). This paper is part of a larger study that explored ‘finding home’ through a series of individual and group audio and video-recorded interviews (including walk and drive alongs) with seven adults (aged 50+) with diverse homeless histories. In addition to the main findings, participants shared their experience of filmmaking and CBPR. Findings revealed four main tensions: 1) openness of sharing stories versus privacy and anonymity; 2) balancing participation/engagement and over-burdening; 3) negotiating interpersonal conflict and community building; and 4) ethical issues surrounding copyright and ownership of the film. Ultimately, we advocate for more CBPR film projects, as they not only provide a rich contextualized window into people’s everyday lives but serve to advance the voices of marginalized populations beyond traditional academic circles.

On the Influence of Transfer Function Noise on Sound Zone Control in a Room

Sound zones are valuable in scenarios where multiple people are present in the same room but want to listen to individual audio content without wearing headphones. The purpose of sound zone methods is to minimize the acoustic leakage between the zones by controlling multiple loudspeakers. This requires knowledge of how the loudspeakers interact with the room and radiate sound to the zones. That interaction is characterized by the transfer functions between the loudspeakers and microphones sampling the sound field in the zones. In this paper, the effect on the acoustic separation due to inherent noise in in situ transfer function measurements is investigated. The attainable separation is analyzed in the frequency range 20–300 Hz by means of the eigenfunctions of a rectangular room. The concept of observable degrees of freedom is introduced to indicate the number of active eigenfunctions, which are different within the zones at a given frequency. Likewise, controllable degrees of freedom indicate whether each source can excite the active eigenfunctions independently. It is argued that high separation can be achieved when the observable degrees of freedom are fewer than the controllable, and the target sound field can be described by the observable degrees of freedom. However, to attain this high separation it is a requirement that the details in the transfer functions associated with these degrees of freedom can be resolved in the presence of the measurement noise. For both simulated and experimental conditions the transfer functions are estimated using Bayesian inference and the uncertainty in the estimates is used to automatically regularize the sound field control. This regularization is seen to improve the performance when the measurement noise is correlated between the microphones and have little effect when the noise is uncorrelated.

Combining audio and video metrics to assess audio-visual quality

In this work, we studied the use of combination models to integrate audio and video quality estimates to predict the overall audio-visual quality. More specifically, an overall quality prediction for an audio-visual signal is obtained by combining the outputs of individual audio and video quality metrics with either a linear, a Minkowski, or a power function. A total of 7 different video quality metrics are considered, from which 3 are Full-Reference and 4 are No-Reference. Similarly, a total of 4 audio quality metrics are tested, 2 of which are Full-Reference and 2 are No-Reference. In total, we tested 18 Full-Reference audio-visual combination metrics and 24 No-Reference audio-visual combination metrics. The performance of all combination metrics are tested on two different audio-visual databases. Therefore, besides analysing the performance of a set of individual audio and video quality metrics, we analyzed the performance of the models that combine these audio and video quality metrics. This work gives an important contribution to the area of audio-visual quality assessment, since previous works either tested combination models only on subjective quality scores or used linear models to combine the outputs of a limited number of audio and video quality metrics.

EXPERIMENTAL INVESTIGATIONS ON THE SURFACE-DRIVEN CAPILLARY FLOW OF AQUEOUS MICROPARTICLE SUSPENSIONS IN THE MICROFLUIDIC LABORATORY-ON-A-CHIP SYSTEMS

In this work, total 1592 individual leakage-free polymethylmethacrylate (PMMA) microfluidic devices as laboratory-on-a-chip systems are fabricated by maskless lithography, hot embossing lithography, and direct bonding technique. Total 1094 individual Audio Video Interleave Files as experimental outputs related to the surface-driven capillary flow have been recorded and analyzed. The influence of effective viscosity, effect of surface wettability, effect of channel aspect ratio, and effect of centrifugal force on the surface-driven microfluidic flow of aqueous microparticle suspensions have been successfully and individually investigated in these laboratory-on-a-chip systems. Also, 5 micron polystyrene particles have been separated from the aqueous microparticle suspensions in the microfluidic lab-on-a-chip systems of modified design with 98% separation efficiency, and 10 micron polystyrene particles have been separated with 100% separation efficiency. About the novelty of this work, the experimental investigations have been performed on the surface-driven microfluidic flow of aqueous microparticle suspensions with the investigations on the separation time in particle-size based separation mechanism to control these suspensions in the microfluidic lab-on-a-chip systems. This research work contains a total of 10,112 individual experimental outputs obtained using total 30 individual instruments by author’s own hands-on completely during more than three years continuously. Author has performed the experimental investigations on both the fluid statics and fluid dynamics to develop an automated fluid machine.

Correlation and agreement between Language ENvironment Analysis (LENA™) and manual transcription for Dutch natural language recordings.

The Language ENvironment Analysis system (LENA™) automatically analyzes the natural sound environments of children. Among other things, it estimates the amounts of adult words (AWC), child vocalizations (CV), conversational turns (CT), and electronic media (TV) that a child is exposed to. To assess LENA's reliability, we compared it to manual transcription. Specifically, we calculated the correlation and agreement between the LENA estimates and manual counts for 48 five-min audio samples. These samples were selected from eight day-long recordings of six Dutch-speaking children (ages 2-5). The correlations were strong for AWC, r = . 87, and CV, r = . 77, and comparatively low for CT, r = . 52, and TV, r = . 50. However, the agreement analysis revealed a constant bias in AWC counts, and proportional biases for CV and CT (i.e., the bias varied with the values for CV and CT). Agreement for detecting electronic media was poor. Moreover, the limits of agreement were wide for all four metrics. That is, the differences between LENA and the manual transcriptions for individual audio samples varied widely around the mean difference. This variation could indicate that LENA was affected by differences between the samples that did not equally affect the human transcribers. The disagreements and biases cast doubt on the comparability of LENA measurements across families and time, which is crucial for using LENA in research. Our sample is too small to conclude within which limits LENA's measurements are comparable, but it seems advisable to be cautious of factors that could systematically bias LENA's performance and thereby create confounds.

Encoding Multiple Audio Objects Using Intra-Object Sparsity

Preserving audio scenes in the form of audio objects has become common in recent years. Object-based audio techniques provide more flexibility for personalized rendering as well as a more accurate audio object trajectory. For encoding and transmitting multiple audio objects in a lossy manner, a new compression framework for multiple simultaneously occurring audio objects is presented in this work. The proposed encoding approach is based on the intra-object sparsity (approximate $k$ -sparsity). After establishing a quantitative measure of approximate $k$ -sparsity, statistical analysis is employed to validate the proposed intra-object sparsity of audio objects. By exploring this intra-object sparsity, multiple simultaneously occurring audio objects are compressed into a mono downmix signal with side information. This downmix signal can be further compressed by legacy audio codecs. Meanwhile, the side information is transmitted in a lossless manner. The objective and subjective evaluations revealed that the proposed compression framework achieved better perceptual quality compared to an existing technique where up to eight audio objects are considered. The subjective evaluations also confirmed that the proposed approach is able to achieve scalable transmission according to the bandwidth while preserving the perceptual quality of both the individual audio objects and the spatial audio scenes.

Musical Source Clustering and Identification in Polyphonic Audio

For music transcription or musical source separation, apart from knowing the multi-F0 contours, it is also important to know which F0 has been played by which instrument. This paper focuses on this aspect, i.e. given the polyphonic audio along with its multiple F0 contours, the proposed system clusters them so as to decide ‘which instrument played when.’ For the task of identifying the instrument or singers in the polyphonic audio, there are many supervised methods available. But many times individual source audio is not available for training. To address this problem, this paper proposes novel schemes using semi-supervised as well as unsupervised approach to source clustering. The proposed theoretical framework is based on auditory perception theory and is implemented using various tools like probabilistic latent component analysis and graph clustering, while taking into account various perceptual cues for characterizing a source. Experiments have been carried out over a wide variety of datasets - ranging from vocal to instrumental as well as from synthetic to real world music. The proposed scheme significantly outperforms a state of the art unsupervised scheme, which does not make use of the given F0 contours. The proposed semi-supervised approach also performs better than another semi-supervised scheme, which makes use of the given F0 information, in terms of computations as well as accuracy.

Local Control of Audio Environment: A Review of Methods and Applications

The concept of a local audio environment is to have sound playback locally restricted such that, ideally, adjacent regions of an indoor or outdoor space could exhibit their own individual audio content without interfering with each other. This would enable people to listen to their content of choice without disturbing others next to them, yet, without any headphones to block conversation. In practice, perfect sound containment in free air cannot be attained, but a local audio environment can still be satisfactorily approximated using directional speakers. Directional speakers may be based on regular audible frequencies or they may employ modulated ultrasound. Planar, parabolic, and array form factors are commonly used. The directivity of a speaker improves as its surface area and sound frequency increases, making these the main design factors for directional audio systems. Even directional speakers radiate some sound outside the main beam, and sound can also reflect from objects. Therefore, directional speaker systems perform best when there is enough ambient noise to mask the leaking sound. Possible areas of application for local audio include information and advertisement audio feed in commercial facilities, guiding and narration in museums and exhibitions, office space personalization, control room messaging, rehabilitation environments, and entertainment audio systems.

Adaptive Quantization Index Modulation Audio Watermarking based on Fuzzy Inference System

Many of the adaptive watermarking schemes reported in the literature consider only local audio signal properties. Many schemes require complex computation along with manual parameter settings. In this paper, we propose a novel, fuzzy, adaptive audio watermarking algorithm based on both global and local audio signal properties. The algorithm performs well for dynamic range of audio signals without requiring manual initial parameter selection. Here, mean value of energy (MVE) and variance of spectral flux (VSF) of a given audio signal constitutes global components, while the energy of each audio frame acts as local component. The Quantization Index Modulation (QIM) step size Δ is made adaptive to both the global and local features. The global component automates the initial selection of Δ using the fuzzy inference system while the local component controls the variation in it based on the energy of individual audio frame. Hence Δ adaptively controls the strength of watermark to meet both the robustness and inaudibility requirements, making the system independent of audio nature. Experimental results reveal that our adaptive scheme outperforms other fixed step sized QIM schemes and adaptive schemes and is highly robust against general attacks.

Quem é o especialista? lugares ocupados por profissionais e pacientes no tratamento dos transtornos alimentares

A epistemologia construcionista social reposiciona profissional e paciente como co-construtores do cuidado em saúde. Assumindo essa perspectiva, buscou-se, com este estudo, conhecer as práticas discursivas de pessoas diagnosticadas com Anorexia Nervosa e Bulimia Nervosa sobre os lugares ocupados por pacientes e profissionais na construção do tratamento. Foram realizadas entrevistas individuais audiogravadas com pacientes de um serviço de assistência em transtornos alimentares. O discurso construcionista social orientou essa pesquisa. Para análise do corpus foram utilizadas as propostas das delimitações temático-sequenciais, as práticas discursivas e produção de sentidos, e a teoria do posicionamento. A construção dos resultados sugere que os padrões de coordenação das ações entre profissionais e pacientes podem sedimentar lugares e posicionamentos enrijecidos e disponibilizar pouco espaço para negociações. As propostas do diálogo aberto e da parceria colaborativa foram oferecidas como possibilidades para construção de novos relacionamentos profissional-paciente, entendendo a conquista do bem-estar como produto da ação conjunta.

Ідентифікація апаратури аудіозапису за статистичними характеристиками аудіофайлів

Наведено результати досліджень з розробки методології та математичної моделі виявлення та аналізу самоподібних структур у паузах аудіофайлів. Модель дозволяє виділяти статистичні характеристики паразитних індивідуальних параметрів апаратури, то фіксуються в аудіозапису. Розроблено модель ідентифікації апаратури аудіозапису за статистичними характеристиками цих параметрів у паузах аудіофайлів. Іл.: 6. Бібліогр.: 20 найм.

Collective patient behaviours derailing ART roll-out in KwaZulu-Natal: perspectives of health care providers.

BackgroundAntiretroviral therapy (ART) roll-out is fraught with challenges, many with serious repercussions. We explored and described patient behaviour-related challenges from the perspective of health care providers from non-governmental organisations involved in ART programmes in KwaZulu-Natal, South Africa.MethodsA descriptive case study design using qualitative approach was applied during this study. Data was collected from nine key informants from the three biggest NGOs involved in ART roll-out using in-depth semi-structured interviews. Transcribing and coding for emergent themes was done by two independent reviewers. Ethical approval for the study was granted by the UNISA research ethics committee of The Faculty of Health Sciences. Written consent was obtained from directors of the three NGOs involved and individual audio taped informed consent was obtained from all study participants prior to data collection.ResultsFindings revealed six broad areas of patient behaviour challenges. These were patient behaviour related to socio-economic situation of patient (skipping of medication due to lack of food, or due to lack of transport fees), belief systems (traditional and religious), stigma (non- disclosure), sexual practices (non-acceptability of condoms, teenage pregnancies), escapism (drug and alcohol abuse) and opportunism (skipping medication in order to access disability grant, teenage pregnancies in order to access child grant).ConclusionNew programmes need to address patient behaviour as a complex phenomenon requiring a multi-pronged approach that also addresses social norms and institutions. In the face of continued ART scale up, this is further evidence for the need for multi-sectoral collaboration to ensure successful and sustainable ART roll-out.

Using audio for Feedback on assessments: tutor and student experiences

Recently we have been providing individual audio feedback to 1st and 2nd year undergraduate Chemistry students on a variety of assessments (posters, laboratory reports, laboratory diaries) with the aim of providing richer, more detailed and more comprehensible individual feedback than is possible within the same timeframe using written feedback. In this communication, various aspects of the use of audio for feedback are discussed including practical and technical aspects of the recording of audio files whilst viewing and assessing student work, the transmission of these files to individual students, our experiences as tutors of providing audio feedback and the experiences and views of students on audio feedback.