Subject: [AUDITORY] ISCA Workshop on Machine Learning Challenges for Hearing Aids (Clarity-2021) - Registration open From: Jon Barker <j.p.barker@xxxxxxxx> Date: Fri, 30 Jul 2021 09:56:51 +0100--000000000000309dbe05c85367c8 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=3D=3D=3D=3D=3D 1st ISCA Workshop on Machine Learning Challenges for Hearing Aids (Clarity-2021) Online Event, 16th/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=3D=3D=3D=3D=3D For programme details and registration please visit the workshop website https://claritychallenge.github.io/clarity2021-workshop/ *IMPORTANT DATES* 16th September - Workshop tutorial session 17th September - Workshop / Clarity Challenge results announced 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 two-day virtual event 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.) *Invited Talks* - Christine Evers, University of Southampton - Barry M. Gibbs, University of Liverpool - James Kates, University of Colorado - Karolina Smeds, ORCA Europe *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 --=20 Professor Jon Barker, Department of Computer Science, University of Sheffield +44 (0) 114 222 1824 --000000000000309dbe05c85367c8 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><div><br></div><div>=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=3D=3D=3D=3D= =3D<br><br>1st ISCA Workshop on Machine Learning Challenges for Hearing Aid= s (Clarity-2021)<br>Online Event, 16th/17th September, 2021<br><a href=3D"h= ttp://claritychallenge.github.io/clarity2021-workshop/">claritychallenge.gi= thub.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=3D=3D=3D=3D=3D<br><br>F= or programme details and registration please visit the workshop website<br>= <br><a href=3D"https://claritychallenge.github.io/clarity2021-workshop/">ht= tps://claritychallenge.github.io/clarity2021-workshop/</a><br><br><b>IMPORT= ANT DATES<br></b><br>16th September - Workshop tutorial session<br>17th Sep= tember - Workshop / Clarity Challenge results announced<br><br>One of the b= iggest 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 effe= ctively can lead to social withdrawal and isolation. Disabling hearing impa= irment affects 360 million people worldwide, with that number increasing be= cause of the ageing population. Unfortunately, current hearing aid technolo= gy is often ineffective in noisy situations. Although amplification can res= tore audibility, it does not compensate fully for the effects of hearing lo= ss.<br><br>The aim of this two-day virtual event is to report on the Clarit= y 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 processi= ng in hearing aids. (For details of the challenge please visit the Clarity = Challenge website.)<br><br><b>Invited Talks<br></b><br>- Christine Evers, U= niversity of Southampton<br>- Barry M. Gibbs, University of Liverpool<br>- = James Kates, University of Colorado<br>- Karolina Smeds, ORCA Europe<br><br= ><b>Organisers<br></b><br>The Clarity Project Team<br>Prof Michael Akeroyd,= University of Nottingham<br>Prof Jon Barker, =C2=A0University of Sheffield= <br>Prof Trevor Cox, University of Salford<br>Prof John Culling, =C2=A0Univ= ersity of Cardiff<br>Dr Simone Graetzer, University of Salford<br>Prof Grah= am Naylor, University of Nottingham<br>Eszter Porter, University of Notting= ham<br>Dr Rhoddy Viveros Mu=C3=B1oz, University of Cardiff<br><br></div>-- = <br><div dir=3D"ltr" class=3D"gmail_signature" data-smartmail=3D"gmail_sign= ature"><div dir=3D"ltr"><div><div dir=3D"ltr">Professor Jon Barker,<div><di= v>Department of Computer Science,</div><div>University of Sheffield</div><d= iv>+44 (0) 114 222 1824</div><div><br></div></div></div></div></div></div><= /div> --000000000000309dbe05c85367c8--