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Touch plays a central role in how humans perceive and recognize materials through physical contact. Despite decades of research, the mechanisms by which tactile signals are transformed into meaningful perceptual representations remain…

人机交互 · 计算机科学 2026-05-19 Yasemin Vardar

Deep learning methods have revolutionized speech recognition, image recognition, and natural language processing since 2010. Each of these tasks involves a single modality in their input signals. However, many applications in the artificial…

人工智能 · 计算机科学 2020-07-15 Chao Zhang , Zichao Yang , Xiaodong He , Li Deng

Haptic feedback has been integrated into Virtual and Augmented Reality, complementing acoustic and visual information and contributing to an all-round immersive experience in multiple fields, spanning from the medical domain to…

多媒体 · 计算机科学 2025-11-26 Antonio Luigi Stefani , Niccolò Bisagno , Andrea Rosani , Nicola Conci , Francesco De Natale

Computer-generated visualisations can accompany recorded or live music to create novel audiovisual experiences for audiences. We present a system to streamline the creation of audio-driven visualisations based on audio feature extraction…

多媒体 · 计算机科学 2021-06-21 Max Graf , Harold Chijioke Opara , Mathieu Barthet

The present methodology is aimed at cross-modal machine learning and uses multidisciplinary tools and methods drawn from a broad range of areas and disciplines, including music, systematic musicology, dance, motion capture, human-computer…

人机交互 · 计算机科学 2017-12-04 Fabio Paolizzo

Handheld kinesthetic haptic interfaces can provide greater mobility and richer tactile information as compared to traditional grounded devices. In this paper, we introduce a new handheld haptic interface which takes input using…

系统与控制 · 电气工程与系统科学 2023-09-07 Megh Vipul Doshi , Michael Hagenow , Robert Radwin , Michael Gleicher , Bilge Mutlu , Michael Zinn

Humans use a host of signals to infer the emotional state of others. In general, computer systems that leverage signals from multiple modalities will be more robust and accurate in the same task. We present a multimodal affect and context…

人机交互 · 计算机科学 2019-03-29 Daniel McDuff , Kael Rowan , Piali Choudhury , Jessica Wolk , ThuVan Pham , Mary Czerwinski

Our experience of the world is multisensory, spanning a synthesis of language, sight, sound, touch, taste, and smell. Yet, artificial intelligence has primarily advanced in digital modalities like text, vision, and audio. This paper…

机器学习 · 计算机科学 2026-01-14 Paul Pu Liang

This study investigates emotional expression and perception in music performance using computational and neurophysiological methods. The influence of different performance settings, such as repertoire, diatonic modal etudes, and…

This paper presents key aspects and trade-offs that designers and Human-Computer Interaction practitioners might encounter when designing multimodal interaction for older adults. The paper gathers literature on multimodal interaction and…

人机交互 · 计算机科学 2021-03-10 Gianluca Schiavo , Ornella Mich , Michela Ferron , Nadia Mana

Visual question answering and visual dialogue tasks have been increasingly studied in the multimodal field towards more practical real-world scenarios. A more challenging task, audio visual scene-aware dialogue (AVSD), is proposed to…

计算与语言 · 计算机科学 2019-08-15 Yi-Ting Yeh , Tzu-Chuan Lin , Hsiao-Hua Cheng , Yu-Hsuan Deng , Shang-Yu Su , Yun-Nung Chen

Humans are talented with the ability to perform diverse interactions in the teaching process. However, when humans want to teach AI, existing interactive systems only allow humans to perform repetitive labeling, causing an unsatisfactory…

人机交互 · 计算机科学 2022-09-07 Zhongyi Zhou

Multimodal sentiment analysis is a key technology in the fields of human-computer interaction and affective computing. Accurately recognizing human emotional states is crucial for facilitating smooth communication between humans and…

计算机视觉与模式识别 · 计算机科学 2026-01-07 Wangyuan Zhu , Jun Yu

Multi-modal emotion recognition in conversations is a challenging problem due to the complex and complementary interactions between different modalities. Audio and textual cues are particularly important for understanding emotions from a…

声音 · 计算机科学 2025-04-02 Jiachen Luo , Huy Phan , Lin Wang , Joshua Reiss

Multimodal input systems can help bridge the wide range of physical abilities found in older generations. After conducting a survey/interview session with a group of older adults at an assisted living community we believe that gesture and…

人机交互 · 计算机科学 2020-08-28 Adam S. Williams , Sarah Coler , Francisco Ortega

The analysis of the current integration attempts of some modes and use cases of user-machine interaction is presented. The new concept of the user-driven intelligent interface is proposed on the basis of multimodal augmented reality and…

People feel emotions when listening to music. However, emotions are not tangible objects that can be exploited in the music composition process as they are difficult to capture and quantify in algorithms. We present a novel musical…

人工智能 · 计算机科学 2018-10-09 Eunjeong Stella Koh , Shahrokh Yadegari

Haptic feedback is critical in a broad range of human-machine/computer-interaction applications. However, the high cost and low portability/wearability of haptic devices remain unresolved issues, severely limiting the adoption of this…

人机交互 · 计算机科学 2024-10-28 Panagiotis Kourtesis , Ferran Argelaguet , Sebastian Vizcay , Maud Marchal , Claudio Pacchierotti

Grounded haptic devices can provide a variety of forces but have limited working volumes. Wearable haptic devices operate over a large volume but are relatively restricted in the types of stimuli they can generate. We propose the concept of…

人机交互 · 计算机科学 2020-10-23 Anthony Steed , Sebastian Friston , Vijay Pawar , David Swapp

Music Emotion Recognition involves the automatic identification of emotional elements within music tracks, and it has garnered significant attention due to its broad applicability in the field of Music Information Retrieval. It can also be…

声音 · 计算机科学 2023-08-29 Kexin Zhu , Xulong Zhang , Jianzong Wang , Ning Cheng , Jing Xiao