A Survey: Speech Recognition Approaches and Techniques

Singh, Atma Prakash; Nath, R.; Kumar, Santosh

doi:10.1109/upcon.2018.8596954

Cited by 25 publications

(6 citation statements)

References 6 publications

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“…If a user who has not trained the model attempts to use it, there is a high likelihood of commands being misclassified. On the contrary, speaker-independent recognition aims to identify speakers without prior training, making it a versatile and general solution [41].…”

Section: Voice Recognitionmentioning

confidence: 99%

Integration of Deep Learning and Collaborative Robot for Assembly Tasks

Mendez,

Ochoa,

Olivera-Guzman

et al. 2024

Applied Sciences

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Human–robot collaboration has gained attention in the field of manufacturing and assembly tasks, necessitating the development of adaptable and user-friendly forms of interaction. To address this demand, collaborative robots (cobots) have emerged as a viable solution. Deep Learning has played a pivotal role in enhancing robot capabilities and facilitating their perception and understanding of the environment. This study proposes the integration of cobots and Deep Learning to assist users in assembly tasks such as part handover and storage. The proposed system includes an object classification system to categorize and store assembly elements, a voice recognition system to classify user commands, and a hand-tracking system for close interaction. Tests were conducted for each isolated system and for the complete application as used by different individuals, yielding an average accuracy of 91.25%. The integration of Deep Learning into cobot applications has significant potential for transforming industries, including manufacturing, healthcare, and assistive technologies. This work serves as a proof of concept for the use of several neural networks and a cobot in a collaborative task, demonstrating communication between the systems and proposing an evaluation approach for individual and integrated systems.

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Section: Voice Recognitionmentioning

confidence: 99%

Integration of Deep Learning and Collaborative Robot for Assembly Tasks

Mendez,

Ochoa,

Olivera-Guzman

et al. 2024

Applied Sciences

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“…Humans interpret information and express ideas through various communication techniques. An essential tool of communication and information exchange is the human voice [ 64 ] and therefore technological advancements in the field of speech recognition have become prevalent through the application of AI [ 65 ]. Microsoft and Google have also provided cloud speech-to-text capabilities via deep learning models [ 66 ], which involve large neural network models that are able to make decisions that are data-driven [ 67 ].…”

Section: Integrating Artificial Intelligence (Ai) and Creativitymentioning

confidence: 99%

“…The integration of AI with VR environments, also denoted by the term Intelligent Virtual Environments [ 74 ], presents other benefits for such applications, which include the possibility of having a design space which embodies interaction partners having varied forms and appearances; AI systems are easily adaptable to specific or elusive user groups and AI offers a high degree of versatility to simulate various tasks and domains [ 64 ]. AI also enables multimodal interaction that is based on multiple forms of communication, both verbal and non-verbal.…”

Section: Integrating Artificial Intelligence (Ai) and Creativitymentioning

confidence: 99%

An Extended AI-Experience: Industry 5.0 in Creative Product Innovation

Grech

Mehnen

Wodehouse

2023

Sensors

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Creativity plays a significant role in competitive product ideation. With the increasing emergence of Virtual Reality (VR) and Artificial Intelligence (AI) technologies, the link between such technologies and product ideation is explored in this research to assist and augment creative scenarios in the engineering field. A bibliographic analysis is performed to review relevant fields and their relationships. This is followed by a review of current challenges in group ideation and state-of-the-art technologies with the aim of addressing them in this study. This knowledge is applied to the transformation of current ideation scenarios into a virtual environment using AI. The aim is to augment designers’ creative experiences, a core value of Industry 5.0 that focuses on human-centricity, social and ecological benefits. For the first time, this research reclaims brainstorming as a challenging and inspiring activity where participants are fully engaged through a combination of AI and VR technologies. This activity is enhanced through three key areas: facilitation, stimulation, and immersion. These areas are integrated through intelligent team moderation, enhanced communication techniques, and access to multi-sensory stimuli during the collaborative creative process, therefore providing a platform for future research into Industry 5.0 and smart product development.

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“…Speech and voice recognition will never be possible without artificial intelligence (Singh et al, 2018 ). All modern deep learning techniques, including BERT (Brunner et al, 2020 ) contribute to better speech, voice and speech recognition (Amberkar et al, 2018 ).…”

Section: Cutting Edge Assistive Technologiesmentioning

confidence: 99%

“…Non-invasive brain-computer interfaces emerge in this area, leading to much better performance compared to traditional systems that process auditory and visual information (Brumberg et al, 2018 ). United with deep learning methods and architectures, they “boost classification performance” of algorithms for computer vision and natural language processing (Singh et al, 2018 ).…”

Section: Cutting Edge Assistive Technologiesmentioning

confidence: 99%

Cutting-edge communication and learning assistive technologies for disabled children: An artificial intelligence perspective

Zdravkova

Krasniqi²,

Dalipi³

et al. 2022

Front. Artif. Intell.

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In this study we provide an in-depth review and analysis of the impact of artificial intelligence (AI) components and solutions that support the development of cutting-edge assistive technologies for children with special needs. Various disabilities are addressed and the most recent assistive technologies that enhance communication and education of disabled children, as well as the AI technologies that have enabled their development, are presented. The paper summarizes with an AI perspective on future assistive technologies and ethical concerns arising from the use of such cutting-edge communication and learning technologies for children with disabilities.

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A Survey: Speech Recognition Approaches and Techniques

Cited by 25 publications

References 6 publications

Integration of Deep Learning and Collaborative Robot for Assembly Tasks

Integration of Deep Learning and Collaborative Robot for Assembly Tasks

An Extended AI-Experience: Industry 5.0 in Creative Product Innovation

Cutting-edge communication and learning assistive technologies for disabled children: An artificial intelligence perspective

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