Amul&’modaltrainingapproach · PDF fileIntroduc&on" •...

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A mul&modal training approach to improve cochlear implant users' ability to handle simultaneous talk Amy Beeston and Emina Kur&ć Mul&modality in Language Research Leeds 26 June 2014

Transcript of Amul&’modaltrainingapproach · PDF fileIntroduc&on" •...

A  mul&-­‐modal  training  approach    to  improve  cochlear  implant  users'  ability  to  handle  simultaneous  talk  

Amy  Beeston  and  Emina  Kur&ć  Mul&modality  in  Language  Research  

Leeds  ·∙  26  June  2014  

University  of  Sheffield  •   Prof  Bill  Wells,  Human  Communica&on  Sciences  •   Prof  Guy  Brown,  Computer  Science  •   Dr  Emina  Kur&ć  and  Amy  Beeston,  Research  Associates,  Computer  Science  •   Ella  Page,  project  student,  Human  Communica&on  Sciences    Sheffield  Teaching  Hospitals  NHS  Trust  •   Dr  Harriet  Crook,  Clinical  Scien&st,  Neurotology  •   Erica  Bradley,  Speech  &  Language  Therapist,  Neurotology    Cochlear  implant  (CI)  user  panel  •   5  cochlear-­‐implanted  par&cipants  recruited  from  Sheffield  Cochlear  Implant  Service  

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Mul&modality  in  language  research  26  June  2014  ·∙  Leeds  ·∙  Amy  Beeston  and  Emina  Kur&ć  

Introduc&on  

•  Losing  your  hearing  is  not  simply  the  absence  of  sound  –  for  individual:  loss  of  capacity  to  take  part  in  social  life  –  addi&onal  societal  s&gma:  being  treated  differently*  

•  Cochlear  implanta&on  is  not  a  cure  for  deafness  –  it  is  a  prosthe&c  subs&tute.  

•  Approx  324,200  people  worldwide  implanted  by  end  of  2012†  –  10,000  cases  in  UK†  –  c.  113  per  month  in  UK‡  

•  Insufficient  evidence/training  materials  to  guide  clinicians  to  help  cochlear  implant  (CI)  users  deal  with  simultaneous  talk.  

Mul&modality  in  language  research  26  June  2014  ·∙  Leeds  ·∙  Amy  Beeston  and  Emina  Kur&ć  

*  Lamb  and  Archibold  (2013),  Adult  Cochlear  Implanta&on:  Evidence  and  experience.  Tech  rep,  The  Ear  Founda&on.  †  NIH  Publica&on  No.  11-­‐4798  (2013-­‐11-­‐01).  ‡  Bri&sh  Cochlear  Implant  Group,  Annual  Update  on  UK  Cochlear  Implant  Provision  (2011-­‐2012).  

Electric  hearing  

Mul&modality  in  language  research  26  June  2014  ·∙  Leeds  ·∙  Amy  Beeston  and  Emina  Kur&ć  

www.mrc-­‐cbu.cam.ac.uk  

•  Acous&cal  vibra&ons  are  delivered  to  brain  as  electrical  signals  

Challenges  for  CI  users  

•  Cochlear  implant  (CI)  users  need  op&mum  conversa&onal  sejngs  (quiet,  one  partner,  awareness  to  avoid  overlap).  

•  Q:  “When  no  background  noise  is  present,  can  you  effortlessly  par&cipate  in  conversa&ons  with  friends  or  family  members  (e.g.,  aner  dinner)?”  

Mul&modality  in  language  research  26  June  2014  ·∙  Leeds  ·∙  Amy  Beeston  and  Emina  Kur&ć  

•  Mean  response  for  26  adults  =  5.7  

MED-­‐EL  Hearing  Implant  Sound  Quality  Index  (HISQUI)  v23015_2.0,  English.  

always  never  

“almost  always”  

“frequently”  

Challenges  for  CI  users  

•  Q:  “When  mul&ple  people  are  talking  simultaneously,  can  you  effortlessly  follow  discussions  of  friends  and  family  members?”  

Mul&modality  in  language  research  26  June  2014  ·∙  Leeds  ·∙  Amy  Beeston  and  Emina  Kur&ć  

MED-­‐EL  Hearing  Implant  Sound  Quality  Index  (HISQUI)  v23015_2.0,  English.  

•  Mean  response  for  26  adults  =  2.8  •  Unfamiliar  voices  are  s&ll  more  difficult  to  follow  •  Limits  of  the  device?  Conversa&onal/social  experience?  

always  never  

“occasionally”  “rarely”  

Social  signals  and  behaviours  

•  Mul&ple  behavioural  cues  combine  to  produce  a  social  signal  

Mul&modality  in  language  research  26  June  2014  ·∙  Leeds  ·∙  Amy  Beeston  and  Emina  Kur&ć  

Vinciarelli  et  al.  (2009).  Social  signal  processing:  Survey  of  an  emerging  domain.  Image  and  Vision  Compu&ng  27,  1743–1759.  

–  Physical  appearance  –  Gesture  and  posture  –  Face/eyes  behaviour  –  Space  and  environment  –  Linguis'c  content  –  Vocal  behaviour  *  

*  prosodic  features,    e.g.,  pitch,  loudness,  dura&on,  silence,  …  

•  Stronger  reliance  for  CI  users  on  non-­‐auditory  cues?  •  Is  vocal  non-­‐verbal  behaviour  informa&ve  or  distrac&ng?  

CI  sound  encoding  

•  22  electrodes  vs.  30,000  hair  cells.  •  Low  spectral  resolu&on:  hard  to  dis&nguish  one  talker  from  

another  (especially  concurrent  talkers).  •  Poor  representa&on  of  voice  F0:  hard  to  iden&fy  social  ac&ons  

realised  by  prosodic  cues  (e.g.,  turn  compe&&on).  

Mul&modality  in  language  research  26  June  2014  ·∙  Leeds  ·∙  Amy  Beeston  and  Emina  Kur&ć  

www.cochlear.com  

Scene  analysis  problem  

Mul&modality  in  language  research  26  June  2014  ·∙  Leeds  ·∙  Amy  Beeston  and  Emina  Kur&ć  

•  Parse  single-­‐channel  stream  without  cues  from  pitch  or  loca&on  

Kur&ć  et  al.  (2012).  A  corpus  of  spontaneous  mul&-­‐party  conversa&on  in  Bosnian  Serbo-­‐Croa&an  and  Bri&sh  English.  Proc.  LREC,  Istanbul.  

Conversa&onal  dataset  

Mul&modality  in  language  research  26  June  2014  ·∙  Leeds  ·∙  Amy  Beeston  and  Emina  Kur&ć  

•  3  hours  of  informal  talk,  na&ve  English  (UK)  

•  16%  of  total  talk  &me  is  overlapping  talk  

•  41%  of  speaker  turns  are  overlapped  by  another  speaker  

Kur&ć  et  al.  (2012).  A  corpus  of  spontaneous  mul&-­‐party  conversa&on  in  Bosnian  Serbo-­‐Croa&an  and  Bri&sh  English.  Proc.  LREC,  Istanbul.  

•  Lip-­‐reading  impossible;  Gaze,  gesture,  posture,  …  •  Segmenta&on  by  turn  construc&on  unit  (TCU),  transcrip&on,  

overlap  compe&&veness,  xml  data  in  ELAN  annota&on  format  

CI-­‐user  feedback  

Mul&modality  in  language  research  26  June  2014  ·∙  Leeds  ·∙  Amy  Beeston  and  Emina  Kur&ć  

•  Web-­‐based  ques&onnaire  –  hearing  conversa&ons  –  taking  part  in  conversa&ons  –  age,  gender,  and  hearing  status  (implant  type)  per  ear  

 •  CI-­‐user  panel  

–  5  expert  CI-­‐users  recruited  for  dura&on  of  project  –  conversa&onal  experiences,  awareness  of  overlap  –  grading  speech  material  –  grading  user  tasks  –  evaluate  training  sonware        –  listening  skills      –  (later,  speaking  skills)  

 

Listening  skill  development  

•  Objec&ve  –  Understand  mul&-­‐party  conversa&on  •  Visualisa&on  of  acous&c  informa&on  •  CI-­‐user  difficulty  ra&ngs  for  speech  material  and  tasks  

Mul&modality  in  language  research  26  June  2014  ·∙  Leeds  ·∙  Amy  Beeston  and  Emina  Kur&ć  

Reported  difficul&es  –  iden&fy  talker  –  recognise  speech  –  understand  ac&on  

i.  Speech  material  

•  Graded  exposure  to  mul&-­‐party  conversa&on  –  Incremental  learning  through  repe&&on  

•  Classify  by  number/gender  of  talkers,  turn  transi&ons  

Mul&modality  in  language  research  26  June  2014  ·∙  Leeds  ·∙  Amy  Beeston  and  Emina  Kur&ć  

ii.  User  tasks  

•  Widen  conversa&onal  experience  –  Rate  difficulty  for  CI  user  

•  Focus  on  non-­‐linguis&c  aspects  –  iden&fy  number  of  talkers  –  iden&fy  same/different  gender  –  iden&fy  clear/overlap  

Mul&modality  in  language  research  26  June  2014  ·∙  Leeds  ·∙  Amy  Beeston  and  Emina  Kur&ć  

N  G  T  speech  collec'on          0  0  0  1  talker                  1  0  0  2  talkers,  same  gender,  clear    1  0  1  2  talkers,  same  gender,  overlap    1  1  0  2  talkers,  diff.  gender,  clear    1  1  1  2  talkers,  diff.  gender,  overlap    

Number  of  talkers,  N    (single  =  0,  mul&ple  =  1)  

Gender,  G    (same  =  0,  different  =  1)  

Turn  exchange,  T    (clear  =  0,  in  overlap  =  1)  

(0,  0,  0)  T   G  

E  

Speaking  skill  development  

Mul&modality  in  language  research  26  June  2014  ·∙  Leeds  ·∙  Amy  Beeston  and  Emina  Kur&ć  

•  Objec&ve:  par&cipate  in  mul&-­‐party  conversa&on  •  1.  gather  voice  norms  (pitch,  intensity,  tempo)  •  2.  use  overlaps  appropriately  

–  Iden&fy  entry  &mes  (especially  in  overlap)  –  Control  pitch/loudness  (show  compe&&veness)  

Conclusions  and  further  work  

Mul&modality  in  language  research  26  June  2014  ·∙  Leeds  ·∙  Amy  Beeston  and  Emina  Kur&ć  

•  Some  CI-­‐users  keen  to  develop  mul&-­‐party  conversa&onal  skills  –  varied  popula&on  –  different  experiences/strategies  

•  Informal  talk  is  extremely  challenging  –  missing  some  turn-­‐taking  cues  –  mul&modal  presenta&on  of  acous&c  cues  

•  Learning  interac&onal  strategies  for  handling  overlapping  talk  –  complement  technological  advances  –  increase  social  par&cipa&on  

•  Sonware  may  be  more  widely  relevant  –  hearing  or  communica&ve  difficul&es  

Thank  you  for  your  ayen&on  

•  Any  ques&ons?  

Mul&modality  in  language  research  26  June  2014  ·∙  Leeds  ·∙  Amy  Beeston  and  Emina  Kur&ć