Spectral Smearing Research Articles

Close approximations to the sound of a cochlear implant.

Cochlear implant (CI) systems differ in terms of electrode design and signal processing. It is likely that patients fit with different implant systems will experience different percepts when presented speech via their implant. The sound quality of speech can be evaluated by asking single-sided-deaf (SSD) listeners fit with a cochlear implant (CI) to modify clean signals presented to their typically hearing ear to match the sound quality of signals presented to their CI ear. In this paper, we describe very close matches to CI sound quality, i.e., similarity ratings of 9.5 to 10 on a 10-point scale, by ten patients fit with a 28 mm electrode array and MED EL signal processing. The modifications required to make close approximations to CI sound quality fell into two groups: One consisted of a restricted frequency bandwidth and spectral smearing while a second was characterized by a wide bandwidth and no spectral smearing. Both sets of modifications were different from those found for patients with shorter electrode arrays who chose upshifts in voice pitch and formant frequencies to match CI sound quality. The data from matching-based metrics of CI sound quality document that speech sound-quality differs for patients fit with different CIs and among patients fit with the same CI.

Tacho-less spur gear condition monitoring at variable speed operation using the adaptive application of variational mode extraction

Effective condition monitoring of machine components contributes to a safer working environment for operators and assists in averting critical machinery shutdowns. In real-world industrial scenarios, fault detection must remain simplified, user-friendly and robust despite speed variations. The operational demands of machinery frequently result in speed fluctuations, leading to spectral smearing, thereby compromising the efficiency of the analysis methodology. Furthermore, the intricacies of parameter initialisation often increase the complexity of the analysis methods. This study introduces a fault diagnosis algorithm that requires minimal initialisation and operates independently of tacho pulses. The algorithm proposed in the study incorporates variational mode extraction with the maxima tracking algorithm for instantaneous frequency estimation. Hankel matrix-based selective spectral fusion is proposed to mitigate the impact of frequency tracking errors caused by transient noise. The results of spectral side-band-based fault severity analysis, conducted on an in-house spur gearbox test-bed with seeded tooth chips, underscore the superior performance of the proposed algorithm when compared to contemporary non-stationary analysis methods.

Effects of spectral smearing on speech understanding and masking release in simulated bilateral cochlear implants.

Differences in spectro-temporal degradation may explain some variability in cochlear implant users' speech outcomes. The present study employs vocoder simulations on listeners with typical hearing to evaluate how differences in degree of channel interaction across ears affects spatial speech recognition. Speech recognition thresholds and spatial release from masking were measured in 16 normal-hearing subjects listening to simulated bilateral cochlear implants. 16-channel sine-vocoded speech simulated limited, broad, or mixed channel interaction, in dichotic and diotic target-masker conditions, across ears. Thresholds were highest with broad channel interaction in both ears but improved when interaction decreased in one ear and again in both ears. Masking release was apparent across conditions. Results from this simulation study on listeners with typical hearing show that channel interaction may impact speech recognition more than masking release, and may have implications for the effects of channel interaction on cochlear implant users' speech recognition outcomes.

The synchrosqueezing transform to evaluate paleoclimate cyclicity

Centennial and millennial-scale climate cycles are observed in paleoclimate proxies distributed globally. For example, periods of ∼2.3, ∼1.5, ∼1, and ≤0.5 thousand years (kyr) are reported in the Holocene, and numerous studies have related cycles with such periods to fluctuations in solar intensity received at the Earth's surface. For the 1.5 kyr cycle, however, there is still much uncertainty surrounding the exact period and presence of the oscillation. This uncertainty is primarily due to difficulty distinguishing cycles from one another; distinguishing this 1.5 kyr cycle from surrounding cycles and determining the onset and cessation of this cycle is crucial to the evaluation of the mechanism driving this cycle. Commonly methods for paleoclimate spectral analysis, such as the Continuous Wavelet Transform and Short-Time Fourier Transform cannot clearly reveal the onset or cessation of sporadic climatic cycles if neighboring spectral peaks are present within an octave due to spectral smearing and leakage. Here, we present a novel application of the Synchrosqueezing Transform in paleoclimate research to obtain improved separation of climate cycles and to more precisely determine the onset and cessation of cycles that are sporadic through the paleoclimate proxy time-series. The SST and its inverse provide a more exact estimate of the onset and cessation of which is useful in comparing to the spectra of other paleoclimate proxies to determine the drivers of specific climate oscillations. We demonstrate that application of the SST to a range of Holocene climate proxies provides consistent identification of the 1.5 kyr cycle.

Speech phoneme and spectral smearing based non-invasive COVID-19 detection.

COVID-19 is a deadly viral infection that mainly affects the nasopharyngeal and oropharyngeal cavities before the lung in the human body. Early detection followed by immediate treatment can potentially reduce lung invasion and decrease fatality. Recently, several COVID-19 detections methods have been proposed using cough and breath sounds. However, very little study has been done on the use of phoneme analysis and the smearing of the audio signal in COVID-19 detection. In this paper, this problem has been addressed and the classification of speech samples has been carried out in COVID-19-positive and healthy audio samples. Additionally, the grouping of the phonemes based on reference classification accuracies have been proposed for effectiveness and faster detection of the disease at a primary stage. The Mel and Gammatone Cepstral coefficients and their derivatives are used as the features for five standard machine learning-based classifiers. It is observed that the generalized additive model provides the highest accuracy of 97.22% for the phoneme grouping "/t//r//n//g//l/." This smearing-based phoneme classification technique can also be used in the future to classify other speech-related disease detections.

Effects of spectral smearing on speech understanding and masking release in simulated bilateral cochlear implants

Cochlear implants (CIs) have limited spectral resolution due to the number of activated electrodes and current spread in the cochlea, with ramifications for speech processing. Differences in degree of channel interaction across ears may partially explain variability in outcomes among CI users. This study explores how channel interaction impacts speech understanding in simulated cochlear implants. Speech recognition thresholds (SRTs) were measured in the presence of two speech maskers by 16 normal-hearing subjects listening to simulated bilateral CIs. Speech was delivered to both ears while maskers were delivered binaurally (diotic) or monaurally (dichotic). Stimuli were 16-channel sine-vocoded speech simulating 1) limited channel interaction in both ears, 2) limited channel interaction in one and broad in the other, or 3) broad channel interaction in both. Masking release was quantified as the SRT difference between diotic and dichotic conditions. SRTs were highest with broad channel interaction in both ears; when interaction decreased in one ear, SRTs improved, and improved further with limited interaction in both. Masking release was apparent across all conditions, but especially when the interaction was similar across ears (broad: 6.45 dB; limited: 6.51 dB). These results suggest that channel interaction may impact speech recognition more than masking release.

Effects of Spectral Resolution on Simple Magnetic Field Diagnostics of the Mg ii H and K Lines

We study the effects of finite spectral resolution on the magnetic field values retrieved through the weak-field approximation (WFA) from the cores of the Mg ii h and k lines. The retrieval of the line-of-sight component of the magnetic field, B LOS, from synthetic spectra generated in a uniformly magnetized FAL-C atmosphere is accurate when restricted to the inner lobes of Stokes V. As we degrade the spectral resolution, partial redistribution effects, which more prominently affect the outer lobes of Stokes V, are brought into the line core through spectral smearing, degrading the accuracy of the WFA and resulting in an inference bias, which is more pronounced as the resolution becomes poorer. When applied to a diverse set of spectra emerging from a sunspot simulation, we find good accuracy in the retrieved B LOS when comparing it to the model value at the height where the optical depth in the line core is unity. The accuracy is preserved up to field strengths of B ∼ 1500 G. Limited spectral resolution results in a small bias toward weaker retrieved fields. The WFA for the transverse component of the magnetic field is also evaluated. Reduced spectral resolution degrades the accuracy of the inferences, because spectral mixing results in the line effectively probing deeper layers of the atmosphere.

The effects of Lombard perturbation on speech intelligibility in noise for normal hearing and cochlear implant listeners.

Natural compensation of speech production in challenging listening environments is referred to as the Lombard effect (LE). The resulting acoustic differences between neutral and Lombard speech have been shown to provide intelligibility benefits for normal hearing (NH) and cochlear implant (CI) listeners alike. Motivated by this outcome, three LE perturbation approaches consisting of pitch, duration, formant, intensity, and spectral contour modifications were designed specifically for CI listeners to combat speech-in-noise performance deficits. Experiment 1 analyzed the effects of loudness, quality, and distortion of approaches on speech intelligibility with and without formant-shifting. Significant improvements of +9.4% were observed in CI listeners without the formant-shifting approach at +5 dB signal-to-noise ratio (SNR) large-crowd-noise (LCN) when loudness was controlled, however, performance was found to be significantly lower for NH listeners. Experiment 2 evaluated the non-formant-shifting approach with additional spectral contour and high pass filtering to reduce spectral smearing and decrease distortion observed in Experiment 1. This resulted in significant intelligibility benefits of +30.2% for NH and +21.2% for CI listeners at 0 and +5 dB SNR LCN, respectively. These results suggest that LE perturbation may be useful as front-end speech modification approaches to improve intelligibility for CI users in noise.

Reaction Time Sensitivity to Spectrotemporal Modulations of Sound.

We tested whether sensitivity to acoustic spectrotemporal modulations can be observed from reaction times for normal-hearing and impaired-hearing conditions. In a manual reaction-time task, normal-hearing listeners had to detect the onset of a ripple (with density between 0–8 cycles/octave and a fixed modulation depth of 50%), that moved up or down the log-frequency axis at constant velocity (between 0–64 Hz), in an otherwise-unmodulated broadband white-noise. Spectral and temporal modulations elicited band-pass filtered sensitivity characteristics, with fastest detection rates around 1 cycle/oct and 32 Hz for normal-hearing conditions. These results closely resemble data from other studies that typically used the modulation-depth threshold as a sensitivity criterion. To simulate hearing-impairment, stimuli were processed with a 6-channel cochlear-implant vocoder, and a hearing-aid simulation that introduced separate spectral smearing and low-pass filtering. Reaction times were always much slower compared to normal hearing, especially for the highest spectral densities. Binaural performance was predicted well by the benchmark race model of binaural independence, which models statistical facilitation of independent monaural channels. For the impaired-hearing simulations this implied a “best-of-both-worlds” principle in which the listeners relied on the hearing-aid ear to detect spectral modulations, and on the cochlear-implant ear for temporal-modulation detection. Although singular-value decomposition indicated that the joint spectrotemporal sensitivity matrix could be largely reconstructed from independent temporal and spectral sensitivity functions, in line with time-spectrum separability, a substantial inseparable spectral-temporal interaction was present in all hearing conditions. These results suggest that the reaction-time task yields a valid and effective objective measure of acoustic spectrotemporal-modulation sensitivity.

Dynamic transverse magnetic susceptibility in the projector augmented-wave method: Application to Fe, Ni, and Co

We present a first principles implementation of the dynamic transverse magnetic susceptibility in the framework of linear response time-dependent density functional theory. The dynamic susceptibility allows one to obtain the magnon dispersion as well as magnon lifetimes for a particular material, which strongly facilitates the interpretation of inelastic neutron scattering experiments as well as other spectroscopic techniques. We apply the method to Fe, Ni, and Co and perform a thorough convergence analysis with respect the basis set size, $k$-point sampling, spectral smearing and unoccupied bands. In particular, it is shown that while the gap error (acoustic magnon energy at $\mathbf{q}=\mathbf{0}$) is highly challenging to converge, the spin-wave stiffness and the dispersion relation itself are much less sensitive to convergence parameters. Our final results agrees well with experimentally extracted magnon dispersion relations except for Ni, where it is well-known that the exchange splitting energy is poorly represented in the local density approximation. We also find good agreement with previous first principles calculations and explain how differences in the calculated dispersion relations can arise from subtle differences in computational approaches.

Effect of Channel Interaction on Vocal Cue Perception in Cochlear Implant Users.

Speech intelligibility in multitalker settings is challenging for most cochlear implant (CI) users. One possibility for this limitation is the suboptimal representation of vocal cues in implant processing, such as the fundamental frequency (F0), and the vocal tract length (VTL). Previous studies suggested that while F0 perception depends on spectrotemporal cues, VTL perception relies largely on spectral cues. To investigate how spectral smearing in CIs affects vocal cue perception in speech-on-speech (SoS) settings, adjacent electrodes were simultaneously stimulated using current steering in 12 Advanced Bionics users to simulate channel interaction. In current steering, two adjacent electrodes are simultaneously stimulated forming a channel of parallel stimulation. Three such stimulation patterns were used: Sequential (one current steering channel), Paired (two channels), and Triplet stimulation (three channels). F0 and VTL just-noticeable differences (JNDs; Task 1), in addition to SoS intelligibility (Task 2) and comprehension (Task 3), were measured for each stimulation strategy. In Tasks 2 and 3, four maskers were used: the same female talker, a male voice obtained by manipulating both F0 and VTL (F0+VTL) of the original female speaker, a voice where only F0 was manipulated, and a voice where only VTL was manipulated. JNDs were measured relative to the original voice for the F0, VTL, and F0+VTL manipulations. When spectral smearing was increased from Sequential to Triplet, a significant deterioration in performance was observed for Tasks 1 and 2, with no differences between Sequential and Paired stimulation. Data from Task 3 were inconclusive. These results imply that CI users may tolerate certain amounts of channel interaction without significant reduction in performance on tasks relying on voice perception. This points to possibilities for using parallel stimulation in CIs for reducing power consumption.

A Methodology to Handle Spectral Smearing in Gearboxes Using Adaptive Mode Decomposition and Dynamic Time Warping

Tacho-less order tracking is an effective tool for fault detection in gearboxes operating under speed fluctuations. This technique's performance depends on extracting instantaneous shaft speed information from a complex multicomponent gearbox signal, which is first preprocessed by a bandpass filter. However, spectral overlap resulting from the time-varying frequency components makes it challenging to isolate the shaft speed harmonic mono-component using this approach. In order to overcome such issues, an adaptive tacho-less order-tracking (OT) method combining the variational mode decomposition (VMD) and the fast dynamic time warping (FDTW) is proposed in this article. The proposed method first decomposes the measured gearbox vibration signal using VMD to estimate the instantaneous shaft speed profile to construct the shaft vibration signal. The gearbox vibration signal is then resampled based on the optimal warping path obtained by FDTW, which performs an “elastic” stretching and compression along the time axis of the extracted shaft vibration signal with respect to a sinusoidal reference signal with a constant shaft rotational frequency. Finally, the presence of gear fault is detected by constructing the order spectrum of the resampled vibration signal. The effectiveness of the proposed algorithm is demonstrated using both simulation analysis and experimental validation using measurements from two different wind-turbine gearboxes collected under test and field conditions, respectively.

Consistent independent low-rank matrix analysis for determined blind source separation

Independent low-rank matrix analysis (ILRMA) is the state-of-the-art algorithm for blind source separation (BSS) in the determined situation (the number of microphones is greater than or equal to that of source signals). ILRMA achieves a great separation performance by modeling the power spectrograms of the source signals via the nonnegative matrix factorization (NMF). Such a highly developed source model can solve the permutation problem of the frequency-domain BSS to a large extent, which is the reason for the excellence of ILRMA. In this paper, we further improve the separation performance of ILRMA by additionally considering the general structure of spectrograms, which is called consistency, and hence, we call the proposed method Consistent ILRMA. Since a spectrogram is calculated by an overlapping window (and a window function induces spectral smearing called main- and side-lobes), the time-frequency bins depend on each other. In other words, the time-frequency components are related to each other via the uncertainty principle. Such co-occurrence among the spectral components can function as an assistant for solving the permutation problem, which has been demonstrated by a recent study. On the basis of these facts, we propose an algorithm for realizing Consistent ILRMA by slightly modifying the original algorithm. Its performance was extensively evaluated through experiments performed with various window lengths and shift lengths. The results indicated several tendencies of the original and proposed ILRMA that include some topics not fully discussed in the literature. For example, the proposed Consistent ILRMA tends to outperform the original ILRMA when the window length is sufficiently long compared to the reverberation time of the mixing system.

Matching pursuit-based sparse spectral analysis: Estimating frequency-dependent anomalies from nonstationary seismic data

Spectral decomposition has been widely used to detect frequency-dependent anomalies associated with hydrocarbons. By ignoring the time-variant feature of the frequency content of individual reflected wavelets, we have adopted a sparse time-frequency spectrum and developed a matching pursuit-based sparse spectral analysis (MP-SSA) method to estimate the sparse time-frequency representation of the seismic data. Further, we evaluate a generalized nonstationary convolution model concerning propagation attenuation and frequency-dependent reflectivity, and we mathematically evaluate the sparse time-frequency spectrum of the nonstationary seismic data as being equal to the product of the Fourier spectrum of the source wavelet, frequency-dependent reflection coefficient, and the cumulative attenuation during seismic wave propagation. Therefore, the reflectivity spectrum, which is a combination of the frequency-dependent reflectivity and the propagation attenuation, can be determined by dividing the sparse time-frequency spectrum of the seismic data by the Fourier spectrum of the source wavelet. Application of the matching pursuit-based decomposition methods to synthetic nonstationary convolutional data illustrates that the adopted MP-SSA spectrum shows a higher time resolution than the matching pursuit-based Wigner-Ville distribution and the matching pursuit-based instantaneous spectral analysis spectra. Notably, the MP-SSA method can avoid spectral smearing, which may introduce distortions to the frequency-dependent anomaly estimation. Application of the amplitude versus frequency analysis based on MP-SSA to field data illustrates the potential of using the sparse reflectivity spectral intercept and gradient to detect the hydrocarbon reservoirs.

A computational study to model the effect of electrode-to-auditory nerve fiber distance on spectral resolution in cochlear implant.

Spectral ripple discrimination (SRD) has been widely used to evaluate the spectral resolution in cochlear implant (CI) recipients based on its strong correlation with speech perception performance. However, despite its usefulness for predicting speech perception outcomes, SRD performance exhibits large across-subject variabilities even among subjects implanted with the same CIs and sound processors. The potential factors of this observation include current spread, nerve survival, and CI mapping. Previous studies have found that the spectral resolution reduces with increasing distance of the stimulation electrode from the auditory nerve fibers (ANFs), attributable to increasing current spread. However, it remains unclear whether the spread of excitation is the only cause of the observation, or whether other factors such as temporal interaction also contribute to it. In this study, we used a computational model to investigate channel interaction upon non-simultaneous stimulation with respect to the electrode–ANF distance, and evaluated the SRD performance for five electrode–ANF distances. The SRD performance was determined based on the similarity between two neurograms in response to standard and inverted stimuli and used to evaluate the spectral resolution in the computational model. The spread of excitation was observed to increase with increasing electrode–ANF distance, consistent with previous findings. Additionally, the preceding pulses delivered from neighboring channels induced a channel interaction that either inhibited or facilitated the neural responses to subsequent pulses depending on the electrode–ANF distance. The SRD performance was also found to decrease with increasing electrode–ANF distance. The findings of this study suggest that variation of the neural responses (inhibition or facilitation) with the electrode–ANF distance in CI users may cause spectral smearing, and hence poor spectral resolution. A computational model such as that used in this study is a useful tool for understanding the neural factors related to CI outcomes, such as cannot be accomplished by behavioral studies alone.

Precompensating for spread of excitation in a cochlear implant coding strategy

Cochlear implant users’ limited ability to understand speech in noisy environments has been linked to the poor spatial resolution and the high degree of spectral smearing associated with the spread of neural excitation. A sound coding algorithm that aims to improve the spectro-temporal representation of the sound signal at the implanted ear by precompensating the electrical stimulation for the spread of excitation is presented in this study. The spread precompensation algorithm was integrated into the standard clinical advanced combination encoder (ACE) strategy and the resulting strategy was called SPACE. SPACE was evaluated acutely with a group of six implant users and was compared to their daily used ACE strategy in terms of preference rating and speech recognition in four-talker babble and stationary speech-shaped noise. While no significant differences in preference rating were observed, speech recognition in four-talker babble was improved by SPACE processing. Analysis of the group results revealed a significant improvement in mean speech reception threshold (SRT) over the ACE strategy of 1.4 dB in four-talker babble, whereas the difference of 0.9 dB in stationary noise did not reach statistical significance. Assessment of individual differences showed that four out of six listeners obtained significant SRT improvements with SPACE and that no subject scored significantly worse compared to ACE. The results suggest that the proposed sound coding strategy has the potential to improve speech perception for cochlear implant users in challenging listening situations.

Approximations to the Voice of a Cochlear Implant: Explorations With Single-Sided Deaf Listeners.

Fourteen single-sided deaf listeners fit with an MED-EL cochlear implant (CI) judged the similarity of clean signals presented to their CI and modified signals presented to their normal-hearing ear. The signals to the normal-hearing ear were created by (a) filtering, (b) spectral smearing, (c) changing overall fundamental frequency (F0), (d) F0 contour flattening, (e) changing formant frequencies, (f) altering resonances and ring times to create a metallic sound quality, (g) using a noise vocoder, or (h) using a sine vocoder. The operations could be used singly or in any combination. On a scale of 1 to 10 where 10 was a complete match to the sound of the CI, the mean match score was 8.8. Over half of the matches were 9.0 or higher. The most common alterations to a clean signal were band-pass or low-pass filtering, spectral peak smearing, and F0 contour flattening. On average, 3.4 operations were used to create a match. Upshifts in formant frequencies were implemented most often for electrode insertion angles less than approximately 500°. A relatively small set of operations can produce signals that approximate the sound of the MED-EL CI. There are large individual differences in the combination of operations needed. The sound files in Supplemental Material approximate the sound of the MED-EL CI for patients fit with 28-mm electrode arrays.

An examination of the continuous wavelet transform for volcano-seismic spectral analysis

Volcanoes produce widely varying seismic signals due to the presence of complex and non-linear physical processes. The temporal distribution of seismicity at volcanoes ranges from individual transients to swarms of many small events and protracted volcanic tremor. The spectral range of volcanic signals is unequivocally broadband, with coincident high (>20 Hz) and very low (down to periods of hundreds of seconds) frequency signals frequently observed at many volcanic systems. As such, interpretations of volcano-seismic source and process require suitable characterisation in the time-frequency (T-F) domain. The adoption of automated approaches to routine seismic processing at volcanoes also creates the need to evaluate how we suitably extract discriminatory features of interest from such diverse volcano-seismic signals.Here we assess the performance of the continuous wavelet transform (CWT) for spectral representations of volcano-seismic signals. The localisation property of wavelet transforms gives the CWT a distinct advantage over commonly used moving-window Fourier transforms, enabling it to capture sharp changes in signal and represent signals over a wide range of timescales. Examination of seismic data for typical volcano-seismic phenomena, such as volcano-tectonic earthquakes (VTs), shows that CWT scalograms have better T-F resolution across broader frequency ranges than Fourier transform spectrograms, which suffer from greater spectral smearing in the time domain at higher frequencies. The inherent log-scale representation of CWT scalograms is also better suited for detection and representation of very-long-period (VLP) signals and for distinguishing volcanic signals from ambient microseismic noise.When applied to seismic data from Santiaguito volcano in Guatemala, CWT analysis reveals pre- and syn-eruptive signals across a wide range of frequency bands, ranging from 600 s to 50 Hz, with ultra-long-period signals (ULPs; 30 to 600 s) detected on instruments up to 1.9 km from the active vent, which is beyond the range of previously detected ULPs at this volcanic system. The CWT scalogram conveniently represents these simultaneous syn-eruptive spectral features in a single plot, which can aid exploratory analysis and inform source models. Furthermore, the ‘edge detection’ capabilities of the CWT accurately identify sharp changes in the raw signal over the VLP-ULP frequency range (5 to 600+ s), thought to represent sudden deflation associated with eruption, providing a useful tool for ‘picking’ explosive eruptions. The addition of an average wavelet energy distribution to CWT scalograms, which reveals the average energy across the whole signal at each wavelet scale, is also useful for characterising spectral content and identifying spectral peaks, as its smooth appearance is easier to interpret than FFT spectral amplitude plots.We conclude that wavelet transform methods are underutilised in volcano seismology, where their T-F localisation properties would be particularly well-suited, and suggest potential applications in terms of automated event detection and classification.

On the measurement of seismic traveltime changes in the time–frequency domain with wavelet cross-spectrum analysis

SUMMARY The spatial distribution of temporal variations in seismic wavespeed is key to understanding the sources and physical mechanisms of various geophysical processes. The imaging of wavespeed changes requires accurate measurements of traveltime delays with both high lapse-time and frequency resolutions. However, traditional methods for time-shift estimation suffer from their limited resolutions. In this paper we propose a new approach, the wavelet method, to measure the traveltime changes in the time–frequency domain. This method is based on wavelet cross-spectrum analysis, and can provide optimal time–frequency joint resolution while being computationally efficient. It can deal not only with coda but also dispersive surface waves even in the presence of cycle skipping. Using synthetic coda, we show that the wavelet method can retrieve traveltime shifts more stably and accurately than traditional methods. An application at Salton Sea Geothermal Field indicates that the wavelet method is less affected by spectral smearing and better discriminates dv/v variations at different frequencies. Furthermore, upon investigations on synthetic coda, we illustrate that the bias on dv/v measurements due to changes in source frequency content is likely to be negligible, either with traditional methods or with the new wavelet method. The wavelet method sheds lights on applications of seismic interferometry that aim to locate changes in space.

Impact of room acoustic parameters on speech and music perception among participants with cochlear implants

ObjectivesBesides numerous other factors, listening experience with cochlear implants is substantially impaired by room acoustics. Even for persons without hearing impairment, the perception of auditory scenes, for example, concerning speech intelligibility, acoustic quality or audibility, is considerably influenced by room acoustics. For CI users, complex listening environments are usually associated with heavy losses.The aim of the present study was to determine room acoustic criteria that particularly influence speech pleasantness for CI users. DesignAccordingly, speech material of the Oldenburg Sentence Test (Oldenburger Satztest, OLSA) as well as basic music material (major and minor triads) were auralized using the software Auratorium which allows auralization of simulated rooms. The constructed rooms for speech stimuli were based on the standard DIN 18041:2016–03 concerning acoustic quality in rooms, the binding standard referred to by room acoustic consultants in Germany, which also includes specifications for inclusive applications in schools. For the music perception tests, two typical concert halls of different sizes were modelled. The auralized test stimuli were unilaterally presented to 10 CI users via their auxiliary input as well as to 18 participants with typical hearing via headphones (control group). Speech pleasantness was evaluated using modified MUSHRA tests. Concerning music perception, chord discrimination was tested using paired comparisons. ResultsA strong preference of small source to listener distances by CI users was found, but no significant preference for room acoustic attenuation which exceeded the recommended for inclusive applications in schools. The analyses of the energy-time-structures suggested that a dense concentration of early reflections makes a beneficial impact on CI listeners’ pleasantness ratings. Music materials were distinguished more consistently without any room acoustic impact, while any room acoustic impact led to performance close to chance level. This effect is probably due to spectral smearing effects caused by reverberation. ConclusionsThese results suggest that in terms of pleasantness of speech, for CI-users, source-to-listener distance is the more influential parameter than room attenuation which goes beyond the German standard recommendation. Reflections from which CI users can benefit seem to occur much earlier than those from which NH listeners benefit. Future studies on chord discrimination concerning room acoustics are needed.