Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Pinto, Valencia; Kulkarni, Manasa; Govind, Sangeetha Title A name given to the resource Inclusive Interfaces: Enhancing Voice Assistants for Diverse Speech Abilities Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived 2025 17th IEEE International Conference on Computational Intelligence and Communication Networks, CICN 2025;pp.2028-2033 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/CICN67655.2025.11368248" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/CICN67655.2025.11368248</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105034683407?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105034683407?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Pinto V., CHRIST University, Department of Computer Science, Karnataka, Bangalore, India; Kulkarni M., CHRIST University, Department of Computer Science, Karnataka, Bangalore, India; Govind S., CHRIST University, Department of Computer Science, Karnataka, Bangalore, India Description An account of the resource The main goal of this research is to highlight the considerable challenges that people suffering from dysarthria have to face while using Automatic Speech Recognition (ASR) technologies and virtual assistants. Current voice-controlled technologies struggle to understand disordered speech, which reveals a significant gap in research about how to adapt these technologies to speech changes caused by health conditions. We propose to explore non-verbal voice signals as a quieter potential solution. The work uses a systematic literature review and comparative analysis across various scenarios to point out the weaknesses of ASR in terms of accuracy and security. The research proves that non-verbal input always provides greater performance in accuracy, reliability, and convenience. This analysis lays the groundwork for designing more accessible technologies. Designed for researchers and developers, this research is an avenue for future work where future efforts address the empirical evaluation of a specialized non-verbal system to support user autonomy. 2025 IEEE. Subject The topic of the resource Accessibility; Automatic Speech Recognition(ASR); Dysarthria; Non-Verbal Interaction; Voice Assistants Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Relation A related resource ISBN: 979-833158733-8; Language A language of the resource English Type The nature or genre of the resource Conference paper Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Format The file format, physical medium, or dimensions of the resource online