Subject: [AUDITORY] SUBMISSION DEADLINE EXTENDED: CSL Special issue on Advances in Automatic Speaker Verification Anti-spoofing From: Md Sahidullah <sahidullahmd@xxxxxxxx> Date: Thu, 3 Oct 2019 10:47:49 +0200 List-Archive:<http://lists.mcgill.ca/scripts/wa.exe?LIST=AUDITORY>--00000000000094fecf0593fda461 Content-Type: text/plain; charset="UTF-8" [Apologies for possible cross-posting] Deadline for paper submission is extended to October 30, 2019 Computer Speech and Language Special issue on Advances in Automatic Speaker Verification Anti-spoofing ( https://www.journals.elsevier.com/computer-speech-and-language/call-for-papers/advances-in-automatic-speaker ) The performance of voice biometrics systems based on automatic speaker verification (ASV) technology degrades significantly in the presence of spoofing attacks. Over the past few years considerable progress has been made in the field of ASV anti-spoofing. This includes the development of new speech corpora, common evaluation protocols and advancements in front-end feature extraction and back-end classifiers. The ASVspoof initiative was launched to promote the development of countermeasures which aim to protect ASV from spoofing attacks. ASVspoof 2015, the first edition, focused on the detection of synthetic speech created with voice conversion (VC) and text-to-speech (TTS) methods. The second edition, ASVspoof 2017, focused on the detection of replayed speech. ASVspoof 2019, the latest edition included two sub-challenges geared towards "logical access" (LA) and "physical access" (PA) scenarios. The LA scenario relates to the detection of synthetic speech created with advanced VC and TTS methods developed by academic and non-academic organizations. The PA scenario promotes the develop of countermeasures for the detection of replayed speech signals. More than 60 academic and industrial teams participated in the ASVspoof 2019 challenge. Preliminary results indicate considerable performance improvements in terms of two evaluation metrics adopted for the challenge. The top-ranking teams applied different machine learning algorithms suitable for the discrimination of natural and spoofed speech. This special issue will feature articles describing top-performing techniques and detailed analyses of some of the systems reported in recent years by leading anti-spoofing researchers. The special issue will also consist of an overview article which covers ASVspoof 2019 challenge results, and meta analyses. The scope of the special issue is, however, not limited to work performed using the ASVspoof challenge datasets; studies conducted with other datasets are also welcome. Please contact at info@xxxxxxxx if you have any questions about the relevance of your work for this special issue. Topics of interest include (but are not limited to): -Speaker verification anti-spoofing on ASVspoof 2019 -Datasets for speaker verification anti-spoofing -Deep learning for spoofing and anti-spoofing -Joint evaluation of countermeasures and speaker verification -Evaluation methodology for speaker verification anti-spoofing -Voice conversion for spoofing speaker verification systems -Text-to-speech for spoofing speaker verification systems -Robust spoofing countermeasures -Generalized spoofing countermeasures -Audio watermarking for spoofing countermeasures -Acoustic fingerprinting for spoofing countermeasures -Knowledge-based approaches for spoofing countermeasures -Open source toolkit for speaker verification anti-spoofing Important Dates: Submission open: June 1, 2019 Submission deadline: October 30, 2019 Acceptance deadline: March 10, 2020 Publication: April, 2020 Guest Editors: Andreas Nautsch, EURECOM, France Hector Delgado, Nuance Communications, Spain Massimiliano Todisco, EURECOM, France Md Sahidullah, Inria, France Ville Vestman, UEF, Finland Xin Wang, NII, Japan Advisory Committee: Junichi Yamagishi, NII, Japan Kong-Aik Lee, NEC Corp, Japan Nicolas Evans, EURCOM, France Tomi Kinnunen, UEF, Finland -- Md Sahidullah website: *https://sites.google.com/site/iitkgpsahi/ <https://sites.google.com/site/iitkgpsahi/>* --00000000000094fecf0593fda461 Content-Type: text/html; charset="UTF-8" Content-Transfer-Encoding: quoted-printable <div dir=3D"ltr"><div lang=3D"x-unicode" style=3D"font-family:-moz-fixed;fo= nt-size:12px">[Apologies for possible cross-posting]</div><div lang=3D"x-un= icode" style=3D"font-family:-moz-fixed;font-size:12px"><br></div><div lang= =3D"x-unicode" style=3D"font-family:-moz-fixed;font-size:12px"><h2 align=3D= "center" style=3D"text-align:center;margin:10pt 0cm 0.0001pt;line-height:19= .9333px;break-after:avoid;font-size:13pt;font-family:Cambria,serif;color:rg= b(79,129,189)"><span lang=3D"EN-US">Deadline=C2=A0for paper submission is e= xtended to=C2=A0</span><span lang=3D"EN-US">October 30, 2019</span></h2></d= iv><div lang=3D"x-unicode" style=3D"font-family:-moz-fixed;font-size:12px">= <br></div><div lang=3D"x-unicode" style=3D"font-family:-moz-fixed;font-size= :12px"><br>Computer Speech and Language Special issue on Advances in Automa= tic Speaker Verification Anti-spoofing=C2=A0<br>(<a href=3D"https://www.jou= rnals.elsevier.com/computer-speech-and-language/call-for-papers/advances-in= -automatic-speaker" target=3D"_blank">https://www.journals.elsevier.com/com= puter-speech-and-language/call-for-papers/advances-in-automatic-speaker</a>= )=C2=A0<br><br>The performance of voice biometrics systems based on automat= ic speaker verification (ASV) technology degrades significantly in the pres= ence of spoofing attacks. Over the past few years considerable progress has= been made in the field of ASV anti-spoofing. This includes the development= of new speech corpora, common evaluation protocols and advancements in fro= nt-end feature extraction and back-end classifiers. The ASVspoof initiative= was launched to promote the development of countermeasures which aim to pr= otect ASV from spoofing attacks. ASVspoof 2015, the first edition, focused = on the detection of synthetic speech created with voice conversion (VC) and= text-to-speech (TTS) methods. The second edition, ASVspoof 2017, focused o= n the detection of replayed speech.=C2=A0<br><br>ASVspoof 2019, the latest = edition included two sub-challenges geared towards "logical access&quo= t; (LA) and "physical access" (PA) scenarios. The LA scenario rel= ates to the detection of synthetic speech created with advanced VC and TTS = methods developed by academic and non-academic organizations. The PA scenar= io promotes the develop of countermeasures for the detection of replayed sp= eech signals. More than 60 academic and industrial teams participated in th= e ASVspoof 2019 challenge. Preliminary results indicate considerable perfor= mance improvements in terms of two evaluation metrics adopted for the chall= enge. The top-ranking teams applied different machine learning algorithms s= uitable for the discrimination of natural and spoofed speech.=C2=A0<br><br>= This special issue will feature articles describing top-performing techniqu= es and detailed analyses of some of the systems reported in recent years by= leading anti-spoofing researchers. The special issue will also consist of = an overview article which covers ASVspoof 2019 challenge results, and meta = analyses. The scope of the special issue is, however, not limited to work p= erformed using the ASVspoof challenge datasets; studies conducted with othe= r datasets are also welcome.=C2=A0<br><br>Please contact at=C2=A0<a href=3D= "mailto:info@xxxxxxxx" target=3D"_blank">info@xxxxxxxx</a>=C2=A0if = you have any questions about the relevance of your work for this special is= sue.=C2=A0<br><br>Topics of interest include (but are not limited to):=C2= =A0<br><br>-Speaker verification anti-spoofing on ASVspoof 2019=C2=A0<br>-D= atasets for speaker verification anti-spoofing=C2=A0<br>-Deep learning for = spoofing and anti-spoofing=C2=A0<br>-Joint evaluation of countermeasures an= d speaker verification=C2=A0<br>-Evaluation methodology for speaker verific= ation anti-spoofing=C2=A0<br>-Voice conversion for spoofing speaker verific= ation systems=C2=A0<br>-Text-to-speech for spoofing speaker verification sy= stems=C2=A0<br>-Robust spoofing countermeasures=C2=A0<br>-Generalized spoof= ing countermeasures=C2=A0<br>-Audio watermarking for spoofing countermeasur= es=C2=A0<br>-Acoustic fingerprinting for spoofing countermeasures=C2=A0<br>= -Knowledge-based approaches for spoofing countermeasures=C2=A0<br>-Open sou= rce toolkit for speaker verification anti-spoofing=C2=A0<br><br>Important D= ates:=C2=A0<br><br>Submission open: June 1, 2019=C2=A0<br>Submission=C2=A0d= eadline: October 30, 2019=C2=A0<br>Acceptance=C2=A0deadline: March 10, 2020= =C2=A0<br>Publication: April, 2020<br><br>Guest Editors:=C2=A0<br><br>Andre= as Nautsch, EURECOM, France=C2=A0<br>Hector Delgado, Nuance Communications,= Spain=C2=A0<br>Massimiliano Todisco, EURECOM, France=C2=A0<br>Md Sahidulla= h, Inria, France=C2=A0<br>Ville Vestman, UEF, Finland=C2=A0<br>Xin Wang, NI= I, Japan=C2=A0<br><br>Advisory Committee:=C2=A0<br><br>Junichi Yamagishi, N= II, Japan=C2=A0<br>Kong-Aik Lee, NEC Corp, Japan=C2=A0<br>Nicolas Evans, EU= RCOM, France=C2=A0<br>Tomi Kinnunen, UEF, Finland</div><div><br></div>-- <b= r><div dir=3D"ltr" class=3D"gmail_signature" data-smartmail=3D"gmail_signat= ure"><div dir=3D"ltr"><div><div dir=3D"ltr"><div><div dir=3D"ltr"><div><div= dir=3D"ltr"><div dir=3D"ltr"><div dir=3D"ltr"><div dir=3D"ltr"><font face= =3D"comic sans ms, sans-serif" size=3D"2" color=3D"#000000">Md Sahidullah</= font><div><font face=3D"comic sans ms, sans-serif" size=3D"2" color=3D"#000= 000">website:=C2=A0</font><font color=3D"#0000ee" face=3D"comic sans ms, sa= ns-serif" size=3D"2"><u><a href=3D"https://sites.google.com/site/iitkgpsahi= /" target=3D"_blank">https://sites.google.com/site/iitkgpsahi/</a></u></fon= t></div></div></div></div></div></div></div></div></div></div></div></div><= /div> --00000000000094fecf0593fda461--