Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Chon, Ben Sangbae"'
To achieve successful deployment of AI research, it is crucial to understand the demands of the industry. In this paper, we present the results of a survey conducted with professional audio engineers, in order to determine research priorities and def
Externí odkaz:
http://arxiv.org/abs/2307.04292
This paper introduces FALL-E, a foley synthesis system and its training/inference strategies. The FALL-E model employs a cascaded approach comprising low-resolution spectrogram generation, spectrogram super-resolution, and a vocoder. We trained every
Externí odkaz:
http://arxiv.org/abs/2306.09807
In real-world acoustic scenarios, there often are multiple sound sources present in a room. These sources are situated in various locations and produce sounds that reach the listener from multiple directions. The presence of multiple sources in a roo
Externí odkaz:
http://arxiv.org/abs/2305.15898
Separation of multiple singing voices into each voice is a rarely studied area in music source separation research. The absence of a benchmark dataset has hindered its progress. In this paper, we present an evaluation dataset and provide baseline stu
Externí odkaz:
http://arxiv.org/abs/2211.07302
Autor:
Park, Soochul, Chon, Ben Sangbae
In the field of audio signal processing research, source separation has been a popular research topic for a long time and the recent adoption of the deep neural networks have shown a significant improvement in performance. The improvement vitalizes t
Externí odkaz:
http://arxiv.org/abs/2010.12139
Publikováno v:
ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
Separation of multiple singing voices into each voice is a rarely studied area in music source separation research. The absence of a benchmark dataset has hindered its progress. In this paper, we present an evaluation dataset and provide baseline stu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6bb62086604dfdfb56f095e49828d187
https://doi.org/10.1109/icassp49357.2023.10095425
https://doi.org/10.1109/icassp49357.2023.10095425
