On causality and aural impulse responses synthesized using the inverse discrete Fourier transform.

Causality is a fundamental property of physical systems and dictates that a time impulse response characterizing any causal system must be one-sided. However, when synthesized using the inverse discrete Fourier transform (IDFT) of a corresponding band-limited numerical frequency transfer function, several papers have reported two-sided IDFT impulse responses of ear-canal reflectance and ear-probe source parameters. Judging from the literature on ear-canal reflectance, the significance and source of these seemingly non-physical negative-time components appear largely unclear. This paper summarizes and clarifies different sources of negative-time components through ideal and practical examples and illustrates the implications of constraining aural IDFT impulse responses to be one-sided. Two-sided IDFT impulse responses, derived from frequency-domain measurements of physical systems, normally occur due to the two-sided properties of the discrete Fourier transform. Still, reflectance IDFT impulse responses may serve a number of practical and diagnostic purposes.

Understanding Interdependencies between Mechanical Velocity and Electrical Voltage in Electromagnetic Micromixers.

Micromixers are critical components in the lab-on-a-chip or micro total analysis systems technology found in micro-electro-mechanical systems. In general, the mixing performance of the micromixers is determined by characterising the mixing time of a system, for example the time or number of circulations and vibrations guided by tracers (i.e., fluorescent dyes). Our previous study showed that the mixing performance could be detected solely from the electrical measurement. In this paper, we employ electromagnetic micromixers to investigate the correlation between electrical and mechanical behaviours in the mixer system. This work contemplates the "anti-reciprocity" concept by providing a theoretical insight into the measurement of the mixer system; the work explains the data interdependence between the electrical point impedance (voltage per unit current) and the mechanical velocity. This study puts the electromagnetic micromixer theory on a firm theoretical and empirical basis.

Assessing the efficacy of hearing-aid amplification using a phoneme test.

Consonant-vowel (CV) perception experiments provide valuable insights into how humans process speech. Here, two CV identification experiments were conducted in a group of hearing-impaired (HI) listeners, using 14 consonants followed by the vowel /ɑ/. The CVs were presented in quiet and with added speech-shaped noise at signal-to-noise ratios of 0, 6, and 12 dB. The HI listeners were provided with two different amplification schemes for the CVs. In the first experiment, a frequency-independent amplification (flat-gain) was provided and the CVs were presented at the most-comfortable loudness level. In the second experiment, a frequency-dependent prescriptive gain was provided. The CV identification results showed that, while the average recognition error score obtained with the frequency-dependent amplification was lower than that obtained with the flat-gain, the main confusions made by the listeners on a token basis remained the same in a majority of the cases. An entropy measure and an angular distance measure were proposed to assess the highly individual effects of the frequency-dependent gain on the consonant confusions in the HI listeners. The results suggest that the proposed measures, in combination with a well-controlled phoneme speech test, may be used to assess the impact of hearing-aid signal processing on speech intelligibility.

Evaluating hearing aid amplification using idiosyncratic consonant errors.

The goal of this study is to provide a metric for evaluating a given hearing-aid insertion gain using a consonant recognition based measure. The basic question addressed is how treatment impacts phone recognition at the token level, relative to a flat insertion gain, at the most-comfortable-level (MCL). These tests are directed at fine-tuning a treatment, with the ultimate goal of improving speech perception, and to identify when a hearing level gain-based treatment degrades phone recognition. Eight subjects with hearing loss were tested under two conditions: flat-gain and a treatment insertion gain, based on subject's hearing level. The speech corpus consisted of consonant-vowel tokens at different signal to speech-weighted noise conditions, presented at the subject's MCL. The treatment caused the average score to improve for 31% of the trials and decrease for 12%. An analysis method based on the accumulated error differences was devised to quantify the benefit each individual ear received from the treatment. Using this measure, the effect of the treatment could be evaluated, providing precise characterization of idiosyncratic phone recognition. This analysis directs the audiologist toward the most susceptible subject-dependent tokens, to focus in the process of fine-tuning the insertion gain of the hearing-aid.

Generalized metamaterials: Definitions and taxonomy.

This article reviews the development of metamaterials (MM), starting from Newton's discovery of the wave equation, and ends with a discussion of the need for a technical taxonomy (classification) of these materials, along with a better defined definition of metamaterials. It is intended to be a technical definition of metamaterials, based on a historical perspective. The evolution of MMs began with the discovery of the wave equation, traceable back to Newton's calculation of the speed of sound. The theory of sound evolved to include quasi-statics (Helmholtz) and the circuit equations of Kirchhoff's circuit laws, leading to the ultimate development of Maxwell's equations and the equation for the speed of light. Be it light, or sound, the speed of the wave-front travel defines the wavelength, and thus the quasi-static (QS) approximation. But there is much more at stake than QSs. Taxonomy requires a proper statement of the laws of physics, which includes at least the six basic network postulates: (P1) causality (non-causal/acausal), (P2) linearity (non-linear), (P3) real (complex) time response, (P4) passive (active), (P5) time-invariant (time varying), and (P6) reciprocal (non-reciprocal). These six postulates are extended to include MMs.

On the method of Hunt's parameter calibration.

This note comments on the observations of Bernier et al. (2016) regarding errors in Appendix A of Kim and Allen (2013). We acknowledge that the equations in the Appendix are in error, but wish to point out that these equations were not actually used for our analysis. We appreciate their effort in pointing out the errors, and offering corrected equations.

Effects of Negative Middle Ear Pressure on Wideband Acoustic Immittance in Normal-Hearing Adults.

OBJECTIVES: Wideband acoustic immittance (WAI) measurements are capable of quantifying middle ear performance over a wide range of frequencies relevant to human hearing. Static pressure in the middle ear cavity affects sound transmission to the cochlea, but few datasets exist to quantify the relationship between middle ear transmission and the static pressure. In this study, WAI measurements of normal ears are analyzed in both negative middle ear pressure (NMEP) and ambient middle ear pressure (AMEP) conditions, with a focus on the effects of NMEP in individual ears. DESIGN: Eight subjects with normal middle ear function were trained to induce consistent NMEPs, quantified by the tympanic peak pressure (TPP) and WAI. The effects of NMEP on the wideband power absorbance level are analyzed for individual ears. Complex (magnitude and phase) WAI quantities at the tympanic membrane (TM) are studied by removing the delay due to the residual ear canal (REC) volume between the probe tip and the TM. WAI results are then analyzed using a simplified classical model of the middle ear. RESULTS: For the 8 ears presented here, NMEP has the largest and most significant effect across ears from 0.8 to 1.9 kHz, resulting in reduced power absorbance by the middle ear and cochlea. On average, NMEP causes a decrease in the power absorbance level for low- to mid-frequencies, and a small increase above about 4 kHz. The effects of NMEP on WAI quantities, including the absorbance level and TM impedance, vary considerably across ears. The complex WAI at the TM and fitted model parameters show that NMEP causes a decrease in the aggregate compliance at the TM. Estimated REC delays show little to no dependence on NMEP. CONCLUSIONS: In agreement with previous results, these data show that the power absorbance level is most sensitive to NMEP around 1 kHz. The REC effect is removed from WAI measurements, allowing for direct estimation of complex WAI at the TM. These estimates show NMEP effects consistent with an increased stiffness in the middle ear, which could originate from the TM, tensor tympani, annular ligament, or other middle ear structures. Model results quantify this nonlinear, stiffness-related change in a systematic way, that is not dependent on averaging WAI results in frequency bands. Given the variability of pressure effects, likely related to intersubject variability at AMEP, TPP is not a strong predictor of change in WAI at the TM. More data and modeling will be needed to better quantify the relationship between NMEP, WAI, and middle ear transmission.

Developmental PCB exposure increases susceptibility to audiogenic seizures in adulthood.

Developmental exposure to polychlorinated biphenyls (PCBs) causes auditory deficits. Thus, we recently conducted a study to investigate if developmental PCB exposure would exacerbate noise-induced hearing loss in adulthood. Unexpectedly, some PCB-exposed rats exhibited seizure-like behaviors when exposed to loud noise. Therefore, we conducted the current experiment to determine if adult rats perinatally exposed to PCBs are more susceptible to audiogenic seizures when tested in a standard audiogenic seizure paradigm. Adult male and female rats exposed to PCBs during gestation and lactation (0, 1, 3 or 6 mg/kg/day) and previously tested in the noise-induced hearing loss study were presented with a 100 dB noise stimulus. If they did not exhibit clonus in response to the 100 dB noise, they were exposed to a 105 dB stimulus 24-48 h later. This was followed by an 110 dB stimulus 24-48 h later if they did not exhibit clonus at 105 dB. Female and male rats exposed to either 3 or 6 mg/kg PCBs exhibited a significantly higher incidence of audiogenic seizures, shorter latency to onset of seizures, and greater severity of seizures compared to controls. Thyroxine measured in littermates at weaning was significantly lower in all PCB groups compared to controls, suggesting a potential mechanism for the increased incidence of audiogenic seizures. This is the first study to show that developmental PCB exposure increases the susceptibility to audiogenic seizures in adulthood.

Across- and within-consonant errors for isolated syllables in noise.

PURPOSE: A critical issue in assessing speech recognition involves understanding the factors that cause listeners to make errors. Models like the articulation index show that average error decreases logarithmically with increases in signal-to-noise ratio (SNR). The authors investigated (a) whether this log-linear relationship holds across consonants and for individual tokens and (b) what accounts for differences in error rates at the across- and within-consonant levels. METHOD: Listeners with normal hearing heard CV syllables (16 consonants and 4 vowels) spoken by 14 talkers, presented at 6 SNRs. Stimuli were presented randomly, and listeners indicated which syllable they heard. RESULTS: The log-linear relationship between error and SNR holds across consonants but breaks down at the token level. These 2 sources of variability (across- and within-consonant factors) explain the majority of listeners' errors. Moreover, simply adjusting for differences in token-level error thresholds explains 62% of the variability in listeners' responses. CONCLUSIONS: These results demonstrate that speech tests must control for the large variability among tokens, not average across them, as is commonly done in clinical practice. Accounting for token-level differences in error thresholds with listeners with normal hearing provides a basis for tests designed to diagnostically evaluate individual differences with listeners with hearing impairment.

Effect of calibration method on distortion-product otoacoustic emission measurements at and around 4 kHz.

OBJECTIVES: Distortion-product otoacoustic emissions (DPOAEs) collected after sound pressure level (SPL) calibration are susceptible to standing waves that affect measurements at the plane of the probe microphone due to overlap of incident and reflected waves. These standing-wave effects can be as large as 20 dB, and may affect frequencies both above and below 4 kHz. It has been shown that forward pressure level (FPL) calibration minimizes standing-wave effects by isolating the forward-propagating component of the stimulus. Yet, previous work has failed to demonstrate more than a small difference in test performance and behavioral-threshold prediction with DPOAEs after SPL and FPL calibration. One potential limitation in prior studies is that measurements were restricted to octave and interoctave frequencies; as a consequence, data were not necessarily collected at the standing-wave null frequency. In the present study, DPOAE responses were measured with f2 set to each participant's standing-wave frequency in an effort to increase the possibility that differences in test performance and threshold prediction would be observed for SPL and FPL calibration methods. DESIGN: Data were collected from 42 normal-hearing participants and 93 participants with hearing loss. DPOAEs were measured with f2 set to 4 kHz and at each participant's notch frequency after SPL and FPL calibration. DPOAE input/output functions were obtained from -10 to 80 dB in 5 dB steps for each calibration/stimulus condition. Test performance was evaluated using clinical decision theory. Both area under receiver operating characteristic curves for all stimulus levels and cumulative distributions when L2 = 50 dB (a level at which the best performance was observed regardless of calibration method) were used to evaluate the accuracy with which auditory status was determined. A bootstrap procedure was used to evaluate the significance of the differences in test performance between SPL and FPL calibrations. DPOAE predictions of behavioral threshold were evaluated by correlating actual behavioral thresholds and predicted thresholds using a multiple linear regression model. RESULTS: First, larger DPOAE levels were measured after SPL calibration than after FPL calibration, which demonstrated the expected impact of standing waves. Second, for both FPL and SPL calibration, test performance was best for moderate stimulus levels. Third, differences in test performance between calibration methods were evident at low- and high-stimulus levels. Fourth, there were small but statistically significant improvements in test performance after FPL calibration for clinically relevant conditions. Fifth, calibration method had no effect on threshold prediction. CONCLUSIONS: Standing waves after SPL calibration have an impact on DPOAE levels. Although the effect of calibration method on test performance was small, test performance was better after FPL calibration than after SPL calibration. There was no effect of calibration method on predictions of behavioral threshold.

Within-consonant perceptual differences in the hearing impaired ear.

The consonant recognition of 17 ears with sensorineural hearing loss is evaluated for 14 consonants /p, t, k, f, s, ∫, b, d, g, v, z, 3, m, n/+/a/, under four speech-weighted noise conditions (0, 6, 12 dB SNR, quiet). One male and one female talker were chosen for each consonant, resulting in 28 total consonant-vowel test tokens. For a given consonant, tokens by different talkers were observed to systematically differ, in both the robustness to noise and/or the resulting confusion groups. Such within-consonant token differences were observed for over 60% of the tested consonants and all HI ears. Only when HI responses are examined on an individual token basis does one find that the error may be limited to a small subset of tokens with confusion groups that are restricted to fewer than three confusions on average. Averaging different tokens of the same consonant can raise the entropy of a listener's responses (i.e., the size of the confusion group), causing the listener to appear to behave in a less systematic way. Quantifying these token differences provides insight into HI perception of speech under noisy conditions and characterizes each listener's hearing impairment.

Investigation of bacterial biofilm in the human middle ear using optical coherence tomography and acoustic measurements.

Children with chronic otitis media (OM) often have conductive hearing loss which results in communication difficulties and requires surgical treatment. Recent studies have provided clinical evidence that there is a one-to-one correspondence between chronic OM and the presence of a bacterial biofilm behind the tympanic membrane (TM). Here we investigate the acoustic effects of bacterial biofilms, confirmed using optical coherence tomography (OCT), in adult ears. Non-invasive OCT images are collected to visualize the cross-sectional structure of the middle ear, verifying the presence of a biofilm behind the TM. Wideband measurements of acoustic reflectance and impedance (0.2-6 [kHz]) are used to study the acoustic properties of ears with confirmed bacterial biofilms. Compared to known acoustic properties of normal middle ears, each of the ears with a bacterial biofilm has an elevated power reflectance in the 1 to 3 [kHz] range, corresponding to an abnormally small resistance (real part of the impedance). These results provide assistance for the clinical diagnosis of a bacterial biofilm, which could lead to improved treatment of chronic middle ear infection and further understanding of the impact of chronic OM on conductive hearing loss. This article is part of a special issue entitled "MEMRO 2012".

Two-port network analysis and modeling of a balanced armature receiver.

Models for acoustic transducers, such as loudspeakers, mastoid bone-drivers, hearing-aid receivers, etc., are critical elements in many acoustic applications. Acoustic transducers employ two-port models to convert between acoustic and electromagnetic signals. This study analyzes a widely-used commercial hearing-aid receiver ED series, manufactured by Knowles Electronics, Inc. Electromagnetic transducer modeling must consider two key elements: a semi-inductor and a gyrator. The semi-inductor accounts for electromagnetic eddy-currents, the 'skin effect' of a conductor (Vanderkooy, 1989), while the gyrator (McMillan, 1946; Tellegen, 1948) accounts for the anti-reciprocity characteristic [Lenz's law (Hunt, 1954, p. 113)]. Aside from Hunt (1954), no publications we know of have included the gyrator element in their electromagnetic transducer models. The most prevalent method of transducer modeling evokes the mobility method, an ideal transformer instead of a gyrator followed by the dual of the mechanical circuit (Beranek, 1954). The mobility approach greatly complicates the analysis. The present study proposes a novel, simplified and rigorous receiver model. Hunt's two-port parameters, the electrical impedance Ze(s), acoustic impedance Za(s) and electro-acoustic transduction coefficient Ta(s), are calculated using ABCD and impedance matrix methods (Van Valkenburg, 1964). The results from electrical input impedance measurements Zin(s), which vary with given acoustical loads, are used in the calculation (Weece and Allen, 2010). The hearing-aid receiver transducer model is designed based on energy transformation flow [electric→ mechanic→ acoustic]. The model has been verified with electrical input impedance, diaphragm velocity in vacuo, and output pressure measurements. This receiver model is suitable for designing most electromagnetic transducers and it can ultimately improve the design of hearing-aid devices by providing a simplified yet accurate, physically motivated analysis. This article is part of a special issue entitled "MEMRO 2012".

Characterizing the ear canal acoustic impedance and reflectance by pole-zero fitting.

This study characterizes middle ear complex acoustic reflectance (CAR) and impedance by fitting poles and zeros to real-ear measurements. The goal of this work is to establish a quantitative connection between pole-zero locations and the underlying physical properties of CAR data. Most previous studies have analyzed CAR magnitude; while the magnitude accounts for reflected power, it does not encode latency information. Thus, an analysis that studies the real and imaginary parts of the data together, being more general, should be more powerful. Pole-zero fitting of CAR data is examined using data compiled from various studies, dating back to Voss and Allen (1994). Recent CAR measurements were taken using the Mimosa Acoustics HearID system, which makes complex acoustic impedance and reflectance measurements in the ear canal over a 0.2-6.0 [kHz] frequency range. Pole-zero fits to measurements over this range are achieved with an average RMS relative error of less than 3% with 12 poles. Factoring the reflectance fit into its all-pass and minimum-phase components estimates the effect of the residual ear canal, allowing for comparison of the eardrum impedance and admittance across measurements. It was found that individual CAR magnitude variations for normal middle ears in the 1-4 [kHz] range often give rise to closely-placed pole-zero pairs, and that the locations of the poles and zeros in the s-plane may systematically differ between normal and pathological middle ears. This study establishes a methodology for examining the physical and mathematical properties of CAR using a concise parametric model. Pole-zero modeling accurately parameterizes CAR data, providing a foundation for detection and identification of middle ear pathologies. This article is part of a special issue entitled "MEMRO 2012".

A psychoacoustic method for studying the necessary and sufficient perceptual cues of American English fricative consonants in noise.

In a previous study on plosives, the 3-Dimensional Deep Search (3DDS) method for the exploration of the necessary and sufficient cues for speech perception was introduced (Li et al., (2010). J. Acoust. Soc. Am. 127(4), 2599-2610). Here, this method is used to isolate the spectral cue regions for perception of the American English fricatives /∫, 3, s, z, f, v, θ, δ in time, frequency, and intensity. The fricatives are analyzed in the context of consonant-vowel utterances, using the vowel /α/. The necessary cues were found to be contained in the frication noise for /∫, 3, s, z, f, v/. 3DDS analysis isolated the cue regions of /s, z/ between 3.6 and 8 [kHz] and /∫, 3/ between 1.4 and 4.2 [kHz]. Some utterances were found to contain acoustic components that were unnecessary for correct perception, but caused listeners to hear non-target consonants when the primary cue region was removed; such acoustic components are labeled "conflicting cue regions." The amplitude modulation of the high-frequency frication region by the fundamental F0 was found to be a sufficient cue for voicing. Overall, the 3DDS method allows one to analyze the effects of natural speech components without initial assumptions about where perceptual cues lie in time-frequency space or which elements of production they correspond to.

The influence of stop consonants' perceptual features on the Articulation Index model.

Studies on consonant perception under noise conditions typically describe the average consonant error as exponential in the Articulation Index (AI). While this AI formula nicely fits the average error over all consonants, it does not fit the error for any consonant at the utterance level. This study analyzes the error patterns of six stop consonants /p, t, k, b, d, g/ with four vowels (/α/, /ε/, /I/, /ae/), at the individual consonant (i.e., utterance) level. The findings include that the utterance error is essentially zero for signal to noise ratios (SNRs) at least -2 dB, for >78% of the stop consonant utterances. For these utterances, the error is essentially a step function in the SNR at the utterance's detection threshold. This binary error dependence is consistent with the audibility of a single binary defining acoustic feature, having zero error above the feature's detection threshold. Also 11% of the sounds have high error, defined as ≥ 20% for SNRs greater than or equal to -2 dB. A grand average across many such sounds, having a natural distribution in thresholds, results in the error being exponential in the AI measure, as observed. A detailed analysis of the variance from the AI error is provided along with a Bernoulli-trials analysis of the statistical significance.

Reflectance of acoustic horns and solution of the inverse problem.

A method is described for solving the inverse problem of determining the profile of an acoustic horn when time-domain reflectance (TDR) is known only at the entrance. The method involves recasting Webster's horn equation in terms of forward and backward propagating wave variables. An essential feature of this method is a requirement that the backward propagating wave be continuous at the wave-front at all locations beyond the entrance. Derivation of the inverse solution raises questions about the meaning of causality in the context of wave propagation in non-uniform tubes. Exact reflectance expressions are presented for infinite exponential, conical and parabolic horns based on exact solutions of the horn equation. Diameter functions obtained with the inverse solution are a good match to all three horn profiles.

Perceptual effects of plosive feature modification.

In the 1970-1980's, a number of papers explored the role of the transitional and burst features in consonant-vowel context. These papers left unresolved the relative importance of these two acoustic cues. This research takes advantage of refined signal processing methods, allowing for the visualization and modification of acoustic details. This experiment explores the impact of modifying the strength of the acoustic burst feature on the recognition scores P(c)(SNR) (function of the signal-to-noise ratio), for four plosive sounds /ta, ka, da, ga/. These results show high correlations between the relative burst intensity and the scores P(c)(SNR). Based on this correlation, one must conclude that these bursts are the primary acoustic cues used for the identification of these four consonants. This is in contrast to previous experiments, which used less precise methods to manipulate speech, and observe complex relationships between the scores, bursts and transition cues. In cases where the burst feature is removed entirely, it is shown that naturally existing conflicting acoustic features dominate the score. These observations seem directly inconsistent with transition cues playing a role: if the transition cues were important, they would dominate over low-level conflicting burst cues. These limited results arguably rule out the concept of redundant cues.

Relationship between consonant recognition in noise and hearing threshold.

PURPOSE: Although poorer understanding of speech in noise by listeners who are hearing-impaired (HI) is known not to be directly related to audiometric hearing threshold, HT (f), grouping HI listeners with HT (f) is widely practiced. In this article, the relationship between consonant recognition and HT (f) is considered over a range of signal-to-noise ratios (SNRs). METHOD: Confusion matrices (CMs) from 25 HI ears were generated in response to 16 consonant-vowel syllables presented at 6 different SNRs. Individual differences scaling (INDSCAL) was applied to both feature-based matrices and CMs in order to evaluate the relationship between HT (f) and consonant recognition among HI listeners. RESULTS: The results showed no predictive relationship between the percent error scores (Pe) and HT (f) across SNRs. The multiple regression models showed that the HT (f) accounted for 39% of the total variance of the slopes of the Pe. Feature-based INDSCAL analysis showed consistent grouping of listeners across SNRs, but not in terms of HT (f). Systematic relationship between measures was also not defined by CM-based INDSCAL analysis across SNRs. CONCLUSIONS: HT (f) did not account for the majority of the variance (39%) in consonant recognition in noise when the complete body of the CM was considered.

A psychoacoustic method to find the perceptual cues of stop consonants in natural speech.

Synthetic speech has been widely used in the study of speech cues. A serious disadvantage of this method is that it requires prior knowledge about the cues to be identified in order to synthesize the speech. Incomplete or inaccurate hypotheses about the cues often lead to speech sounds of low quality. In this research a psychoacoustic method, named three-dimensional deep search (3DDS), is developed to explore the perceptual cues of stop consonants from naturally produced speech. For a given sound, it measures the contribution of each subcomponent to perception by time truncating, highpass/lowpass filtering, or masking the speech with white noise. The AI-gram, a visualization tool that simulates the auditory peripheral processing, is used to predict the audible components of the speech sound. The results are generally in agreement with the classical studies that stops are characterized by a short duration burst followed by a F2 transition, suggesting the effectiveness of the 3DDS method. However, it is also shown that /ba/ and /pa/ may have a wide band click as the dominant cue. F2 transition is not necessary for the perception of /ta/ and /ka/. Moreover, many stop consonants contain conflicting cues that are characteristic of competing sounds. The robustness of a consonant sound to noise is determined by the intensity of the dominant cue.