Zobrazeno 1 - 8
of 8
pro vyhledávání: '"R. Channing Moore"'
Autor:
Caroline Liu, Daniel P. W. Ellis, Manoj Plakal, Shawn Hershey, Eduardo Fonseca, Aren Jansen, R. Channing Moore
Publikováno v:
ICASSP
To reveal the importance of temporal precision in ground truth audio event labels, we collected precise (~0.1 sec resolution) "strong" labels for a portion of the AudioSet dataset. We devised a temporally strong evaluation set (including explicit neg
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0a6937aea8dccae8e0c7e85d9248bd37
https://doi.org/10.1109/icassp39728.2021.9414579
https://doi.org/10.1109/icassp39728.2021.9414579
Autor:
Eduardo Fonseca, Aren Jansen, Daniel P. W. Ellis, Scott Wisdom, Marco Tagliasacchi, John R. Hershey, Manoj Plakal, Shawn Hershey, R. Channing Moore, Xavier Serra
Comunicació presentada a 2021 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA), celebrat del 17 al 20 d'octubre de 2021 a New Paltz, Estats Units. Real-world sound scenes consist of time-varying collections of sound
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b61bcf54e52a20604b992da9fb020b48
Publikováno v:
PLoS Computational Biology, Vol 9, Iss 3, p e1002942 (2013)
Given the extraordinary ability of humans and animals to recognize communication signals over a background of noise, describing noise invariant neural responses is critical not only to pinpoint the brain regions that are mediating our robust percepti
Externí odkaz:
https://doaj.org/article/7c2c5575599b4dc19d7fd054c069d659
Autor:
R. Channing Moore, Manoj Plakal, Shawn Hershey, Aren Jansen, Rif A. Saurous, Daniel P. W. Ellis, Ashok C. Popat
Publikováno v:
ICASSP
Humans do not acquire perceptual abilities in the way we train machines. While machine learning algorithms typically operate on large collections of randomly-chosen, explicitly-labeled examples, human acquisition relies more heavily on multimodal uns
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3533adfecacf51f3482a45c45cde20b0
Autor:
R. Channing Moore, Jiayang Liu, Daniel P. W. Ellis, Manoj Plakal, Rif A. Saurous, Shawn Hershey, Ratheet Pandya, Aren Jansen
Publikováno v:
ICASSP
Even in the absence of any explicit semantic annotation, vast collections of audio recordings provide valuable information for learning the categorical structure of sounds. We consider several class-agnostic semantic constraints that apply to unlabel
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::db3af88665575c08b62b132350a1681e
https://doi.org/10.1109/icassp.2018.8461684
https://doi.org/10.1109/icassp.2018.8461684
Autor:
Aren Jansen, Jort F. Gemmeke, Manoj Plakal, Daniel P. W. Ellis, Wade Lawrence, Dylan Freedman, Marvin Ritter, R. Channing Moore
Publikováno v:
ICASSP
Audio event recognition, the human-like ability to identify and relate sounds from audio, is a nascent problem in machine perception. Comparable problems such as object detection in images have reaped enormous benefits from comprehensive datasets - p
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::806c5ff2a1bc65209d05320257e8e93d
https://doi.org/10.1109/icassp.2017.7952261
https://doi.org/10.1109/icassp.2017.7952261
Autor:
R. Channing Moore, Aren Jansen, Sourish Chaudhuri, Kevin W. Wilson, Manoj Plakal, Shawn Hershey, Rif A. Saurous, Daniel P. W. Ellis, Devin Platt, Malcolm Slaney, Bryan Seybold, Ron Weiss, Jort F. Gemmeke
Publikováno v:
ICASSP
Convolutional Neural Networks (CNNs) have proven very effective in image classification and show promise for audio. We use various CNN architectures to classify the soundtracks of a dataset of 70M training videos (5.24 million hours) with 30,871 vide
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::82f4931fb9e5b087ff1934c8093ff651
Publikováno v:
PLoS computational biology, vol 9, iss 3
PLoS Computational Biology, Vol 9, Iss 3, p e1002942 (2013)
PLoS Computational Biology
PLoS Computational Biology, Vol 9, Iss 3, p e1002942 (2013)
PLoS Computational Biology
Given the extraordinary ability of humans and animals to recognize communication signals over a background of noise, describing noise invariant neural responses is critical not only to pinpoint the brain regions that are mediating our robust percepti
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e398675ef946d7c664800d1e26612f1f
https://doi.org/10.1371/journal.pcbi.1002942
https://doi.org/10.1371/journal.pcbi.1002942