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pro vyhledávání: '"Schuller, Björn W."'
Emotion and Intent Joint Understanding in Multimodal Conversation (MC-EIU) aims to decode the semantic information manifested in a multimodal conversational history, while inferring the emotions and intents simultaneously for the current utterance. M
Externí odkaz:
http://arxiv.org/abs/2407.02751
Autor:
Christ, Lukas, Amiriparian, Shahin, Hawighorst, Friederike, Schill, Ann-Kathrin, Boutalikakis, Angelo, Graf-Vlachy, Lorenz, König, Andreas, Schuller, Björn W.
Flattery is an important aspect of human communication that facilitates social bonding, shapes perceptions, and influences behavior through strategic compliments and praise, leveraging the power of speech to build rapport effectively. Its automatic d
Externí odkaz:
http://arxiv.org/abs/2406.17667
Autor:
Chang, Yi, Ren, Zhao, Zhao, Zhonghao, Nguyen, Thanh Tam, Qian, Kun, Schultz, Tanja, Schuller, Björn W.
Speech emotion recognition (SER) plays a crucial role in human-computer interaction. The emergence of edge devices in the Internet of Things (IoT) presents challenges in constructing intricate deep learning models due to constraints in memory and com
Externí odkaz:
http://arxiv.org/abs/2406.15119
Foundation models have shown great promise in speech emotion recognition (SER) by leveraging their pre-trained representations to capture emotion patterns in speech signals. To further enhance SER performance across various languages and domains, we
Externí odkaz:
http://arxiv.org/abs/2406.10275
Telling stories is an integral part of human communication which can evoke emotions and influence the affective states of the audience. Automatically modeling emotional trajectories in stories has thus attracted considerable scholarly interest. Howev
Externí odkaz:
http://arxiv.org/abs/2406.02251
Publikováno v:
published at ICASSP 2024
Heart murmurs are a common manifestation of cardiovascular diseases and can provide crucial clues to early cardiac abnormalities. While most current research methods primarily focus on the accuracy of models, they often overlook other important aspec
Externí odkaz:
http://arxiv.org/abs/2405.03953
Publikováno v:
publised at ICASSP 2024
Automatically detecting Alzheimer's Disease (AD) from spontaneous speech plays an important role in its early diagnosis. Recent approaches highly rely on the Transformer architectures due to its efficiency in modelling long-range context dependencies
Externí odkaz:
http://arxiv.org/abs/2405.03952
Imbuing machines with the ability to talk has been a longtime pursuit of artificial intelligence (AI) research. From the very beginning, the community has not only aimed to synthesise high-fidelity speech that accurately conveys the semantic meaning
Externí odkaz:
http://arxiv.org/abs/2404.19363
Autor:
Lian, Zheng, Sun, Haiyang, Sun, Licai, Wen, Zhuofan, Zhang, Siyuan, Chen, Shun, Gu, Hao, Zhao, Jinming, Ma, Ziyang, Chen, Xie, Yi, Jiangyan, Liu, Rui, Xu, Kele, Liu, Bin, Cambria, Erik, Zhao, Guoying, Schuller, Björn W., Tao, Jianhua
Multimodal emotion recognition is an important research topic in artificial intelligence. Over the past few decades, researchers have made remarkable progress by increasing dataset size and building more effective architectures. However, due to vario
Externí odkaz:
http://arxiv.org/abs/2404.17113
Autor:
Amiriparian, Shahin, Gerczuk, Maurice, Lutz, Justina, Strube, Wolfgang, Papazova, Irina, Hasan, Alkomiet, Kathan, Alexander, Schuller, Björn W.
The delayed access to specialized psychiatric assessments and care for patients at risk of suicidal tendencies in emergency departments creates a notable gap in timely intervention, hindering the provision of adequate mental health support during cri
Externí odkaz:
http://arxiv.org/abs/2404.12132