Zobrazeno 31 - 40
of 117
pro vyhledávání: '"Weon Jung"'
In this work, we propose an overlapped speech detection system trained as a three-class classifier. Unlike conventional systems that perform binary classification as to whether or not a frame contains overlapped speech, the proposed approach classifi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::95a8558010a57b68e17d6330a6b10626
http://arxiv.org/abs/2104.02878
http://arxiv.org/abs/2104.02878
Publikováno v:
Journal of Orthopaedic Trauma. 33:250-255
Objective To identify risk factors associated with subsequent recurrent instability and to identify predictors of poor outcomes in terrible triad injury of the elbow. Design Retrospective cohort study. Setting University trauma center. Patients/parti
Publikováno v:
Odyssey
Publikováno v:
INTERSPEECH
Constructing a dataset for replay spoofing detection requires a physical process of playing an utterance and re-recording it, presenting a challenge to the collection of large-scale datasets. In this study, we propose a self-supervised framework for
Autor:
Hansol Chang, Weon Jung, Juhyung Ha, Jae Yong Yu, Sejin Heo, Gun Tak Lee, Jong Eun Park, Se Uk Lee, Sung Yeon Hwang, Hee Yoon, Won Chul Cha, Tae Gun Shin, Taerim Kim
Publikováno v:
Shock; Dec2023, Vol. 60 Issue 6, p782-783, 2p
Publikováno v:
INTERSPEECH
Most studies on speaker verification systems focus on long-duration utterances, which are composed of sufficient phonetic information. However, the performances of these systems are known to degrade when short-duration utterances are inputted due to
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c4784d1479bd32a70ad4fa5a52e5d0b6
http://arxiv.org/abs/2005.03329
http://arxiv.org/abs/2005.03329
Publikováno v:
INTERSPEECH
Recent advances in deep learning have facilitated the design of speaker verification systems that directly input raw waveforms. For example, RawNet extracts speaker embeddings from raw waveforms, which simplifies the process pipeline and demonstrates
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::12aff845942fbe6a16f4b35ddbe7b898
http://arxiv.org/abs/2004.00526
http://arxiv.org/abs/2004.00526
Publikováno v:
ICASSP
Although acoustic scenes and events include many related tasks, their combined detection and classification have been scarcely investigated. We propose three architectures of deep neural networks that are integrated to simultaneously perform acoustic
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::aab790264b95af1618690a76c009ded5
Publikováno v:
INTERSPEECH
Acoustic scene classification systems using deep neural networks classify given recordings into pre-defined classes. In this study, we propose a novel scheme for acoustic scene classification which adopts an audio tagging system inspired by the human
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::349f7be9344fbd334e0ce3aa7bd69ef0
Publikováno v:
ASRU
The short duration of an input utterance is one of the most critical threats that degrade the performance of speaker verification systems. This study aimed to develop an integrated text-independent speaker verification system that inputs utterances w