{"title":"Open Brain AI: An AI Research Platform","authors":"C. Themistocleous","doi":"10.3384/ecp205001","DOIUrl":null,"url":null,"abstract":"Language assessment is pivotal in identifying therapeutic interventions for speech, language, and communication disorders stemming from neurogenic origins, developmental or acquired, and student performance in the classroom. Traditional assessment techniques, however, are predominantly manual, necessitating extensive time and effort for administration and scoring. Such procedures can exacerbate the stress experienced by patients. In response to these inherent challenges, we introduced Open Brain AI (https://openbrainai.com). This state-of-the-art computational platform leverages advanced AI methodologies, encompassing machine learning, natural language processing, large language models, and automated speech-to-text transcription. These capabilities enable Open Brain AI to autonomously analyze multilingual spoken and written language productions. This work aims to present the development and evolution of Open Brain AI, elucidating its AI-driven language processing components and the intricate linguistic metrics it employs to evaluate the overarching and granular discourse structures. Open Brain AI significantly reduces the workload on researchers, clinicians, and teachers by facilitating rapid and automated language analysis. It allows healthcare and education professionals to optimize their operational processes, reallocating precious time and resources to more personalized user interactions. Moreover, Open Brain AI provides clinicians, researchers, and educators the autonomy to undertake essential data analytics, freeing up more bandwidth to focus on other vital facets of therapeutic intervention and care.","PeriodicalId":285622,"journal":{"name":"Linköping Electronic Conference Proceedings","volume":"40 11","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Linköping Electronic Conference Proceedings","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3384/ecp205001","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Language assessment is pivotal in identifying therapeutic interventions for speech, language, and communication disorders stemming from neurogenic origins, developmental or acquired, and student performance in the classroom. Traditional assessment techniques, however, are predominantly manual, necessitating extensive time and effort for administration and scoring. Such procedures can exacerbate the stress experienced by patients. In response to these inherent challenges, we introduced Open Brain AI (https://openbrainai.com). This state-of-the-art computational platform leverages advanced AI methodologies, encompassing machine learning, natural language processing, large language models, and automated speech-to-text transcription. These capabilities enable Open Brain AI to autonomously analyze multilingual spoken and written language productions. This work aims to present the development and evolution of Open Brain AI, elucidating its AI-driven language processing components and the intricate linguistic metrics it employs to evaluate the overarching and granular discourse structures. Open Brain AI significantly reduces the workload on researchers, clinicians, and teachers by facilitating rapid and automated language analysis. It allows healthcare and education professionals to optimize their operational processes, reallocating precious time and resources to more personalized user interactions. Moreover, Open Brain AI provides clinicians, researchers, and educators the autonomy to undertake essential data analytics, freeing up more bandwidth to focus on other vital facets of therapeutic intervention and care.
语言评估对于确定语言、言语和交流障碍的治疗干预措施至关重要,这些障碍源于神经源性、发育性或后天性,以及学生在课堂上的表现。然而,传统的评估技术以人工操作为主,需要花费大量的时间和精力进行操作和评分。这些程序会加重患者的压力。为了应对这些固有的挑战,我们推出了开放脑人工智能 (https://openbrainai.com)。这一先进的计算平台采用了先进的人工智能方法,包括机器学习、自然语言处理、大型语言模型和自动语音转文字。这些功能使开放脑人工智能能够自主分析多语言口语和书面语言产品。这项工作旨在介绍开放脑人工智能的发展和演变,阐明其人工智能驱动的语言处理组件,以及其用于评估总体和细粒度话语结构的复杂语言学指标。开放脑人工智能通过促进快速和自动化的语言分析,大大减轻了研究人员、临床医生和教师的工作量。它允许医疗保健和教育专业人员优化操作流程,将宝贵的时间和资源重新分配给更个性化的用户互动。此外,Open Brain AI 还为临床医生、研究人员和教育工作者提供了进行基本数据分析的自主权,从而腾出更多带宽来关注治疗干预和护理的其他重要方面。