Zobrazeno 1 - 10
of 157
pro vyhledávání: '"Tomi Kinnunen"'
Publikováno v:
SoftwareX, Vol 14, Iss , Pp 100697- (2021)
The human voice differs substantially between individuals. This facilitates automatic speaker verification (ASV) — recognizing a person from his/her voice. ASV accuracy has substantially increased throughout the past decade due to recent advances i
Externí odkaz:
https://doaj.org/article/db2a715585ee4a9fab4be20618be7f76
Autor:
Md Sahidullah, Héctor Delgado, Massimiliano Todisco, Andreas Nautsch, Xin Wang, Tomi Kinnunen, Nicholas Evans, Junichi Yamagishi, Kong-Aik Lee
Publikováno v:
Handbook of Biometric Anti-Spoofing ISBN: 9789811952876
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2a28ab832d9b57c6178353a13f717050
https://doi.org/10.1007/978-981-19-5288-3_13
https://doi.org/10.1007/978-981-19-5288-3_13
We address speaker comparison by listening in a game-like environment, hypothesized to make the task more motivating for naive listeners. We present the same 30 trials selected with the help of an x-vector speaker recognition system from VoxCeleb to
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7107366da152d248370ff02618803367
http://arxiv.org/abs/2205.04923
http://arxiv.org/abs/2205.04923
Autor:
Hye-jin Shim, Hemlata Tak, Xuechen Liu, Hee-Soo Heo, Jee-weon Jung, Joon Son Chung, Soo-Whan Chung, Ha-Jin Yu, Bong-Jin Lee, Massimiliano Todisco, Héctor Delgado, Kong Aik Lee, Md Sahidullah, Tomi Kinnunen, Nicholas Evans
Publikováno v:
Odyssey 2022-The Speaker and Language Recognition Workshop
Odyssey 2022-The Speaker and Language Recognition Workshop, Jun 2022, Beijing, China
Odyssey 2022-The Speaker and Language Recognition Workshop, Jun 2022, Beijing, China
Deep learning has brought impressive progress in the study of both automatic speaker verification (ASV) and spoofing countermeasures (CM). Although solutions are mutually dependent, they have typically evolved as standalone sub-systems whereby CM sol
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4807a8147c4a95135bc271fb3a3291a6
http://arxiv.org/abs/2204.09976
http://arxiv.org/abs/2204.09976
As automatic speaker verification (ASV) systems are vulnerable to spoofing attacks, they are typically used in conjunction with spoofing countermeasure (CM) systems to improve security. For example, the CM can first determine whether the input is hum
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d41bb2402e15d601f2aa54976969ae6f
http://arxiv.org/abs/2201.09709
http://arxiv.org/abs/2201.09709
Due to a constantly increasing amount of speech data that is stored in different types of databases, voice privacy has become a major concern. To respond to such concern, speech researchers have developed various methods for speaker de-identification
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1d79d741e7446ae49416acba86e5ed06
Publikováno v:
Computer Science
Odyssey 2022 – The Speaker and Language Recognition Workshop
Odyssey 2022 – The Speaker and Language Recognition Workshop, Jun 2022, Beijing, China. pp.85-91, ⟨10.21437/Odyssey.2022-12⟩
Odyssey 2022 – The Speaker and Language Recognition Workshop
Odyssey 2022 – The Speaker and Language Recognition Workshop, Jun 2022, Beijing, China. pp.85-91, ⟨10.21437/Odyssey.2022-12⟩
In this paper, we initiate the concern of enhancing the spoofing robustness of the automatic speaker verification (ASV) system, without the primary presence of a separate countermeasure module. We start from the standard ASV framework of the ASVspoof
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c2807873c6bd50bb6e492f34fea7b7de
Publikováno v:
ICASSP 2022-IEEE International Conference on Acoustics, Speech and Signal Processing
ICASSP 2022-IEEE International Conference on Acoustics, Speech and Signal Processing, May 2022, Singapore, Singapore. ⟨10.1109/ICASSP43922.2022.9747185⟩
ICASSP 2022-IEEE International Conference on Acoustics, Speech and Signal Processing, May 2022, Singapore, Singapore. ⟨10.1109/ICASSP43922.2022.9747185⟩
In this study, we focus on nonlinear compression methods in spectral features for speaker verification based on deep neural network. We consider different kinds of channel-dependent (CD) nonlinear compression methods optimized in a data-driven manner
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::21a590bf652e39939e85560d36eda9e9
Autor:
Kong Aik Lee, Massimiliano Todisco, Héctor Delgado, Xin Wang, Tomi Kinnunen, Ville Vestman, Nicholas Evans, Douglas A. Reynolds, Sahidullah, Junichi Yamagishi, Andreas Nautsch
Publikováno v:
IEEE/ACM Transactions on Audio, Speech and Language Processing
IEEE/ACM Transactions on Audio, Speech and Language Processing, Institute of Electrical and Electronics Engineers, 2020, IEEE/ACM Transactions on Audio, Speech, and Language Processing, 28, pp.2195-2210. ⟨10.1109/TASLP.2020.3009494⟩
IEEE/ACM Transactions on Audio, Speech and Language Processing, 2020, IEEE/ACM Transactions on Audio, Speech, and Language Processing, 28, pp.2195-2210. ⟨10.1109/TASLP.2020.3009494⟩
IEEE/ACM Transactions on Audio, Speech and Language Processing, Institute of Electrical and Electronics Engineers, 2020, IEEE/ACM Transactions on Audio, Speech, and Language Processing, 28, pp.2195-2210. ⟨10.1109/TASLP.2020.3009494⟩
IEEE/ACM Transactions on Audio, Speech and Language Processing, 2020, IEEE/ACM Transactions on Audio, Speech, and Language Processing, 28, pp.2195-2210. ⟨10.1109/TASLP.2020.3009494⟩
Recent years have seen growing efforts to develop spoofing countermeasures (CMs) to protect automatic speaker verification (ASV) systems from being deceived by manipulated or artificial inputs. The reliability of spoofing CMs is typically gauged usin
Autor:
Tomi Kinnunen, Akihiro Kato
Publikováno v:
IEEE/ACM Transactions on Audio, Speech, and Language Processing. 27:2336-2349
The fundamental frequency (F0) in a speech signal, which corresponds to pitch, is one of the key features involved in a variety of speech processing tasks. Therefore, accurate F0 estimation has remained an important problem to be solved over decades.