Purpose Artificial intelligence(AI)is developing across the world in every domain,such as finance,manufacturing,entertainment,agriculture,retail,healthcare,and law.Its use in the education sector has exponentially inc...Purpose Artificial intelligence(AI)is developing across the world in every domain,such as finance,manufacturing,entertainment,agriculture,retail,healthcare,and law.Its use in the education sector has exponentially increased.The present global survey explored the utilization of AI among academicians in audiology and speech-language therapy(ASLT)and their willingness to use AI tools in their academic work.Method This study used a cross-sectional survey design.One hundred and six ASLT academicians participated in the survey(February 2024 to April 2024).The questionnaire contains 18 items,which included a five-point rating scale,yes-no,and open-ended questions.Descriptive statistics were used for analysis.Results Most of the participants were from Asia and North America,followed by Africa.Nearly sixty-eight percent of the academicians used AI tools in their practice.The major concerns reported by the participants were the authenticity of the data,security,the addition of irrelevant information,and incorrect citations.The participants also mentioned that the frequent use of AI tools can reduce a person’s ability to devise novel ideas.AI tools such as ChatGPT,Canva,Grammarly AI,Mentimeter,QuillBot,ResearchRabbit,and Scribd were reported by participants.Conclusions The present study highlights the use of AI tools among ASLT academicians.However,only a few academicians have prior experience in AI courses.This indicates the pressing need for training concerning the appropriate use of AI in academia and support from universities.Furthermore,AI should be incorporated into academia with appropriate monitoring and ethical considerations.展开更多
The global trend of population aging poses significant challenges to society and healthcare systems,particularly because of neurocognitive disorders(NCDs)such as Parkinson's disease(PD)and Alzheimer's disease(...The global trend of population aging poses significant challenges to society and healthcare systems,particularly because of neurocognitive disorders(NCDs)such as Parkinson's disease(PD)and Alzheimer's disease(AD).In this context,artificial intelligence techniques have demonstrated promising potential for the objective assessment and detection of NCDs.Multimodal contactless screening technologies,such as speech-language processing,computer vision,and virtual reality,offer efficient and convenient methods for disease diagnosis and progression tracking.This paper systematically reviews the specific methods and applications of these technologies in the detection of NCDs using data collection paradigms,feature extraction,and modeling approaches.Additionally,the potential applications and future prospects of these technologies for the detection of cognitive and motor disorders are explored.By providing a comprehensive summary and refinement of the extant theories,methodologies,and applications,this study aims to facilitate an in-depth understanding of these technologies for researchers,both within and outside the field.To the best of our knowledge,this is the first survey to cover the use of speech-language processing,computer vision,and virtual reality technologies for the detection of NSDs.展开更多
The purpose of the present study was to examine the differences between perceptions of non-native phonotactic rules and constraints by monolingual English-speaking undergraduate students in a program of communication ...The purpose of the present study was to examine the differences between perceptions of non-native phonotactic rules and constraints by monolingual English-speaking undergraduate students in a program of communication disorders who had taken and passed a course in the study of phonology and by undergraduate students in communication disorders who had not yet taken a course in phonology. Participants listened to audio recordings of words from Hindi, Hmong, Kurdish, Russian, and Swedish recorded by speakers fluent in those languages. Each of the words contained at least one phonotactic constraint that is not permitted in American English phonology. Participants were instructed to write exactly what they heard after each word in the recordings, and their perceptions of the illegal constraints were scored as correct or incorrect. No significant difference was found between the students who had taken a phonology course and the students who had not. The most common misperception made was the omission of one phoneme when two were illegally combined. The results of this study, though not consistent with anticipated results, have many implications for issues concerning the linguistic diversity of the United States, among other issues related to language.展开更多
文摘Purpose Artificial intelligence(AI)is developing across the world in every domain,such as finance,manufacturing,entertainment,agriculture,retail,healthcare,and law.Its use in the education sector has exponentially increased.The present global survey explored the utilization of AI among academicians in audiology and speech-language therapy(ASLT)and their willingness to use AI tools in their academic work.Method This study used a cross-sectional survey design.One hundred and six ASLT academicians participated in the survey(February 2024 to April 2024).The questionnaire contains 18 items,which included a five-point rating scale,yes-no,and open-ended questions.Descriptive statistics were used for analysis.Results Most of the participants were from Asia and North America,followed by Africa.Nearly sixty-eight percent of the academicians used AI tools in their practice.The major concerns reported by the participants were the authenticity of the data,security,the addition of irrelevant information,and incorrect citations.The participants also mentioned that the frequent use of AI tools can reduce a person’s ability to devise novel ideas.AI tools such as ChatGPT,Canva,Grammarly AI,Mentimeter,QuillBot,ResearchRabbit,and Scribd were reported by participants.Conclusions The present study highlights the use of AI tools among ASLT academicians.However,only a few academicians have prior experience in AI courses.This indicates the pressing need for training concerning the appropriate use of AI in academia and support from universities.Furthermore,AI should be incorporated into academia with appropriate monitoring and ethical considerations.
基金Supported by the National Science and Technology Major Project(2022ZD0118002)the Basic Research Project of the Institute of Software,Chinese Academy of Sciences(ISCAS-JCMS-202306)the Youth Innovation Promotion Association CAS Grant(2023119).
文摘The global trend of population aging poses significant challenges to society and healthcare systems,particularly because of neurocognitive disorders(NCDs)such as Parkinson's disease(PD)and Alzheimer's disease(AD).In this context,artificial intelligence techniques have demonstrated promising potential for the objective assessment and detection of NCDs.Multimodal contactless screening technologies,such as speech-language processing,computer vision,and virtual reality,offer efficient and convenient methods for disease diagnosis and progression tracking.This paper systematically reviews the specific methods and applications of these technologies in the detection of NCDs using data collection paradigms,feature extraction,and modeling approaches.Additionally,the potential applications and future prospects of these technologies for the detection of cognitive and motor disorders are explored.By providing a comprehensive summary and refinement of the extant theories,methodologies,and applications,this study aims to facilitate an in-depth understanding of these technologies for researchers,both within and outside the field.To the best of our knowledge,this is the first survey to cover the use of speech-language processing,computer vision,and virtual reality technologies for the detection of NSDs.
文摘The purpose of the present study was to examine the differences between perceptions of non-native phonotactic rules and constraints by monolingual English-speaking undergraduate students in a program of communication disorders who had taken and passed a course in the study of phonology and by undergraduate students in communication disorders who had not yet taken a course in phonology. Participants listened to audio recordings of words from Hindi, Hmong, Kurdish, Russian, and Swedish recorded by speakers fluent in those languages. Each of the words contained at least one phonotactic constraint that is not permitted in American English phonology. Participants were instructed to write exactly what they heard after each word in the recordings, and their perceptions of the illegal constraints were scored as correct or incorrect. No significant difference was found between the students who had taken a phonology course and the students who had not. The most common misperception made was the omission of one phoneme when two were illegally combined. The results of this study, though not consistent with anticipated results, have many implications for issues concerning the linguistic diversity of the United States, among other issues related to language.
