Subject: [AUDITORY] [CfP] Clarity-2021 - ISCA Workshop on Machine Learning Challenges for Hearing Aids From: Jon Barker <j.p.barker@xxxxxxxx> Date: Tue, 20 Apr 2021 18:23:16 +0100--00000000000051f1d205c06ab4a7 Content-Type: text/plain; charset="UTF-8" Content-Transfer-Encoding: quoted-printable -- Apologies for cross-listing -- -- Please forward to other interested colleagues -- =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D= =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D= =3D=3D=3D 2021 ISCA Workshop on Machine Learning Challenges for Hearing Aids (Clarity-2021) Online Event, 17th September, 2021 claritychallenge.github.io/clarity2021-workshop/ =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D= =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D= =3D=3D=3D IMPORTANT DATES 15th June, 2021 - Clarity Challenge and Workshop paper submission deadline 1st July, 2021 - Workshop registration opens 2nd August, 2021 - Paper acceptance notification to authors 17th September - Workshop / Clarity Challenge results announced 17th October, 2021 - Final Challenge paper submission (2 to 6 pages) One of the biggest challenges for hearing-impaired listeners is understanding speech in the presence of background noise. Everyday social noise levels can have a devastating impact on speech intelligibility. Inability to communicate effectively can lead to social withdrawal and isolation. Disabling hearing impairment affects 360 million people worldwide, with that number increasing because of the ageing population. Unfortunately, current hearing aid technology is often ineffective in noisy situations. Although amplification can restore audibility, it does not compensate fully for the effects of hearing loss. The aim of this one-day virtual workshop is to report on the Clarity Enhancement Challenge, the first-ever machine learning challenge targeted at helping those with a hearing impairment. The challenge was launched at the start of 2021, and is seeking to find new approaches to signal processing in hearing aids. (For details of the challenge please visit the Clarity Challenge website.) The Clarity-2021 workshop will be focused on presenting the 1st Clarity Enhancement Challenge, but is also open to relevant non-challenge papers. Relevant research topics include (but are not limited to) - Models of speech intelligibility and quality for normal and hearing impaired listeners - Applications of auditory scene analysis - Binaural technology for speech enhancement and source separation - Multi-microphone processing technology - Real-time approaches to speech enhancement - Statistical model-driven approaches to hearing aid processing - Audio quality & intelligibility assessment hearing aid and cochlear implant users - Efficient and effective integration of psychoacoustic testing in machine learning - Machine learning for diverse target listeners - Machine learning models of hearing impairment For further workshop information please visit the workshop website ( https://claritychallenge.github.io/clarity2021-workshop). For information on the Clarity Challenge visit the Clarity project page ( http://claritychallenge.org) *Organisers* The Clarity Project Team Prof Michael Akeroyd, University of Nottingham Prof Jon Barker, University of Sheffield Prof Trevor Cox, University of Salford Prof John Culling, University of Cardiff Dr Simone Graetzer, University of Salford Prof Graham Naylor, University of Nottingham Eszter Porter, University of Nottingham Dr Rhoddy Viveros Mu=C3=B1oz, University of Cardiff --00000000000051f1d205c06ab4a7 Content-Type: text/html; charset="UTF-8" Content-Transfer-Encoding: quoted-printable <div dir=3D"ltr">-- Apologies for cross-listing --<br>-- Please forward to = other interested colleagues --<br><br>=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D= =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D= =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D<br><br>2021 ISCA Workshop = on Machine Learning Challenges for Hearing Aids (Clarity-2021)<br>Online Ev= ent, 17th September, 2021<br><a href=3D"http://claritychallenge.github.io/c= larity2021-workshop/">claritychallenge.github.io/clarity2021-workshop/</a><= br><br>=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D= =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D= =3D=3D=3D=3D=3D=3D<br><br>IMPORTANT DATES<br><br>15th June, 2021 - Clarity = Challenge and Workshop paper submission deadline<br>1st July, 2021 - Worksh= op registration opens<br>2nd August, 2021 - Paper acceptance notification t= o authors =C2=A0<br>17th September - Workshop / Clarity Challenge results a= nnounced<br>17th October, 2021 - Final Challenge paper submission (2 to 6 p= ages)<br><br>One of the biggest challenges for hearing-impaired listeners i= s understanding speech in the presence of background noise. Everyday social= noise levels can have a devastating impact on speech intelligibility. Inab= ility to communicate effectively can lead to social withdrawal and isolatio= n. Disabling hearing impairment affects 360 million people worldwide, with = that number increasing because of the ageing population. Unfortunately, cur= rent hearing aid technology is often ineffective in noisy situations. Altho= ugh amplification can restore audibility, it does not compensate fully for = the effects of hearing loss.<br><br>The aim of this one-day virtual worksho= p is to report on the Clarity Enhancement Challenge, the first-ever machine= learning challenge targeted at helping those with a hearing impairment. Th= e challenge was launched at the start of 2021, and is seeking to find new a= pproaches to signal processing in hearing aids. (For details of the challen= ge please visit the Clarity Challenge website.)<br><br>The Clarity-2021 wor= kshop will be focused on presenting the 1st Clarity Enhancement Challenge, = but is also open to relevant non-challenge papers. Relevant research topics= include (but are not limited to)<br><br>- Models of speech intelligibility= and quality for normal and hearing impaired listeners<br>- Applications of= auditory scene analysis<br>- Binaural technology for speech enhancement an= d source separation<br>- Multi-microphone processing technology<br>- Real-t= ime approaches to speech enhancement<br>- Statistical model-driven approach= es to hearing aid processing<br>- Audio quality & intelligibility asses= sment hearing aid and cochlear implant users<br>- Efficient and effective i= ntegration of psychoacoustic testing in machine learning<br>- Machine learn= ing for diverse target listeners<br>- Machine learning models of hearing im= pairment<br><br>For further workshop information please visit the workshop = website (<a href=3D"https://claritychallenge.github.io/clarity2021-workshop= ">https://claritychallenge.github.io/clarity2021-workshop</a>). For informa= tion on the Clarity Challenge visit the Clarity project page (<a href=3D"ht= tp://claritychallenge.org">http://claritychallenge.org</a>)<br><br><b>Organ= isers<br></b><br>The Clarity Project Team<br>Prof Michael Akeroyd, Universi= ty of Nottingham<br>Prof Jon Barker, =C2=A0University of Sheffield<br>Prof = Trevor Cox, University of Salford<br>Prof John Culling, =C2=A0University of= Cardiff<br>Dr Simone Graetzer, University of Salford<br>Prof Graham Naylor= , University of Nottingham<br>Eszter Porter, University of Nottingham<br>Dr= Rhoddy Viveros Mu=C3=B1oz, University of Cardiff<br><br><div><br></div><di= v dir=3D"ltr" class=3D"gmail_signature" data-smartmail=3D"gmail_signature">= <div dir=3D"ltr"><div><div dir=3D"ltr"><div><div><br></div></div></div></di= v></div></div></div> --00000000000051f1d205c06ab4a7--