Output signal-to-noise ratio and speech perception in noise: effects of algorithm

Hybrid method for noise rejection from breath sound using transient artifact reduction algorithm and spectral subtraction

OBJECTIVES

Computerized breath sound based diagnostic methods are one of the emerging technologies gaining popularity in terms of detecting respiratory disorders. However, the breath sound signal used in such automated systems used to be too noisy, which affects the quality of the diagnostic interpretations. To address this problem, the proposed work presents the new hybrid approach to reject the noises from breath sound.

METHODS

In this method, 80 chronic obstructive pulmonary disease (COPD), 75 asthmatics and 80 normal breath sounds were recorded from the participants of a hospital. Each of these breath sound data were decontaminated using hybrid method of Butterworth band-pass filter, transient artifact reduction algorithm and spectral subtraction algorithm. The study examined the algorithms noise rejection potential over each category of breath sound by estimating the noise rejection performance metrics, i.e., mean absolute error (MAE), mean square error (MSE), peak signal to noise ratio (PSNR), and signal to noise ratio (SNR).

RESULTS

Using this algorithm, the study obtained a high value of SNR of 70 dB and that of PSNR of 72 dB.

CONCLUSIONS

The study could definitely a suitable one to suppress noises and to produce noise free breath sound signal.

The Noise Reduction Algorithm May Not Compensate for the Degradation in Output Signal-to-Noise Ratio Caused by Wide Dynamic Range Compression

PURPOSE

Most modern hearing aids (HAs) employ wide dynamic range compression (WDRC) and noise reduction (NR) algorithms. It is known that the nonlinear effects of WDRC and NR cause changes to the output signal-to-noise ratio (SNR) of an HA. However, the relative contributions of WDRC and NR to the nonlinear effects are not fully understood. The current study investigated (a) whether WDRC or NR dominates the nonlinear effects measured at the output of a digital HA and (b) whether the electroacoustic effectiveness of NR depends on WDRC parameters while input SNR and background noise are systematically varied.

METHOD

Test stimuli were Connected Speech Test sentences in multitalker babble noise (2- or 20-talker), presented at input SNRs ranging from -10 to +10 dB. The HA was programmed using multiband WDRC set according to the National Acoustic Laboratories for Nonlinear HA fitting formula 2 prescriptive fits for four standard audiograms and two compression speeds. The NR algorithm of the HA was switched on or off in separate conditions. Nonlinear electroacoustic effects from the WDRC and NR algorithms were assessed by measuring the output SNR of the HA using a phase-inversion technique. To investigate whether there are other factors that may be important besides the output SNR, the Hearing Aid Speech Intelligibility Index and the Hearing Aid Speech Quality Index were applied to the recordings to generate inferences on aided speech intelligibility and perceived speech quality.

RESULTS

Results showed that WDRC dominated the net nonlinear effect at low-input SNRs, and the net nonlinear effect of WDRC and NR was reduced at high-input SNRs. Results also showed that the effectiveness of NR depended on compression parameters. The effectiveness of NR was partially explained by the trend of Hearing Aid Speech Intelligibility Index and Hearing Aid Speech Quality Index scores, potentially indicating that the Hearing Aid Speech Intelligibility Index and Hearing Aid Speech Quality Index scores may capture factors that cannot be captured by the output SNR metric.

CONCLUSIONS

Results suggest that the individual signal-processing stages in an HA should not be considered as independent. Electroacoustic evaluation of WDRC and NR algorithms in isolation is not sufficient to capture the combined nonlinear effect of the two algorithms.

SUPPLEMENTAL MATERIAL

https://doi.org/10.23641/asha.25962541.

Effects of entropy in real-world noise on speech perception in listeners with normal hearing and hearing lossa)

Hearing aids show more benefit in traditional laboratory speech-in-noise tests than in real-world noisy environments. Real-world noise comprises a large range of acoustic properties that vary randomly and rapidly between and within environments, making quantifying real-world noise and using it in experiments and clinical tests challenging. One approach is to use acoustic features and statistics to quantify acoustic properties of real-world noise and control for them or measure their relationship to listening performance. In this study, the complexity of real-world noise from different environments was quantified using entropy in both the time- and frequency-domains. A distribution of noise segments from low to high entropy were extracted. Using a trial-by-trial design, listeners with normal hearing and hearing loss (in aided and unaided conditions) repeated back sentences embedded in these noise segments. Entropy significantly affected speech perception, with a larger effect of entropy in the time-domain than the frequency-domain, a larger effect for listeners with normal hearing than for listeners with hearing loss, and a larger effect for listeners with hearing loss in the aided than unaided condition. Speech perception also differed between most environment types. Combining entropy with the environment type improved predictions of speech perception above the environment type alone.

Characterization and Prediction of Speech Intelligibility at the Output of Hearing Aids in a Noisy Working Environment

Objective

Hearing aids are more and more technically advanced, but do not necessarily guarantee the reproduction of useful signals in all working environments. This is particularly the case for speech intelligibility. This study focuses on the prediction of hearing aid performance in the case of a moderate deafness setting, in service and industrial work environments. To improve intelligibility, hearing aids propose signal processing options such as noise reduction and compression. These processes can transform hearing aids into nonlinear systems. The aim of this study is to develop a nonlinear method for the characterization of hearing aids.

Materials and Methods

The method is based on the synchronized swept sine (SSS) signal method.[16] The SSS method is applied for determining hearing aid frequency responses fitted according to the present methodology and several processing options. The characterization of hearing aid's program containing the noise reduction function is specifically analyzed. Indeed, to be fully active and efficient, the hearing aid, with the noise reduction feature activated, needs to be immersed in a noisy environment which does not allow nonlinear characterization. A linear approach is taken to study this feature. Three hearing aids commonly sold by hearing care professionals are studied here; all of them have three different programs. The characterization for each program is discussed.

Results

The statistical study showed that the intelligibility, assessed using the speech transmission index in these sound environments, is well estimated for every program, although certain differences are observed when the compression effect is too high in the service work sector.

Conclusion

The characterizations of hearing aids using the programs studied did not highlight the presence of frequency nonlinearities. The characterization method could not take into account amplitude nonlinearities when there is too much gain compression in the hearing process. Globally, all the hearing aid programs provided a very significant improvement in intelligibility in service and industrial work contexts.

Verification of Estimated Output Signal-to-Noise Ratios From a Phase Inversion Technique Using a Simulated Hearing Aid

PURPOSE

The signal-to-noise ratio (SNR) for speech presented in background noise may vary after being processed by digital hearing aids with nonlinear signal processing algorithms, such as wide dynamic range compression (WDRC). A phase inversion technique has been previously developed to assess the output SNR of hearing aids. However, systematic validations of this technique have not been conducted. This study aims to validate the phase inversion technique.

METHOD

A simulated hearing aid with multichannel WDRC was implemented, from which the output SNRs, computed via shadow filtering, for connected speech in background noise were directly computed. The agreement between the shadow filter output SNRs and those estimated using the phase inversion technique for the same stimuli was utilized to validate the phase inversion technique. The background noise was 2- or 20-talker babble noise, and the speech stimuli were presented at SNRs of -10 to +10 dB at the input of the simulated hearing aid. The simulated hearing aid was configured to provide amplification for four representative audiograms, and the WDRC was set to be fast or slow acting. To investigate the effects of additive noise, independent of the presented noise stimulus, on the phase inversion estimated output SNR, the same simulated hearing aid was implemented with an additive Gaussian noise at its input (45 and 60 dB SPL).

RESULTS

Results showed that the phase inversion technique could either overestimate or underestimate output SNR, depending on the test condition; the estimation errors tended to coincide with temporal landmarks, such as natural pauses between consecutive sentences or fricatives; and increasing the simulated noise led to poorer estimates of output SNR.

CONCLUSIONS

Results imply that the accuracy of the phase inversion technique is dependent on the test conditions. Thus, the phase inversion technique should be used with caution, and its validity should be evaluated further.

Modeling the effects of dynamic range compression on signals in noise

Hearing aids use dynamic range compression (DRC), a form of automatic gain control, to make quiet sounds louder and loud sounds quieter. Compression can improve listening comfort, but it can also cause unwanted distortion in noisy environments. It has been widely reported that DRC performs poorly in noise, but there has been little mathematical analysis of these noise-induced distortion effects. This work introduces a mathematical model to study the behavior of DRC in noise. By making simplifying assumptions about the signal envelopes, we define an effective compression function that models the compression applied to one signal in the presence of another. Using the properties of concave functions, we prove results about DRC that have been previously observed experimentally: that the effective compression applied to each sound in a mixture is weaker than it would have been for the signal alone; that uncorrelated signal envelopes become negatively correlated when compressed as a mixture; and that compression can reduce the long-term signal-to-noise ratio in certain conditions. These theoretical results are supported by software experiments using recorded speech signals.

A Comparison of Environment Classification Among Premium Hearing Instruments

Hearing aids classify acoustic environments into multiple, generic classes for the purposes of guiding signal processing. Information about environmental classification is made available to the clinician for fitting, counseling, and troubleshooting purposes. The goal of this study was to better inform scientists and clinicians about the nature of that information by comparing the classification schemes among five premium hearing instruments in a wide range of acoustic scenes including those that vary in signal-to-noise ratio and overall level (dB SPL). Twenty-eight acoustic scenes representing various prototypical environments were presented to five premium devices mounted on an acoustic manikin. Classification measures were recorded from the brand-specific fitting software then recategorized to generic labels to conceal the device company, including (a) Speech in Quiet, (b) Speech in Noise, (c) Noise, and (d) Music. Twelve normal-hearing listeners also classified each scene. The results revealed a variety of similarities and differences among the five devices and the human subjects. Where some devices were highly dependent on input overall level, others were influenced markedly by signal-to-noise ratio. Differences between human and hearing aid classification were evident for several speech and music scenes. Environmental classification is the heart of the signal processing strategy for any given device, providing key input to subsequent decision-making. Comprehensive assessment of environmental classification is essential when considering the cost of signal processing errors, the potential impact for typical wearers, and the information that is available for use by clinicians. The magnitude of differences among devices is remarkable and to be noted.

Cortical organization restored by cochlear implantation in young children with single sided deafness

Early treatment of single sided deafness in children has been recommended to protect from neurodevelopmental preference for the better hearing ear and from social and educational deficits. A fairly homogeneous group of five young children (≤3.6 years of age) with normal right sided hearing who received a cochlear implant to treat deafness in their left ears were studied. Etiology of deafness was largely cytomegalovirus (n = 4); one child had an enlarged vestibular aqueduct. Multi-channel electroencephalography of cortical evoked activity was measured repeatedly over time at: 1) acute (0.5 ± 0.7 weeks); 2) early chronic (1.1 ± 0.2 months); and 3) chronic (5.8 ± 3.4 months) cochlear implant stimulation. Results indicated consistent responses from the normal right ear with marked changes in activity from the implanted left ear. Atypical distribution of peak amplitude activity from the implanted ear at acute stimulation marked abnormal lateralization of activity to the ipsilateral left auditory cortex and recruitment of extra-temporal areas including left frontal cortex. These abnormalities resolved with chronic implant use and contralateral aural preference emerged in both auditory cortices. These findings indicate that early implantation in young children with single sided deafness can rapidly restore bilateral auditory input to the cortex needed to improve binaural hearing.