Developing a Conversation Assistant for the Hearing Impaired Using Automatic Speech Recognition

I Abstract (in Finnish) IIin Finnish) II

[1]  Roger K. Furness,et al.  Ambisonics-An Overview , 1990 .

[2]  Joseph F. Dumas,et al.  A Practical Guide to Usability Testing , 1993 .

[3]  Debora Shaw,et al.  Handbook of usability testing: How to plan, design, and conduct effective tests , 1996 .

[4]  Toomas Altosaar,et al.  Applications for the hearing-impaired: evaluation of finnish phoneme recognition methods , 1997, EUROSPEECH.

[5]  Jakob Nielsen,et al.  Usability engineering , 1997, The Computer Science and Engineering Handbook.

[6]  Methods for the subjective assessment of small impairments in audio systems , 2015 .

[7]  Maria Ebling,et al.  On the contributions of different empirical data in usability testing , 2000, DIS '00.

[8]  Alex Acero,et al.  Spoken Language Processing: A Guide to Theory, Algorithm and System Development , 2001 .

[9]  R. Shannon,et al.  Speech recognition in noise as a function of the number of spectral channels: comparison of acoustic hearing and cochlear implants. , 2001, The Journal of the Acoustical Society of America.

[10]  Krzysztof Marasek,et al.  SPEECON – Speech Databases for Consumer Devices: Database Specification and Validation , 2002, LREC.

[11]  I. Stewart,et al.  The application of voice recognition technology to the development and presentation of complex engineering terminology to hearing impaired students , 2003 .

[12]  Ye-Yi Wang,et al.  Is word error rate a good indicator for spoken language understanding accuracy , 2003, 2003 IEEE Workshop on Automatic Speech Recognition and Understanding (IEEE Cat. No.03EX721).

[13]  Constantine Stephanidis,et al.  Unified user interface design: designing universally accessible interactions , 2004, Interact. Comput..

[14]  Qian-Jie Fu,et al.  Noise Susceptibility of Cochlear Implant Users: The Role of Spectral Resolution and Smearing , 2005, Journal of the Association for Research in Otolaryngology.

[15]  Dzmitry Aliakseyeu,et al.  Transcription Table: Text Support During Meetings , 2005, INTERACT.

[16]  Ebru Arisoy,et al.  Unlimited vocabulary speech recognition for agglutinative languages , 2006, NAACL.

[17]  Paula C. Stacey,et al.  Hearing-Impaired Children in the United Kingdom, I: Auditory Performance, Communication Skills, Educational Achievements, Quality of Life, and Cochlear Implantation , 2006, Ear and hearing.

[18]  Ville Pulkki Directional Audio Coding in Spatial Sound Reproduction and Stereo Upmixing , 2006 .

[19]  Mikko Kurimo,et al.  Unlimited vocabulary speech recognition with morph language models applied to Finnish , 2006, Comput. Speech Lang..

[20]  Tara Matthews,et al.  Scribe4Me: Evaluating a Mobile Sound Transcription Tool for the Deaf , 2006, UbiComp.

[21]  Thomas Way,et al.  Inclusion of deaf students in computer science classes using real-time speech transcription , 2007, ITiCSE '07.

[22]  Harry Levitt,et al.  A Historical Perspective on Digital Hearing Aids: How Digital Technology Has Changed Modern Hearing Aids , 2007, Trends in amplification.

[23]  Mark J. F. Gales,et al.  The Application of Hidden Markov Models in Speech Recognition , 2007, Found. Trends Signal Process..

[24]  Richard E. Ladner,et al.  Hearing Impairments , 2008, Web Accessibility.

[25]  Mikko Kurimo,et al.  Statistical Language Modeling for Automatic Speech Recognition of Agglutinative Languages , 2008 .

[26]  Mehryar Mohri,et al.  Speech Recognition with Weighted Finite-State Transducers , 2008 .

[27]  M. Furst,et al.  The benefit of speech enhancement to the hearing impaired , 2008, 2008 IEEE 25th Convention of Electrical and Electronics Engineers in Israel.

[28]  Mikko Kurimo,et al.  Importance of High-Order N-Gram Models in Morph-Based Speech Recognition , 2009, IEEE Transactions on Audio, Speech, and Language Processing.

[29]  Judy van Biljon,et al.  Usability evaluation methods: mind the gaps , 2009, SAICSIT '09.

[30]  Patricia Andrade Pereira,et al.  Communication and Information Barriers to Health Assistance for Deaf Patients , 2010 .

[31]  Wu xiao fen,et al.  Using speech recognition technology to support education for deaf students , 2010, 2010 2nd IEEE International Conference on Information Management and Engineering.

[32]  Ma Jun,et al.  The Exploration of the Strategies and Skills of Effective Use of Voice Recognition Software in the Classroom for Deaf Students , 2010, 2010 Second International Conference on Future Networks.

[33]  Kukka-Maaria Blomberg,et al.  SISÄKORVAISTUTETTA KÄYTTÄVIEN AIKUISTEN ELÄMÄNLAATU , 2010 .

[34]  Mikko Kurimo,et al.  Comparison of noise robust methods in large vocabulary speech recognition , 2010, 2010 18th European Signal Processing Conference.

[35]  David B Pisoni,et al.  Cochlear implants and spoken language processing abilities: review and assessment of the literature. , 2010, Restorative neurology and neuroscience.

[36]  Daniel Povey,et al.  The Kaldi Speech Recognition Toolkit , 2011 .

[37]  Makoto J. Hirayama A communication aid for hearing impaired persons using mobile smart phones , 2011, International Conference on Mobile IT Convergence.

[38]  Javier Jimenez,et al.  Tablet PC and Head Mounted Display for live closed captioning in education , 2011, 2011 IEEE International Conference on Consumer Electronics (ICCE).

[39]  Luigi Ferrucci,et al.  Hearing loss prevalence in the United States. , 2011, Archives of internal medicine.

[40]  Seyed Ghorshi,et al.  Combining Augmented Reality and Speech Technologies to Help Deaf and Hard of Hearing People , 2012, 2012 14th Symposium on Virtual and Augmented Reality.

[41]  Kaarel Kaljurand,et al.  Open and extendable speech recognition application architecture for mobile environments , 2012, SLTU.

[42]  Tara N. Sainath,et al.  Deep Neural Networks for Acoustic Modeling in Speech Recognition: The Shared Views of Four Research Groups , 2012, IEEE Signal Processing Magazine.

[43]  Monica Padilla,et al.  Improving speech perception in noise with current focusing in cochlear implant users , 2013, Hearing Research.

[44]  Rainer Brück,et al.  An assistive technology for hearing-impaired persons: Analysis, requirements and architecture , 2013, 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

[45]  J. Salonen Hearing Impairment and Tinnitus in the Elderly , 2013 .

[46]  Inka Koskela,et al.  Kuulokojeen käyttäjät työelämässä : Monimenetelmäinen tutkimus kuulokojeen käytön esteistä ja edisteistä työelämässä , 2013 .

[47]  Hanseok Ko,et al.  Dialogue enabling speech-to-text user assistive agent with auditory perceptual beamforming for hearing-impaired , 2013, 2013 IEEE International Conference on Consumer Electronics (ICCE).

[48]  Atsushi Nakamura,et al.  Speech Recognition Algorithms Based on Weighted Finite-State Transducers , 2013, Speech Recognition Algorithms Based on Weighted Finite-State Transducers.

[49]  J. Paul Robinson,et al.  Using speech recognition for real-time captioning and lecture transcription in the classroom , 2013, IEEE Transactions on Learning Technologies.

[50]  Mikko Kurimo,et al.  Unsupervised topic adaptation for morph-based speech recognition , 2013, INTERSPEECH.

[51]  Martha A. Sheridan,et al.  Deaf and Hard-of-Hearing People , 2013 .

[52]  Janne Pylkkönen Towards Efficient and Robust Automatic Speech Recognition: Decoding Techniques and Discriminative Training , 2013 .

[53]  B. Moore Cochlear hearing loss : physiological, psychological and technical issues , 2014 .

[54]  Dong Yu,et al.  Automatic Speech Recognition: A Deep Learning Approach , 2014 .

[55]  Tanel Alumäe,et al.  Full-duplex Speech-to-text System for Estonian , 2014, Baltic HLT.

[56]  Sami Keronen Approaching human performance in noise robust automatic speech recognition , 2014 .

[57]  Leigh Ellen Potter,et al.  Design with the deaf: do deaf children need their own approach when designing technology? , 2014, IDC.

[58]  Sanjeev Khudanpur,et al.  Parallel training of DNNs with Natural Gradient and Parameter Averaging , 2014 .

[59]  Yifan Gong,et al.  An Overview of Noise-Robust Automatic Speech Recognition , 2014, IEEE/ACM Transactions on Audio, Speech, and Language Processing.

[60]  Guy Van Camp,et al.  Deafness and Hereditary Hearing Loss Overview , 2014 .

[61]  Tanel Alumäe Recent improvements in Estonian LVCSR , 2014, SLTU.

[62]  Matti Karjalainen,et al.  Communication Acoustics: An Introduction to Speech, Audio and Psychoacoustics , 2015 .

[63]  Susan Hilary Nielsen,et al.  An experience in requirements prototyping with young deaf children , 2015 .

[64]  Raja S. Kushalnagar,et al.  Tracked Speech-To-Text Display: Enhancing Accessibility and Readability of Real-Time Speech-To-Text , 2015, ASSETS.

[65]  Soraia Silva Prietch,et al.  Application Requirements for Deaf Students to use in Inclusive Classrooms , 2015, CLIHC.

[66]  Rainer Brück,et al.  A Pilot Study about the Smartwatch as Assistive Device for Deaf People , 2015, ASSETS.

[67]  Sirpa Riihiaho,et al.  Experiences with usability testing: Effects of thinking aloud and moderator presence , 2015 .

[68]  Wojciech Matusik,et al.  Eye Tracking for Everyone , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[69]  Heikki Kallasjoki Feature Enhancement and Uncertainty Estimation for Recognition of Noisy and Reverberant Speech , 2016 .

[70]  Eric W. Healy,et al.  Difficulty understanding speech in noise by the hearing impaired: Underlying causes and technological solutions , 2016, 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

[71]  Richard E. Ladner,et al.  A Personalizable Mobile Sound Detector App Design for Deaf and Hard-of-Hearing Users , 2016, ASSETS.

[72]  Richard E. Ladner,et al.  Improving Real-Time Captioning Experiences for Deaf and Hard of Hearing Students , 2016, ASSETS.

[73]  Walter S. Lasecki,et al.  The effects of automatic speech recognition quality on human transcription latency , 2016, W4A.

[74]  Ian McGraw,et al.  Personalized speech recognition on mobile devices , 2016, 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[75]  Geoffrey Zweig,et al.  Achieving Human Parity in Conversational Speech Recognition , 2016, ArXiv.

[76]  Xin Yang,et al.  Speech enhancement for hearing-impaired listeners using deep neural networks with auditory-model based features , 2016, 2016 24th European Signal Processing Conference (EUSIPCO).

[77]  Yanmin Qian,et al.  Very Deep Convolutional Neural Networks for Noise Robust Speech Recognition , 2016, IEEE/ACM Transactions on Audio, Speech, and Language Processing.

[78]  Thomas Lunner,et al.  Effects of Hearing Impairment and Hearing Aid Amplification on Listening Effort: A Systematic Review , 2017, Ear and hearing.

[79]  Geoffrey Zweig,et al.  The microsoft 2016 conversational speech recognition system , 2016, 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[80]  Blake S Wilson,et al.  Global hearing health care: new findings and perspectives , 2017, The Lancet.

[81]  Mikko Kurimo,et al.  Improved Subword Modeling for WFST-Based Speech Recognition , 2017, INTERSPEECH.

[82]  Mikko Kurimo,et al.  Automatic Construction of the Finnish Parliament Speech Corpus , 2017, INTERSPEECH.

[83]  J. Karp,et al.  Clonal Expansion of Lgr5-Positive Cells from Mammalian Cochlea and High-Purity Generation of Sensory Hair Cells. , 2017, Cell reports.

[84]  Mikko Kurimo,et al.  Automatic Speech Recognition With Very Large Conversational Finnish and Estonian Vocabularies , 2017, IEEE/ACM Transactions on Audio, Speech, and Language Processing.

[85]  André Mansikkaniemi Continuous Unsupervised Topic Adaptation for Morph-based Speech Recognition , 2017 .