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pro vyhledávání: '"Kowtha, Vasudha"'
This work investigates pretrained audio representations for few shot Sound Event Detection. We specifically address the task of few shot detection of novel acoustic sequences, or sound events with semantically meaningful temporal structure, without a
Externí odkaz:
http://arxiv.org/abs/2305.02382
Pre-trained model representations have demonstrated state-of-the-art performance in speech recognition, natural language processing, and other applications. Speech models, such as Bidirectional Encoder Representations from Transformers (BERT) and Hid
Externí odkaz:
http://arxiv.org/abs/2303.03177
Autor:
Mitra, Vikramjit, Chien, Hsiang-Yun Sherry, Kowtha, Vasudha, Cheng, Joseph Yitan, Azemi, Erdrin
Estimating dimensional emotions, such as activation, valence and dominance, from acoustic speech signals has been widely explored over the past few years. While accurate estimation of activation and dominance from speech seem to be possible, the same
Externí odkaz:
http://arxiv.org/abs/2207.03334
Autor:
Kowtha, Vasudha, Mitra, Vikramjit, Bartels, Chris, Marchi, Erik, Booker, Sue, Caruso, William, Kajarekar, Sachin, Naik, Devang
Emotion plays an essential role in human-to-human communication, enabling us to convey feelings such as happiness, frustration, and sincerity. While modern speech technologies rely heavily on speech recognition and natural language understanding for
Externí odkaz:
http://arxiv.org/abs/2002.01323
Akademický článek
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