Zobrazeno 1 - 10
of 216
pro vyhledávání: '"Reiss, Joshua"'
Autor:
Vanka, Soumya Sai, Steinmetz, Christian, Rolland, Jean-Baptiste, Reiss, Joshua, Fazekas, George
Mixing style transfer automates the generation of a multitrack mix for a given set of tracks by inferring production attributes from a reference song. However, existing systems for mixing style transfer are limited in that they often operate only on
Externí odkaz:
http://arxiv.org/abs/2407.08889
Autor:
Chen, Mingjie, Zhang, Hezhao, Li, Yuanchao, Luo, Jiachen, Wu, Wen, Ma, Ziyang, Bell, Peter, Lai, Catherine, Reiss, Joshua, Wang, Lin, Woodland, Philip C., Chen, Xie, Phan, Huy, Hain, Thomas
Speech emotion recognition is a challenging classification task with natural emotional speech, especially when the distribution of emotion types is imbalanced in the training and test data. In this case, it is more difficult for a model to learn to s
Externí odkaz:
http://arxiv.org/abs/2405.20064
We propose a speech enhancement system for multitrack audio. The system will minimize auditory masking while allowing one to hear multiple simultaneous speakers. The system can be used in multiple communication scenarios e.g., teleconferencing, invoi
Externí odkaz:
http://arxiv.org/abs/2404.17821
Autor:
Yu, Chin-Yun, Mitcheltree, Christopher, Carson, Alistair, Bilbao, Stefan, Reiss, Joshua D., Fazekas, György
Infinite impulse response filters are an essential building block of many time-varying audio systems, such as audio effects and synthesisers. However, their recursive structure impedes end-to-end training of these systems using automatic differentiat
Externí odkaz:
http://arxiv.org/abs/2404.07970
Autor:
Comunità, Marco, Gramaccioni, Riccardo F., Postolache, Emilian, Rodolà, Emanuele, Comminiello, Danilo, Reiss, Joshua D.
Sound design involves creatively selecting, recording, and editing sound effects for various media like cinema, video games, and virtual/augmented reality. One of the most time-consuming steps when designing sound is synchronizing audio with video. I
Externí odkaz:
http://arxiv.org/abs/2310.15247
Noise reduction techniques based on deep learning have demonstrated impressive performance in enhancing the overall quality of recorded speech. While these approaches are highly performant, their application in audio engineering can be limited due to
Externí odkaz:
http://arxiv.org/abs/2310.11364
We present a non-supervised approach to optimize and evaluate the synthesis of non-speech audio effects from a speech production model. We use the Pink Trombone synthesizer as a case study of a simplified production model of the vocal tract to target
Externí odkaz:
http://arxiv.org/abs/2309.14761
Although the design and application of audio effects is well understood, the inverse problem of removing these effects is significantly more challenging and far less studied. Recently, deep learning has been applied to audio effect removal; however,
Externí odkaz:
http://arxiv.org/abs/2308.16177