"Computer, Test My Hearing": Accurate Speech Audiometry with Smart Speakers

Speech audiometry based on matrix sentence tests is an important diagnostic tool for hearing impairment and fitting of hearing aids. This paper introduces a self-conducted measurement for estimating the speech reception threshold (SRT) of a subject, i.e., the signal-to-noise ratio corresponding to 50% intelligibility, based on a smart speaker. While the original measurement procedure is well-evaluated and provides a very high measurement accuracy (< 1 dB test-retest standard deviation), the measurement using a smart speaker differs in several aspects from the commercially available implementation, such as missing control over the absolute presentation level, mode of presentation (headphones vs. loudspeaker), potential errors from the automated response logging, and influence from room acoustics. The SRT measurement accuracy is evaluated with six normal-hearing subjects conducted with an Amazon Alexa application on an Echo Plus loudspeaker in a quiet office environment. We found a significant difference of 0.6 dB in SRT between the proposed and the commercially available testing procedure. However, this bias is smaller than the inter-subject standard deviation, and the measurement accuracy is similar to the original test for normal-hearing listeners, which indicates that smart speakers may become a helpful addition for the screening of hearing deficits.

[1]  Thomas Brand,et al.  Measuring Speech Recognition With a Matrix Test Using Synthetic Speech , 2019, Trends in hearing.

[2]  Joel J. P. C. Rodrigues,et al.  Home-based exercise system for patients using IoT enabled smart speaker , 2017, 2017 IEEE 19th International Conference on e-Health Networking, Applications and Services (Healthcom).

[3]  Birger Kollmeier,et al.  Efficient adaptive procedures for threshold and concurrent slope estimates for psychophysics and speech intelligibility tests. , 2002, The Journal of the Acoustical Society of America.

[4]  Stig Arlinger,et al.  Negative consequences of uncorrected hearing loss—a review , 2003, International journal of audiology.

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

[6]  Birger Kollmeier,et al.  Evaluation of an automated speech-controlled listening test with spontaneous and read responses , 2018, Speech Commun..

[7]  Tammo Houtgast,et al.  Development and validation of an automatic speech-in-noise screening test by telephone , 2004, International journal of audiology.

[8]  Jan Rennies,et al.  Perceived listening effort and speech intelligibility in reverberation and noise for hearing-impaired listeners , 2016, International journal of audiology.

[9]  Anna Warzybok,et al.  The multilingual matrix test: Principles, applications, and comparison across languages: A review , 2015, International journal of audiology.

[10]  A. Kakarountas,et al.  An Acoustic-Based Smart Home System for People Suffering from Dementia , 2019, Technologies.

[11]  T. Houtgast,et al.  How we do it: The Dutch functional hearing–screening tests by telephone and internet , 2006, Clinical otolaryngology : official journal of ENT-UK ; official journal of Netherlands Society for Oto-Rhino-Laryngology & Cervico-Facial Surgery.