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Related papers: Personalized Socially Assistive Robots With End-to…

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Socially assistive robots (SARs) have shown great success in providing personalized cognitive-affective support for user populations with special needs such as older adults, children with autism spectrum disorder (ASD), and individuals with…

Human-Computer Interaction · Computer Science 2024-04-09 Zhonghao Shi , Ellen Landrum , Amy O' Connell , Mina Kian , Leticia Pinto-Alva , Kaleen Shrestha , Xiaoyuan Zhu , Maja J Matarić

Socially Assistive Robots (SARs) offer unique opportunities within speech language pathology (SLP) education and practice by supporting interactive interventions for children with communication disorders. This paper explores the…

Robotics · Computer Science 2025-04-23 Denielle Oliva , Abbie Olszewski , David Feil-Seifer

The emergence of large language models (LLM) and, consequently, vision language models (VLM) has ignited new imaginations among robotics researchers. At this point, the range of applications to which LLM and VLM can be applied in…

Robotics · Computer Science 2024-11-28 Jesse Atuhurra

Socially assistive robots (SAR) have shown great potential to augment the social and educational development of children with autism spectrum disorders (ASD). As SAR continues to substantiate itself as an effective enhancement to human…

Socially Assistive Robotics (SAR) has shown promise in supporting emotion regulation for neurodivergent children. Recently, there has been increasing interest in leveraging advanced technologies to assist parents in co-regulating emotions…

Human-Computer Interaction · Computer Science 2025-07-15 Jing Li , Felix Schijve , Sheng Li , Yuye Yang , Jun Hu , Emilia Barakova

Large Language Models (LLMs) have recently garnered significant attention, primarily for their capabilities in text-based interactions. However, natural human interaction often relies on speech, necessitating a shift towards voice-based…

Computation and Language · Computer Science 2025-08-08 Wenqian Cui , Dianzhi Yu , Xiaoqi Jiao , Ziqiao Meng , Guangyan Zhang , Qichao Wang , Yiwen Guo , Irwin King

Large-language models (LLMs) hold significant promise in improving human-robot interaction, offering advanced conversational skills and versatility in managing diverse, open-ended user requests in various tasks and domains. Despite the…

Robotics · Computer Science 2024-01-09 Callie Y. Kim , Christine P. Lee , Bilge Mutlu

Physically assistive robots present an opportunity to significantly increase the well-being and independence of individuals with motor impairments or other forms of disability who are unable to complete activities of daily living (ADLs).…

Large language models (LLMs) are being integrated into socially assistive robots (SARs) and other conversational agents providing mental health and well-being support. These agents are often designed to sound empathic and supportive in…

Human-Computer Interaction · Computer Science 2026-02-05 Himanshi Lalwani , Hanan Salam

Physically assistive robots present an opportunity to significantly increase the well-being and independence of individuals with motor impairments or other forms of disability who are unable to complete activities of daily living. Speech…

Beyond mere formality, small talk plays a pivotal role in social dynamics, serving as a verbal handshake for building rapport and understanding. For conversational AI and social robots, the ability to engage in small talk enhances their…

Robotics · Computer Science 2024-12-25 Rebecca Ramnauth , Dražen Brščić , Brian Scassellati

Socially assistive robotics (SAR) research has shown great potential for supplementing and augmenting therapy for children with autism spectrum disorders (ASD). However, the vast majority of SAR research has been limited to short-term…

Robotics · Computer Science 2020-01-28 Roxanna Pakkar , Caitlyn Clabaugh , Rhianna Lee , Eric Deng , Maja J Mataric

Social robots aim to establish long-term bonds with humans through engaging conversation. However, traditional conversational approaches, reliant on scripted interactions, often fall short in maintaining engaging conversations. This paper…

Robotics · Computer Science 2024-02-20 Zining Wang , Paul Reisert , Eric Nichols , Randy Gomez

Advances in machine learning have made it possible to perform various text and speech processing tasks, such as automatic speech recognition (ASR), in an end-to-end (E2E) manner. E2E approaches utilizing pre-trained models are gaining…

Audio and Speech Processing · Electrical Eng. & Systems 2024-06-07 Yukiya Hono , Koh Mitsuda , Tianyu Zhao , Kentaro Mitsui , Toshiaki Wakatsuki , Kei Sawada

The rapid advancement of Large Language Models (LLMs) has opened new possibilities in Multi-Robot Systems (MRS), enabling enhanced communication, task allocation and planning, and human-robot interaction. Unlike traditional single-robot and…

Robotics · Computer Science 2026-05-05 Peihan Li , Zijian An , Shams Abrar , Lifeng Zhou

Large language models (LLMs) often struggle to learn from corrective feedback within a conversational context. They are rarely proactive in soliciting this feedback, even when faced with ambiguity, which can make their dialogues feel…

Computation and Language · Computer Science 2026-02-19 Jonathan Cook , Diego Antognini , Martin Klissarov , Claudiu Musat , Edward Grefenstette

End-to-end Spoken Language Models (SLMs) hold great potential for paralinguistic perception, and numerous studies have aimed to enhance their capabilities, particularly for empathetic dialogue. However, current approaches largely depend on…

Computation and Language · Computer Science 2026-01-27 Yuhang Jia , Pei Liu , Haoqin Sun , Jiaming Zhou , Xuxin Cheng , Cao Liu , Ke Zeng , Xunliang Cai , Yong Qin

Cognitive behavioral therapy (CBT) is a widely used therapeutic method for guiding individuals toward restructuring their thinking patterns as a means of addressing anxiety, depression, and other challenges. We developed a large language…

Recent advancements in Large Audio Language Models (LALMs) have demonstrated exceptional performance in speech recognition and translation. However, existing models often suffer from a disconnect between perception and expression, resulting…

Sound · Computer Science 2026-03-02 Yueran Hou , Peilei Jia , Zihan Sun , Qihang Lu , Wenbing Yang , Yingming Gao , Ya Li , Jun Gao

In this paper we examine the use of semantically-aligned speech representations for end-to-end spoken language understanding (SLU). We employ the recently-introduced SAMU-XLSR model, which is designed to generate a single embedding that…

Computation and Language · Computer Science 2022-10-12 Gaëlle Laperrière , Valentin Pelloin , Mickaël Rouvier , Themos Stafylakis , Yannick Estève
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