How Speech Technologies Can Help People with Disabilities

Delić, Vlado; Secujski, Milan; Sedlar, Nataša Vujnović; Miskovic, Dragisa; Mak, Robert; Bojanić, Milana

doi:10.1007/978-3-319-11581-8_30

Cited by 6 publications

(6 citation statements)

References 11 publications

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“…In order to assess the impact of lock-down, risk and protective factors for psychological distress, including changes in routine activities and daily behaviors, were examined. Based on previous literature related to the COVID-19 pandemic [ 6 , 14 , 19 , 20 ], lifestyle and stress management items (e.g., 29-What were your daily life habits during lock-down?) and 6 stressors terms (e.g., 35-Have you experienced sleep disturbances during lock-down?…”

Section: Methodsmentioning

confidence: 99%

The Impact of COVID-19 on Individuals with Hearing and Visual Disabilities during the First Pandemic Wave in Italy

Bubbico¹,

Bellizzi²,

Ferlito

et al. 2021

IJERPH

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Background. The COVID-19 pandemic has imposed radical behavioral and social changes in the general population, significantly impacting the lives of individuals affected by disabilities. The aim of this study was to investigate the impact of COVID-19 on noninstitutionalized subjects with sensorineural disabilities during the first COVID-19 wave in Italy. Methods. A 39-item online national survey was disseminated from 1 April 2020 to 31 June 2020 via social media throughout Italy to communities of individuals with proven severe sensorineural disabilities, affiliated to five national patient associations. The survey collected extensive information on the socio-demographic profile, health, everyday activities, and lifestyle of individuals with hearing and visual disabilities. Results. One hundred and sixty-three respondents with hearing (66.9%) and visual (33.1%) disabilities returned a usable questionnaire. The mean age of interviewees was 38.4 ± 20.2 years and 56.3% of them were females. Despite the vast majority of respondents (77.9%) perceiving their health status as unchanged (68.8% of interviewees with hearing deficits vs. 96.3% of those with visual impairments), about half the interviewees reported sleep disorders during lock-down, more likely those with visual deficits. Remote services were seemingly more effective for business than school activities were. Furthermore, although just 18.8% of respondents rated remote rehabilitation care unsatisfactory, only 12.8% of interviewees felt supported by health and social services. The vast majority of respondents were concerned about the future and the risk of SARS-CoV-2 contagion, particularly individuals with hearing impairments. Among the various risk mitigation measures, facemasks caused the greatest discomfort due to communication barriers, particularly among interviewees affected by hearing disabilities (92.2% vs. 45.7%). The most common request (46.5%) of respondents to reduce the inconveniences of country lock-down was improving the access to and delivery of health and social services (19.3%), followed by the use of transparent masks (17.5%). Conclusions. Although health protection measures such as face masks and social distancing play a key role in preventing and controlling the spread of SARS-CoV-2, the unmet needs of disabled individuals should be carefully considered, especially those affected by sensory disabilities. Tailored access to health and social services for individuals affected by sensorineural disabilities should be implemented. Additional actions should include the use of face shields as a valid alternative to reduce communication barriers linked to hearing-impairment, as well as the improvement of remote services, especially distance learning at school.

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Section: Methodsmentioning

confidence: 99%

The Impact of COVID-19 on Individuals with Hearing and Visual Disabilities during the First Pandemic Wave in Italy

Bubbico¹,

Bellizzi²,

Ferlito

et al. 2021

IJERPH

View full text Add to dashboard Cite

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“…The time-domain waveform of a speech signal, representing the amplitude variations over time, contains essential auditory information. However, to extract meaningful information from the waveform, it is necessary to condense the data of each segment into a limited number of parameters or characteristics while retaining the signal's discriminatory power (Delić et al, 2013;Delić et al, 2014;Ajibola Alim and Rashid, 2018;Alenizi and Al-Karawi, 2023b). As the number of input voice samples increases, the accuracy of the speech recognition systems tends to decrease (Gaikwad, 2010;Virkar et al, 2020).…”

Section: Feature Extractionmentioning

confidence: 99%

“…Speech technologies have the potential to greatly assist individuals with disabilities, contributing to their equality and inclusion in society and everyday life (Delić et al, 2013). Speech, being a natural and intuitive form of human communication, holds great potential as an ideal medium for human-computer interaction.…”

Section: Introductionmentioning

confidence: 99%

“…Despite the complexity of the task, advancements in speech technology continue to pave the way for more seamless and effective human-computer interaction Journal of Disability Research 2024 (Busatlic et al, 2017). As research progresses, speech recognition systems are expected to become more accurate, versatile, and accessible, enabling individuals with disabilities to benefit from natural and intuitive technological interactions (Delić et al, 2013;Al-Karawi, 2021). Over the years, numerous approaches have been proposed for ASR (Abushariah et al, 2010;Ibarra and Guerrero, 2010;Bedoya and Muñoz, 2012).…”

Section: Introductionmentioning

confidence: 99%

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Using Voice Technologies to Support Disabled People

Semary,

Al-Karawi,

Abdelwahab

2024

Journal of Disability Research

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In recent years, significant strides have been made in speech and speaker recognition systems, owing to the rapid evolution of data processing capabilities. Utilizing a speech recognition system facilitates straightforward and efficient interaction, especially for individuals with disabilities. This article introduces an automatic speech recognition (ASR) system designed for seamless adaptation across diverse platforms. The model is meticulously described, emphasizing clarity and detail to ensure reproducibility for researchers advancing in this field. The model’s architecture encompasses four stages: data acquisition, preprocessing, feature extraction, and pattern recognition. Comprehensive insights into the system’s functionality are provided in the Experiments and Results section. In this study, an ASR system is introduced as a valuable addition to the advancement of educational platforms, enhancing accessibility for individuals with visual disabilities. While the achieved recognition accuracy levels are promising, they may not match those of certain commercial systems. Nevertheless, the proposed model offers a cost-effective solution with low computational requirements. It seamlessly integrates with various platforms, facilitates straightforward modifications for developers, and can be tailored to the specific needs of individual users. Additionally, the system allows for the effortless inclusion of new words in its database through a single recording process.

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“…Therefore, voice intelligence can be a crucial and leveling intermediary for populations in developing countries to access the Internet, information, and online services. In short, voice intelligence makes a practical contribution to inclusiveness and helps remove barriers to digital accessibility worldwide (Delić et al, 2014 ).…”

Section: Introductionmentioning

confidence: 99%

The effects of anthropomorphism and multimodal biometric authentication on the user experience of voice intelligence

Kloet

Yang

2022

Front. Artif. Intell.

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Voice intelligence is a revolutionary “zero-touch” type of human-machine interaction based on spoken language. There has been a recent increase in the number and variations of voice assistants and applications that help users to acquire information. The increased popularity of voice intelligence, however, has not been reflected in the customer value chain. Current research on the socio-technological aspects of human-technology interaction has emphasized the importance of anthropomorphism and user identification in the adoption of the technology. Prior research has also pointed out that user perception toward the technology is key to its adoption. Therefore, this research examines how anthropomorphism and multimodal biometric authentication influence the adoption of voice intelligence through user perception in the customer value chain. In this study we conducted a between-subjects online experiment. We designed a 2 × 2 factorial experiment by manipulating anthropomorphism and multimodal biometric authentication into four conditions, namely with and without a combination of these two factors. Subjects were recruited from Amazon MTurk platform and randomly assigned to one of the four conditions. The results drawn from the empirical study showed a significant direct positive effect of anthropomorphism and multimodal biometric authentication on user adoption of voice intelligence in the customer value chain. Moreover, the effect of anthropomorphism is partially mediated by users' perceived ease of use, perceived usefulness, and perceived security risk. This research contributes to the existing literature on human-computer interaction and voice intelligence by empirically testing the simultaneous impact of anthropomorphism and biometric authentication on users' experience of the technology. The study also provides practitioners who wish to adopt voice intelligence in the commercial environment with insights into the user interface design.

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How Speech Technologies Can Help People with Disabilities

Cited by 6 publications

References 11 publications

The Impact of COVID-19 on Individuals with Hearing and Visual Disabilities during the First Pandemic Wave in Italy

The Impact of COVID-19 on Individuals with Hearing and Visual Disabilities during the First Pandemic Wave in Italy

Using Voice Technologies to Support Disabled People

The effects of anthropomorphism and multimodal biometric authentication on the user experience of voice intelligence

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