A Smartphone-Based Multi-Functional Hearing Assistive System to Facilitate Speech Recognition in the Classroom

In this paper, we propose a smartphone-based hearing assistive system (termed SmartHear) to facilitate speech recognition for various target users, who could benefit from enhanced listening clarity in the classroom. The SmartHear system consists of transmitter and receiver devices (e.g., smartphone and Bluetooth headset) for voice transmission, and an Android mobile application that controls and connects the different devices via Bluetooth or WiFi technology. The wireless transmission of voice signals between devices overcomes the reverberation and ambient noise effects in the classroom. The main functionalities of SmartHear include: 1) configurable transmitter/receiver assignment, to allow flexible designation of transmitter/receiver roles; 2) advanced noise-reduction techniques; 3) audio recording; and 4) voice-to-text conversion, to give students visual text aid. All the functions are implemented as a mobile application with an easy-to-navigate user interface. Experiments show the effectiveness of the noise-reduction schemes at low signal-to-noise ratios in terms of standard speech perception and quality indices, and show the effectiveness of SmartHear in maintaining voice-to-text conversion accuracy regardless of the distance between the speaker and listener. Future applications of SmartHear are also discussed.

[1]  Deborah Viviane Ferrari,et al.  Development and Technical Validation of the Mobile Based Assistive Listening System: A Smartphone-Based Remote Microphone. , 2016, American journal of audiology.

[2]  Michael S. Stinson Current and Future Technologies in the Education of Deaf Students , 2010 .

[3]  W. G. Gardner,et al.  HRTF measurements of a KEMAR , 1995 .

[4]  Morton Ann Gernsbacher,et al.  Video Captions Benefit Everyone , 2015, Policy insights from the behavioral and brain sciences.

[5]  Li-Rong Dai,et al.  A Regression Approach to Speech Enhancement Based on Deep Neural Networks , 2015, IEEE/ACM Transactions on Audio, Speech, and Language Processing.

[6]  Erin C Schafer,et al.  Personal FM systems for children with autism spectrum disorders (ASD) and/or attention-deficit hyperactivity disorder (ADHD): an initial investigation. , 2013, Journal of communication disorders.

[7]  Jason Warren,et al.  Long-term use benefits of personal frequency-modulated systems for speech in noise perception in patients with stroke with auditory processing deficits: a non-randomised controlled trial study , 2017, BMJ Open.

[8]  Karen A Doherty,et al.  Age-Related Changes in Listening Effort for Various Types of Masker Noises , 2013, Ear and hearing.

[9]  Jean-Pierre Gagné,et al.  Evaluating the effort expended to understand speech in noise using a dual-task paradigm: the effects of providing visual speech cues. , 2010, Journal of speech, language, and hearing research : JSLHR.

[10]  James M. Kates,et al.  The Hearing-Aid Speech Perception Index (HASPI) , 2014, Speech Commun..

[11]  Yu Tsao,et al.  Generalized maximum a posteriori spectral amplitude estimation for speech enhancement , 2016, Speech Commun..

[12]  Linda Thibodeau Benefits of adaptive FM systems on speech recognition in noise for listeners who use hearing aids. , 2010, American journal of audiology.

[13]  Lisa B. Elliot,et al.  Deaf and Hard-of-Hearing Students' Memory of Lectures with Speech-to-Text and Interpreting/Note Taking Services , 2009 .

[14]  Howard Goldstein,et al.  Benefi t of S/N Enhancing Devices to Speech Perception of Children Listening in a Typical Classroom with Hearing Aids or a Cochlear Implant , 2005 .

[15]  Yu Tsao,et al.  Speech enhancement based on deep denoising autoencoder , 2013, INTERSPEECH.

[16]  Christopher J. Plack,et al.  Listening effort at signal-to-noise ratios that are typical of the school classroom , 2010, International journal of audiology.

[17]  Benjamin W Y Hornsby,et al.  Commentary: listening can be exhausting--fatigue in children and adults with hearing loss. , 2014, Ear and hearing.

[18]  DeLiang Wang,et al.  Ideal ratio mask estimation using deep neural networks for robust speech recognition , 2013, 2013 IEEE International Conference on Acoustics, Speech and Signal Processing.

[19]  Richard Emanuel,et al.  How College Students Spend Their Time Communicating , 2008 .

[20]  Jace Wolfe,et al.  Evaluation of speech recognition in noise with cochlear implants and dynamic FM. , 2009, Journal of the American Academy of Audiology.

[21]  Jean Écalle,et al.  Audio-visual training in children with reading disabilities , 2006, Comput. Educ..

[22]  Jean-Pierre Gagné,et al.  Older adults expend more listening effort than young adults recognizing speech in noise. , 2011, Journal of speech, language, and hearing research : JSLHR.

[23]  Nina Kraus,et al.  Assistive listening devices drive neuroplasticity in children with dyslexia , 2012, Proceedings of the National Academy of Sciences.

[24]  Candace Bourland Hick,et al.  Listening effort and fatigue in school-age children with and without hearing loss. , 2002, Journal of speech, language, and hearing research : JSLHR.

[25]  R. G. Leonard,et al.  A database for speaker-independent digit recognition , 1984, ICASSP.

[26]  James M. Kates,et al.  The Hearing-Aid Speech Quality Index (HASQI) , 2010 .

[27]  Erin C. Schafer,et al.  Improvements in Speech Recognition Using Cochlear Implants and Three Types of FM Systems: A Meta-Analytic Approach , 2009 .

[28]  B. Hornsby The Effects of Hearing Aid Use on Listening Effort and Mental Fatigue Associated With Sustained Speech Processing Demands , 2013, Ear and hearing.

[29]  Gregory A Flamme,et al.  Prevalence of hearing impairment by gender and audiometric configuration: results from the National Health and Nutrition Examination Survey (1999-2004) and the Keokuk County Rural Health Study (1994-1998). , 2008, Journal of the American Academy of Audiology.

[30]  Philipos C. Loizou,et al.  Speech Enhancement: Theory and Practice , 2007 .

[31]  T. Hasselbring,et al.  Use of computer technology to help students with special needs. , 2000, The Future of children.