A blind legend: sonoridade inclusiva no processo de audiogame

A partir das noções de Game Sound e Topologia Sonora analisamos a sonorização do accessible game francês A Blind Legend, que se trata de um audiogame mobile do gênero adventure. Discutindo sobre os conceitos de áudio interativo reativo e áudio interativo adaptativo observaremos como cada uma das três técnicas de sonorização inclusiva aplicadas neste tipo de jogo – Audio Quake, Serialization e Audio Icons/Audio Cues – se comportam dentro da narrativa consumida através do áudio binaural. A proposta é compreender como se desenvolve a sonoridade em um jogo eletrônico 100% sonoro a partir da ótica da imersão e da inclusão. Faz-se antes uma breve revisão histórica sobre o papel do som nos jogos eletrônicos.A bling legend: inclusive sonority in the processo f na audiogameAbstractFrom the notions of Game Sound and Sound Topology, we analyzed the sound of the French accessible game A Blind Legend which is a mobile audiogame of the adventure genre. Discussing the concepts of reactive interactive audio and adaptative interactive audio we will observe how each of the three inclusive sound techniques applied in this type of game – Audio Quake, Serialization and Audio Icons/Audio Cues – behave within of the narrative consumed through binaural audio. The proposal is to comprehend how the sonority is developed in a 100% sound electronic game from of the optical of the immersion and inclusion. Rather, a brief historical review of the role of the sound in electronic games is made.Keywords: Audiogame; game audio; a blind legend; inclusive audio.

Impact of Shared Control Modalities on Performance and Usability of Semi-autonomous Prostheses

Semi-autonomous (SA) control of upper-limb prostheses can improve the performance and decrease the cognitive burden of a user. In this approach, a prosthesis is equipped with additional sensors (e.g., computer vision) that provide contextual information and enable the system to accomplish some tasks automatically. Autonomous control is fused with a volitional input of a user to compute the commands that are sent to the prosthesis. Although several promising prototypes demonstrating the potential of this approach have been presented, methods to integrate the two control streams (i.e., autonomous and volitional) have not been systematically investigated. In the present study, we implemented three shared control modalities (i.e., sequential, simultaneous, and continuous) and compared their performance, as well as the cognitive and physical burdens imposed on the user. In the sequential approach, the volitional input disabled the autonomous control. In the simultaneous approach, the volitional input to a specific degree of freedom (DoF) activated autonomous control of other DoFs, whereas in the continuous approach, autonomous control was always active except for the DoFs controlled by the user. The experiment was conducted in ten able-bodied subjects, and these subjects used an SA prosthesis to perform reach-and-grasp tasks while reacting to audio cues (dual tasking). The results demonstrated that, compared to the manual baseline (volitional control only), all three SA modalities accomplished the task in a shorter time and resulted in less volitional control input. The simultaneous SA modality performed worse than the sequential and continuous SA approaches. When systematic errors were introduced in the autonomous controller to generate a mismatch between the goals of the user and controller, the performance of SA modalities substantially decreased, even below the manual baseline. The sequential SA scheme was the least impacted one in terms of errors. The present study demonstrates that a specific approach for integrating volitional and autonomous control is indeed an important factor that significantly affects the performance and physical and cognitive load, and therefore these should be considered when designing SA prostheses.

Nonverbal Auditory Cues Allow Relationship Quality to be Inferred During Conversations

The claim that nonverbal cues provide more information than the linguistic content of a conversational exchange (the Mehrabian Conjecture) has been widely cited and equally widely disputed, mainly on methodological grounds. Most studies that have tested the Conjecture have used individual words or short phrases spoken by actors imitating emotions. While cue recognition is certainly important, speech evolved to manage interactions and relationships rather than simple information exchange. In a cross-cultural design, we tested participants’ ability to identify the quality of the interaction (rapport) in naturalistic third party conversations in their own and a less familiar language, using full auditory content versus audio clips whose verbal content has been digitally altered to differing extents. We found that, using nonverbal content alone, people are 75–90% as accurate as they are with full audio cues in identifying positive vs negative relationships, and 45–53% as accurate in identifying eight different relationship types. The results broadly support Mehrabian’s claim that a significant amount of information about others’ social relationships is conveyed in the nonverbal component of speech.

Dancing with the sound in edge computing environments

Conventional motion predictions have achieved promising performance. However, the length of the predicted motion sequences of most literatures are short, and the rhythm of the generated pose sequence has rarely been explored. To pursue high quality, rhythmic, and long-term pose sequence prediction, this paper explores a novel dancing with the sound task, which is appealing and challenging in computer vision field. To tackle this problem, a novel model is proposed, which takes the sound as an indicator input and outputs the dancing pose sequence. Specifically, our model is based on the variational autoencoder (VAE) framework, which encodes the continuity and rhythm of the sound information into the hidden space to generate a coherent, diverse, rhythmic and long-term pose video. Extensive experiments validated the effectiveness of audio cues in the generation of dancing pose sequences. Concurrently, a novel dataset of audiovisual multimodal sequence generation has been released to promote the development of this field.

Depression Scale Recognition over Fusion of Visual and Vocal Expression using Artificial Intellectual Method

Now a day’s supported visual and audio cues for automatic depression assessment may be a fast emerging research subject. This comprehensive evaluation of existing methodologies focuses on machine learning (ML) algorithm and image processing (IP) algorithm, as documented in over sixty articles over the last ten years. There is a visual indicator of depression, several data collection procedures are used, and finally examined the previous year or existing datasets. In this article describes techniques and algorithms as well as methods for dimensionality reduction, visual feature extraction, regression approaches, and classification decision procedures, and also various fusion tactics. A significant meta-analysis of published data is given, based on performance indicators that are robust to chance, to identify general trends and important pressing concerns for further research using visual and verbal cues alone or in combination with signals for automated depression evaluation The suggested work also used deep learning and natural language processing to estimate depression levels based on current video data.

Perspective: Does Realism Improve Presence in VR? Suggesting a Model and Metric for VR Experience Evaluation

The concepts of “immersion” and “presence” have been considered as staple metrics for evaluating the quality of virtual reality experiences for more than five decades, even as the concepts themselves have evolved in terms of both technical and psychological aspects. To enhance the user’s experience, studies have investigated the impact of different visual, auditory, and haptic stimuli in various contexts to mainly explore the concepts of “plausibility illusion” and “place illusion”. Previous research has sometimes shown a positive correlation between increased realism and an increase in presence, but not always, and thus, very little of the work around the topic of presence reports an unequivocal correlation. Indeed, one might classify the overall findings within the field around presence as “messy”. Better (or more) visual, auditory, or haptic cues, or increased agency, may lead to increased realism, but not necessarily increased presence, and may well depend on the application context. Rich visual and audio cues in concert contribute significantly to both realism and presence, but the addition of tactile cues, gesture input support, or a combination of these might improve realism, but not necessarily presence. In this paper, we review previous research and suggest a possible theory to better define the relationship between increases in sensory-based realism and presence, and thus help VR researchers create more effective experiences.

Expanding a Large Inclusive Study of Human Listening Rates

As conversational agents and digital assistants become increasingly pervasive, understanding their synthetic speech becomes increasingly important. Simultaneously, speech synthesis is becoming more sophisticated and manipulable, providing the opportunity to optimize speech rate to save users time. However, little is known about people’s abilities to understand fast speech. In this work, we provide an extension of the first large-scale study on human listening rates, enlarging the prior study run with 453 participants to 1,409 participants and adding new analyses on this larger group. Run on LabintheWild, it used volunteer participants, was screen reader accessible, and measured listening rate by accuracy at answering questions spoken by a screen reader at various rates. Our results show that people who are visually impaired, who often rely on audio cues and access text aurally, generally have higher listening rates than sighted people. The findings also suggest a need to expand the range of rates available on personal devices. These results demonstrate the potential for users to learn to listen to faster rates, expanding the possibilities for human-conversational agent interaction.

A Modular Approach for a Patient Unit for Extracorporeal Membrane Oxygenation Simulator

Despite many advancements in extracorporeal membrane oxygenation (ECMO), the procedure is still correlated with a high risk of patient complications. Simulation-based training provides the opportunity for ECMO staff to practice on real-life scenarios without exposing ECMO patients to medical errors while practicing. At Hamad Medical Corporation (HMC) in Qatar, there is a critical need of expert ECMO staff. Thus, a modular ECMO simulator is being developed to enhance the training process in a cost-effective manner. This ECMO simulator gives the instructor the ability to control the simulation modules and run common simulation scenarios through a tablet application. The core modules of the simulation system are placed in the patient unit. The unit is designed modularly such that more modules can be added throughout the simulation sessions to increase the realism of the simulation sessions. The new approach is to enclose the patient unit in a trolley, which is custom-designed and made to include all the components in a modular fashion. Each module is enclosed in a separate box and then mounted to the main blood simulation loop box using screws, quick connect/disconnect liquid fittings, and electrical plugs. This method allows fast upgrade and maintenance for each module separately as well as upgrading modules easily without modifying the trolley’s design. The prototype patient unit has been developed for portability, maintenance, and extensibility. After implementation and testing, the prototype has proven to successfully simulate the main visual and audio cues of the real emergency scenarios, while keeping costs to a minimum.