Prediction of speech intelligibility using a neurogram orthogonal polynomial measure (NOPM)
Sensorineural hearing loss (SNHL) is an increasingly prevalent condition, resulting from damage to the inner ear and causing a reduction in speech intelligibility. This paper proposes a new speech intelligibility prediction metric, the neurogram orthogonal polynomial measure (NOPM). This metric appl...
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| Format: | Article |
| Language: | English |
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Institute of Electrical and Electronics Engineers (IEEE)
2015
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| Online Access: | http://eprints.um.edu.my/13741/1/Prediction_of_Speech_Intelligibility_Using_a_Neurogram_Orthogonal.pdf |
| _version_ | 1796946628155801600 |
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| author | Mamun, N. Jassim, W.A. Zilany, M.S.A. |
| author_facet | Mamun, N. Jassim, W.A. Zilany, M.S.A. |
| author_sort | Mamun, N. |
| collection | UM |
| description | Sensorineural hearing loss (SNHL) is an increasingly prevalent condition, resulting from damage to the inner ear and causing a reduction in speech intelligibility. This paper proposes a new speech intelligibility prediction metric, the neurogram orthogonal polynomial measure (NOPM). This metric applies orthogonal moments to the auditory neurogram to predict speech intelligibility for listeners with and without hearing loss. The model simulates the responses of auditory-nerve fibers to speech signals under quiet and noisy conditions. Neurograms were created using a physiologically based computational model of the auditory periphery. A well-known orthogonal polynomial measure, Krawtchouk moments, was applied to extract features from the auditory neurogram. The predicted intelligibility scores were compared to subjective results, and NOPM showed a good fit with the subjective scores for normal listeners and also for listeners with hearing loss. The proposed metric has a realistic and wider dynamic range than corresponding existing metrics, such as mean structural similarity index measure and neurogram similarity index measure, and the predicted scores are also well-separated as a function of hearing loss. The application of this metric could be extended for assessing hearing-aid and speech-enhancement algorithms. |
| first_indexed | 2024-03-06T05:34:40Z |
| format | Article |
| id | um.eprints-13741 |
| institution | Universiti Malaya |
| language | English |
| last_indexed | 2024-03-06T05:34:40Z |
| publishDate | 2015 |
| publisher | Institute of Electrical and Electronics Engineers (IEEE) |
| record_format | dspace |
| spelling | um.eprints-137412017-07-08T04:05:06Z http://eprints.um.edu.my/13741/ Prediction of speech intelligibility using a neurogram orthogonal polynomial measure (NOPM) Mamun, N. Jassim, W.A. Zilany, M.S.A. T Technology (General) TA Engineering (General). Civil engineering (General) Sensorineural hearing loss (SNHL) is an increasingly prevalent condition, resulting from damage to the inner ear and causing a reduction in speech intelligibility. This paper proposes a new speech intelligibility prediction metric, the neurogram orthogonal polynomial measure (NOPM). This metric applies orthogonal moments to the auditory neurogram to predict speech intelligibility for listeners with and without hearing loss. The model simulates the responses of auditory-nerve fibers to speech signals under quiet and noisy conditions. Neurograms were created using a physiologically based computational model of the auditory periphery. A well-known orthogonal polynomial measure, Krawtchouk moments, was applied to extract features from the auditory neurogram. The predicted intelligibility scores were compared to subjective results, and NOPM showed a good fit with the subjective scores for normal listeners and also for listeners with hearing loss. The proposed metric has a realistic and wider dynamic range than corresponding existing metrics, such as mean structural similarity index measure and neurogram similarity index measure, and the predicted scores are also well-separated as a function of hearing loss. The application of this metric could be extended for assessing hearing-aid and speech-enhancement algorithms. Institute of Electrical and Electronics Engineers (IEEE) 2015 Article PeerReviewed application/pdf en http://eprints.um.edu.my/13741/1/Prediction_of_Speech_Intelligibility_Using_a_Neurogram_Orthogonal.pdf Mamun, N. and Jassim, W.A. and Zilany, M.S.A. (2015) Prediction of speech intelligibility using a neurogram orthogonal polynomial measure (NOPM). IEEE/ACM Transactions on Audio, Speech and Language Processing, 23 (4). pp. 760-773. ISSN 2329-9290, DOI https://doi.org/10.1109/taslp.2015.2401513 <https://doi.org/10.1109/taslp.2015.2401513>. http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7035038&tag=1 10.1109/taslp.2015.2401513 |
| spellingShingle | T Technology (General) TA Engineering (General). Civil engineering (General) Mamun, N. Jassim, W.A. Zilany, M.S.A. Prediction of speech intelligibility using a neurogram orthogonal polynomial measure (NOPM) |
| title | Prediction of speech intelligibility using a neurogram orthogonal polynomial measure (NOPM) |
| title_full | Prediction of speech intelligibility using a neurogram orthogonal polynomial measure (NOPM) |
| title_fullStr | Prediction of speech intelligibility using a neurogram orthogonal polynomial measure (NOPM) |
| title_full_unstemmed | Prediction of speech intelligibility using a neurogram orthogonal polynomial measure (NOPM) |
| title_short | Prediction of speech intelligibility using a neurogram orthogonal polynomial measure (NOPM) |
| title_sort | prediction of speech intelligibility using a neurogram orthogonal polynomial measure nopm |
| topic | T Technology (General) TA Engineering (General). Civil engineering (General) |
| url | http://eprints.um.edu.my/13741/1/Prediction_of_Speech_Intelligibility_Using_a_Neurogram_Orthogonal.pdf |
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