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pro vyhledávání: '"Seyed Omid Sadjadi"'
Automatic emotion recognition plays a key role in computer-human interaction as it has the potential to enrich the next-generation artificial intelligence with emotional intelligence. It finds applications in customer and/or representative behavior a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::eb58cde3b2429b362346f76d63ff9591
http://arxiv.org/abs/2202.08974
http://arxiv.org/abs/2202.08974
Publikováno v:
ICMI
Automatic speech emotion recognition (SER) is a challenging task that plays a crucial role in natural human-computer interaction. One of the main challenges in SER is data scarcity, i.e., insufficient amounts of carefully labeled data to build and fu
Autor:
Christopher Cieri, Seyed Omid Sadjadi, Aditya Joglekar, Meena Chandra-Shekar, John H. L. Hansen
Publikováno v:
Interspeech 2021.
Autor:
Craig S. Greenberg, Lisa P. Mason, Elliot Singer, Douglas A. Reynolds, Seyed Omid Sadjadi, Jaime Hernandez-Cordero
Publikováno v:
Odyssey
Publikováno v:
Voice Technologies for Speech Reconstruction and Enhancement
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::61602b047573491ea97b379a2b4312a6
https://doi.org/10.1515/9781501501265-005
https://doi.org/10.1515/9781501501265-005
Publikováno v:
Computer Speech & Language. 60:101032
The National Institute of Standards and Technology has been conducting Speaker Recognition Evaluations (SREs) for over 20 years. This article provides an overview of the practice of evaluating speaker recognition technology as it has evolved during t
Autor:
Jaime Hernandez-Cordero, Douglas A. Reynolds, Seyed Omid Sadjadi, Elliot Singer, Timothée Kheyrkhah, Craig S. Greenberg, Lisa P. Mason
Publikováno v:
INTERSPEECH
Autor:
Jaime Hernandez-Cordero, Audrey Tong, Craig S. Greenberg, Lisa P. Mason, Elliot Singer, Douglas A. Reynolds, Seyed Omid Sadjadi, Timothée Kheyrkhah
Publikováno v:
Odyssey
Autor:
Seyed Omid Sadjadi, John H. L. Hansen
Publikováno v:
Speech Communication. 72:138-148
Adverse noisy conditions pose great challenges to automatic speech applications including speaker and language identification (SID and LID), where mel-frequency cepstral coefficients (MFCC) are the most commonly adopted acoustic features. Although sy