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of 807
pro vyhledávání: '"Biswas Arijit"'
Autor:
Biswas, Arijit, Jiang, Guanxin
This paper introduces a novel reference-free (RF) audio quality metric called the RF-Generative Machine Listener (RF-GML), designed to evaluate coded mono, stereo, and binaural audio at a 48 kHz sample rate. RF-GML leverages transfer learning from a
Externí odkaz:
http://arxiv.org/abs/2409.10210
Autor:
Wang, Zhuoer, Ribeiro, Leonardo F. R., Papangelis, Alexandros, Mukherjee, Rohan, Wang, Tzu-Yen, Zhao, Xinyan, Biswas, Arijit, Caverlee, James, Metallinou, Angeliki
API call generation is the cornerstone of large language models' tool-using ability that provides access to the larger world. However, existing supervised and in-context learning approaches suffer from high training costs, poor data efficiency, and g
Externí odkaz:
http://arxiv.org/abs/2407.13945
Autor:
Jo, Yohan, Zhao, Xinyan, Biswas, Arijit, Basiou, Nikoletta, Auvray, Vincent, Malandrakis, Nikolaos, Metallinou, Angeliki, Potamianos, Alexandros
While most task-oriented dialogues assume conversations between the agent and one user at a time, dialogue systems are increasingly expected to communicate with multiple users simultaneously who make decisions collaboratively. To facilitate developme
Externí odkaz:
http://arxiv.org/abs/2310.20479
We show how a neural network can be trained on individual intrusive listening test scores to predict a distribution of scores for each pair of reference and coded input stereo or binaural signals. We nickname this method the Generative Machine Listen
Externí odkaz:
http://arxiv.org/abs/2308.09493
Autor:
Biswas, Arijit, Mundt, Harald
Video Multimethod Assessment Fusion (VMAF) [1], [2], [3] is a popular tool in the industry for measuring coded video quality. In this study, we propose an auditory-inspired frontend in existing VMAF for creating videos of reference and coded spectrog
Externí odkaz:
http://arxiv.org/abs/2308.03437
Autor:
Biswas, Arijit, Jiang, Guanxin
Automatic coded audio quality predictors are typically designed for evaluating single channels without considering any spatial aspects. With InSE-NET [1], we demonstrated mimicking a state-of-the-art coded audio quality metric (ViSQOL-v3 [2]) with de
Externí odkaz:
http://arxiv.org/abs/2209.11666
Most popular goal-oriented dialogue agents are capable of understanding the conversational context. However, with the surge of virtual assistants with screen, the next generation of agents are required to also understand screen context in order to pr
Externí odkaz:
http://arxiv.org/abs/2111.11576
Autor:
Haas, Bodo, Hass, Moritz David Sebastian, Voltz, Alexander, Vogel, Matthias, Walther, Julia, Biswas, Arijit, Hass, Daniela, Pfeifer, Alexander
Publikováno v:
In Molecular Metabolism July 2024 85
Automatic coded audio quality assessment is an important task whose progress is hampered by the scarcity of human annotations, poor generalization to unseen codecs, bitrates, content-types, and a lack of flexibility of existing approaches. One of the
Externí odkaz:
http://arxiv.org/abs/2108.13087
In-depth structure-function profiling of the complex formation between clotting factor VIII and heme
Autor:
Hopp, Marie-T., Ugurlar, Deniz, Pezeshkpoor, Behnaz, Biswas, Arijit, Ramoji, Anuradha, Neugebauer, Ute, Oldenburg, Johannes, Imhof, Diana
Publikováno v:
In Thrombosis Research May 2024 237:184-195