AI-Based Automated Speech Therapy Tools for persons with Speech Sound Disorders: A Systematic Literature Review

Abstract

This paper presents a systematic literature review of published studies on AI-based automated speech therapy tools for persons with speech sound disorders (SSD). The COVID-19 pandemic has initiated the requirement for automated speech therapy tools for persons with SSD making speech therapy accessible and affordable. However, there are no guidelines for designing such automated tools and their required degree of automation compared to human experts. In this systematic review, we followed the PRISMA framework to address four research questions: 1) what types of SSD do AI-based automated speech therapy tools address, 2) what is the level of autonomy achieved by such tools, 3) what are the different modes of intervention, and 4) how effective are such tools in comparison with human experts. An extensive search was conducted on digital libraries to find research papers relevant to our study from 2007 to 2022. The results show that AI-based automated speech therapy tools for persons with SSD are increasingly gaining attention among researchers. Articulation disorders were the most frequently addressed SSD based on the reviewed papers. Further, our analysis shows that most researchers proposed fully automated tools without considering the role of other stakeholders. Our review indicates that mobile-based and gamified applications were the most frequent mode of intervention. The results further show that only a few studies compared the effectiveness of such tools compared to expert Speech-Language Pathologists (SLP). Our paper presents the state-of- the-art in the field, contributes significant insights based on the research questions, and provides suggestions for future research directions.

Towards Human-Centered AI in Speech Therapy: Perspectives from a Low-Resource Setting

“…These findings have substantial implications for designing and developing the HCAI-STT for children with functional SSD. The HCAI-STT should incorporate comprehensive AI-based diagnostic capabilities that account for the multifaceted nature of SSD while adhering to HCAI goals such as fairness, accountability, explainability, trustworthiness, and safety [45]. The tool should include modules to facilitate early intervention, enabling parents to engage with therapy processes efficiently and effectively.…”

“…2). However, the existing research in this domain has been limited in its engagement with stakeholders and fails to employ a human-centered approach when incorporating AI into speech therapy [28]. Furthermore, to the best of our knowledge, no studies have been conducted on the needs and perspective of SLPs specifically focusing on the state of Assam/NER of India.…”