ORIGINAL ARTICLE
EFFECT OF DIGITAL NOISE REDUCTION AND DIRECTIONALITY ALGORITHMS IN HEARING AIDS ON TEMPORAL ENVELOPE DISTORTION AND SPEECH RECOGNITION
Geetha Chinnaraj 1, A,C-E,G
,
 
,
 
 
 
 
More details
Hide details
1
Department of Audiology, All India Institute of Speech and Hearing, India
 
 
A - Research concept and design; B - Collection and/or assembly of data; C - Data analysis and interpretation; D - Writing the article; E - Critical revision of the article; F - Final approval of article;
 
 
Publication date: 2022-03-01
 
 
Corresponding author
Geetha Chinnaraj   

Department of Audiology, All India Institute of Speech and Hearing, Manasagangothri, 570006, Mysore, India
 
 
J Hear Sci 2021;11(4):19-29
 
KEYWORDS
TOPICS
ABSTRACT
Background:
Digital signal processing algorithms tend to alter temporal cues in the speech signal and yet individuals with hearing impairment rely strongly on these cues for speech perception. Hence, there is a need to assess the effect of these algorithms on temporal cues and speech perception. The present study aimed to quantify, in a wide dynamic range compression hearing aid, the individual and combined effects of digital noise reduction and directionality algorithms on temporal cues, syllable recognition, and sentence recognition. Temporal cues were quantified by the envelope difference index (EDI).

Material and methods:
The study included 20 individuals (in the age range of 21 to 44 years) with mild to moderate sensorineural hearing loss. Sentence recognition, syllable recognition, and EDI were obtained at different levels in four different aided conditions – digital noise reduction algorithm only, directionality only, both digital noise reduction and directionality on, and both algorithms off. Sentences were presented in noise at +5 dB signal-to-noise ratio from 180° azimuth.

Results:
Compared to independent activation of the algorithms, the combined algorithms significantly improved speech recognition scores at all presentation levels. The temporal changes induced by the algorithms were only mild, even though EDI was the highest when all the algorithms and the directional microphone were activated.

Conclusions:
The noise reduction algorithms and compression induce temporal changes; however speech recognition improved when the algorithms were activated, presumably due to countervailing psychophysical factors.

 
REFERENCES (40)
1.
Souza P. Speech perception and hearing aids. In: Popelka GR, Moore BCJ, Fay RR, Popper AN, Hearing Aids. Switzerland: Springer International, 2016; p. 151–80.
 
2.
Dillon H. Binaural and bilateral considerations in hearing aid fitting. In: Hearing Aids. New York, NY: Thieme, 2001; p. 370–403.
 
3.
Arpita V, Manjula P. Effects of compression release time in hearing aid on acoustic and behavioral measures of speech. Articles based on dissertations done at AIISH, 2012; 10: 20–31.
 
4.
Souza PE, Hoover H, Gallun F. Application of envelope difference index to spectrally sparse speech. J Speech Lang Hear Res, 2012; 50: 824–37.
 
5.
Levitt H. Noise reduction in hearing aids: a review. J Rehabil Res Dev, 2001; 38: 7–19.
 
6.
Levitt H, Bakke M, Kates J. Signal processing for hearing impairment. Scand Audiol Suppl, 1993; 38: 7–19.
 
7.
Boymans M, Dreschler WA. Field trials using a digital hearing aid with active noise reduction and dual-microphone directionality. Audiol, 2000; 39: 260–8.
 
8.
Alcantara JI, Moore BCJ, Kuhnel V, Launer S. Evaluation of noise reduction system in a commercial digital hearing aid. Inter J Audiol, 2003; 42: 34–42.
 
9.
Kuk F, Korhonen P, Slugocki C. Preserving the temporal envelope in hearing aid processed sounds. Hear Review, 2018; 25(10): 40–4.
 
10.
Tachibana RO, Sasaki Y, Riquimaroux H. Relative contributions of spectral and temporal resolutions to the perception of syllables, words, and sentences in noise-vocoded speech. Acoust Sci Technol, 2013; 34(4): 263–70.
 
11.
Li X, Ning Z, Brashears R, Rife K. Relative contributions of spectral and temporal cues for speech recognition in patients with sensorineural hearing loss. J Otol, 2008; 3(2): 84–91.
 
12.
Fortune TW, Woodruff BD, Preves DA. A new technique for quantifying temporal envelope contrasts. Ear Hear, 1994; 15: 93–9.
 
13.
Jenstad LM, Souza PE. Quantifying the effect of compression hearing aid release time on speech acoustics and intelligibility. J Speech Lang Hear Res, 2005; 48: 651–67.
 
14.
Jenstad LM, Souza PE. Temporal envelope changes of compression and speech rate: combined effects on recognition for older adults. J Speech Lang Hear Res, 2007; 50: 1123–38.
 
15.
Ricketts TA, Hornsby BWY. Sound quality measures for speech in noise through a commercial hearing aid implementing “Digital Noise Reduction”. J Am Acad Audiol, 2005; 16: 270–7.
 
16.
Chung K, Zeng FG, Waltzman S. Utilizing hearing aid directional microphones and noise reduction algorithms to improve speech understanding and listening preferences of cochlear implant users. Int Congress Series, 2004; 1273: 89–92.
 
17.
Walden BE, Surr RK, Cord MT, Edwards B, Olson L. Comparison of benefits provided by different hearing aid technologies. J Am Acad Audiol, 2000; 11(10): 540–60.
 
18.
Nordrum S, Erler S, Garstecki D, Dhar S. Comparison of performance on the hearing in noise test using directional microphones and digital noise reduction algorithms. Am J Audiol, 2006; 15: 81–91.
 
19.
Geetha C, Manjula P. Effect of compression, digital noise reduction and directionality on envelope difference index, log-likelihood ratio and perceived quality. Audiol Res, 2014; 4(1): 46–51.
 
20.
Vinodhini P. Relationship Between Envelope Difference Index (EDI) and Sentence Recognition and Speech Quality in Individuals with Hearing Impairment. Unpublished Masters dissertation, University of Mysore, Mysore, 2015.
 
21.
Walaszek J. Effect of compression in hearing aids on the envelope of the speech signal: signal based measures of the side-effects of the compression and their relation to speech intelligibility. Unpublished Masters thesis, Technical University of Denmark, Lingby, 2008.
 
22.
Kennedy E, Levitt H, Neuman AC, Weiss M. Consonant–vowel intensity ratios for maximizing consonant recognition by hearing-impaired listeners. J Acoust Soc Am, 1998; 103: 1098–114.
 
23.
Geetha C, Kumar KSS, Manjula P, Pavan M. Development and standardization of sentence identification test in Kannada language. J Hear Sci, 2014; 4(1): 18–26.
 
24.
Ramakrishna BS, Nair KK, Chiplunkar VN, Atal BS, Ramachandran V, Subramanian R. Some aspects of the relative efficiencies of Indian languages. Ranchi, India: Catholic Press, 1962.
 
25.
Boothroyd A, Medwetsky L. Spectral distribution of /s/ and the frequency response of hearing aids. Ear Hear, 1992; 13: 150–7.
 
26.
Winholtz WS, Titze IR. Conversion of a head-mounted microphone signal into calibrated SPL units. J Voice, 1997; 11: 417–21.
 
27.
Korhonen P, Kuk F, Slugocki C. A method to evaluate the effect of signal processing on the temporal envelope of speech. Hear Review, 2019; 26(6): 10–18.
 
28.
Ricketts TA. Impact of noise source configuration on directional hearing aid benefit and performance. Ear Hear, 2000; 21: 194–205.
 
29.
Souza PE. Effect of compression on speech acoustics, intelligibility, and sound quality. Trends Amplif, 2002; 6: 131–65.
 
30.
Aswathi S, Geetha C. Combined effect of compression and digital noise reduction algorithms on speech perception and speech quality. Articles based on dissertations done at AIISH, 2013; 10: 1–7.
 
31.
Hoover EC, Souza PE, Gallun F. The consonant-weighted Envelope Difference Index (cEDI): a proposed technique for quantifying envelope distortion. J Speech Lang Hear Res, 2012; 55(6): 1802–6.
 
32.
Alexander JM, Masterson K. Effects of WDRC release time and number of channels on output SNR and speech recognition. Ear Hear, 2015; 36: e35–e49.
 
33.
Gatehouse S, Naylor G, Elberling C. Linear and nonlinear hearing aid fittings. 2. Patterns of candidature. Int J Audiol, 2006; 45: 153–71.
 
34.
Balakrishnan U, Freyman RL, Chiang YC, Nerbonne GP, Shea KJ. Consonant recognition for spectrally degraded speech as a function of consonant–vowel intensity ratio. J Acoust Soc Am, 1996; 99: 3758–69.
 
35.
Ohde, RN, Stevens KN. Effect of burst amplitude on the perception of stop consonant place of articulation. J Acoust Soc Am, 1984; 74: 706–14.
 
36.
Hedrick MS, Rice T. Effect of a single-channel wide dynamic range compression circuit on perception of stop consonant place of articulation. J Speech Lang Hear Res, 2000; 43: 1174–84.
 
37.
Hedrick MS, Younger MS. Perceptual weighting of relative amplitude and formant transition cues in aided CV syllables. J Speech Lang Hear Res, 2001; 44: 964–74.
 
38.
Hedrick MS, Younger MS. Labeling of /s/ and /ʃ/ by listeners with normal and impaired hearing, revisited. J Speech Lang Hear Res, 2003; 46: 636–48.
 
39.
Souza PE, Turner CW. Effect of single channel compression on temporal speech information. J Speech Hear Res, 1996; 39: 901–11.
 
40.
Bentler R, Chiou L. Digital noise reduction: an overview. Trends Amplif, 2006; 10: 67–82.
 
Journals System - logo
Scroll to top