1,720,959 research outputs found
Embedded Systems and TensorFlow Frameworks as Assistive Technology Solutions
No full textIn the field of deep learning, this paper presents the design of a wearable computer vision system for visually impaired users. The Assistive Technology solution exploits a powerful single board computer and smart glasses with a camera in order to allow its user to explore the objects within his surrounding environment, while it employs Google TensorFlow machine learning framework in order to real time classify the acquired stills. Therefore the proposed aid can increase the awareness of the explored environment and it interacts with its user by means of audio messages
Using tensorflow to design assistive technologies for people with visual impairments
No full textTensorFlow is an open source deep learning framework developed at Google that enables developers to conceive a wide variety of applications based on artificial intelligence principles. In this paper, we employ such software resources towards the development of a computer vision system for people with visual impairments. We propose a wearable assistive technology solution consisting of a single board computer connected to a camera mounted on the user's glasses. A TensorFlow based software runs on the board in order to real time classify the images captured by the camera, while a text to speech process vocalizes the still's content for the blind person. In this way, the system provides an audio description of the objects in the user's surrounding environment and it may help these people to better detect the things around them
Co-designing the integration of voice-based conversational AI and web augmentation to amplify web inclusivity
Full text linkThe Web has become an essential resource but is not yet accessible to everyone. Assistive technologies and innovative, intelligent frameworks, for example, those using conversational AI, help overcome some exclusions. However, some users still experience barriers. This paper shows how a human-centered approach can shed light on technology limitations and gaps. It reports on a three-step process (focus group, co-design, and preliminary validation) that we adopted to investigate how people with speech impairments, e.g., dysarthria, browse the Web and how barriers can be reduced. The methodology helped us identify challenges and create new solutions, i.e., patterns for Web browsing, by combining voice-based conversational AI, customized for impaired speech, with techniques for the visual augmentation of web pages. While current trends in AI research focus on more and more powerful large models, participants remarked how current conversational systems do not meet their needs, and how it is important to consider each one's specificity for a technology to be called inclusive
Towards a deep learning based ASR system for users with dysarthria
No full textIn this paper, we investigate the benefits of deep learning approaches for the development of personalized assistive technology solutions for users with dysarthria, a speech disorder that leads to low intelligibility of users’ speaking. It prevents these people from using automatic speech recognition (ASR) solutions on computers and mobile devices. In order to address these issue, our effort is to leverage convolutional neural networks toward a speaker dependent ASR software solution intended for users with dysarthria, which can be trained according to particular user’s needs and preferences
Machine learning in assistive technology: A solution for people with dysarthria
No full textNowadays, dysarthric speech processing represents a challenge in assistive technology contexts. In this paper, we investigate the use of machine learning in conjunction with convolutional neural networks to implement a speaker dependent solution that is capable to detect just a few number of predefined keywords. The proposed system has been trained with utterances from Italian users with severe and mild dysarthria and it is configurable according to specific users' preferences
Smart Technologies Empowering Assistive Systems for People with Disabilities
No full textThe thesis investigates the synergy among recent information and communication technologies toward the development of personalized assistive technology solutions for people with disabilities. Three separate case studies have been analysed within the framework of Artificial Intelligence (AI), machine learning and Internet of Things (IoT). The presented applications exploit open source pieces of hardware and software, low cost components with the aim of addressing open challenges for the current assistive technology, including: i) Isolated word recognition system for people with speech disorders, particularly in presence of dysarthria, with the aim of supporting the natural speech interaction with computers and appliances in a personalized smart home context; ii) Computer vision system for users who are blind or visually impaired, aimed at supporting the awareness of the user's surrounding environment, considering smart city scenario; iii) Human computer interfaces based on smart sensors and IoT technologies, especially designed for people with severe motor disabilities
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
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