Acoustic Input Research Articles

Audiovisual training rapidly reduces potentially hazardous perceptual errors caused by earplugs

Our ears capture sound from all directions but do not encode directional information explicitly. Instead, subtle acoustic features associated with unique sound source locations must be learned through experience. Surprisingly, aspects of this mapping process remain highly plastic throughout adulthood: Adult human listeners can accommodate acutely modified acoustic inputs (“new ears”) over a period of a few weeks to recover near-normal sound localization, and this process can be accelerated with explicit training. Here we evaluated the extent of such plasticity given only transient exposure to distorted inputs. Distortions were produced via earplugs, which severely degrade sound localization performance, constraining their usability in real-world settings that require accurate directional hearing. Localization was measured over a period of ten weeks. Provision of feedback via simple paired auditory and visual stimuli led to a rapid decrease in the occurrence of large errors (responses >|±30°| from target) despite only once-weekly exposure to the altered inputs. Moreover, training effects generalized to untrained sound source locations. Lesser but qualitatively similar improvements were observed in a group of subjects that did not receive explicit feedback. In total, data demonstrate that even transient exposure to altered spatial acoustic information is sufficient for meaningful perceptual improvement (i.e., chronic exposure is not required), offering insight on the nature and time course of perceptual learning in the context of spatial hearing. Data also suggest that the large and potentially hazardous errors in localization caused by earplugs can be mitigated with appropriate training, offering a practical means to increase their usability.

Acoustofluidic separation of microparticles: a numerical study

In this paper, two-dimensional simulations are performed to separate polystyrene (PS) and polymethyl methacrylate (PMMA) particles suspended in water using an acoustic field. The acoustic waves are generated by two aluminum interdigitated transducers (IDTs) over a piezoelectric substrate. The effect of input power, inlet flow rate, acoustic frequency, and distance between IDTs and channel on separation efficiency is evaluated by considering channel thickness. It is observed that the separation efficiency is enhanced by increasing acoustic frequency and input power. Also, as the inlet flow rate and distance between IDTs and channel decrease, the separation efficiency increases. The optimum values for input power, flow rate, frequency, and distance are 1.4 W, 0.2 ml/min, 5 MHz, and 75 µm, respectively, and a maximum separation of 88% is achieved.

Voxelwise Encoding Models Show That Cerebellar Language Representations Are Highly Conceptual.

There is a growing body of research demonstrating that the cerebellum is involved in language understanding. Early theories assumed that the cerebellum is involved in low-level language processing. However, those theories are at odds with recent work demonstrating cerebellar activation during cognitive tasks. Using natural language stimuli and an encoding model framework, we performed an fMRI experiment on 3 men and 2 women, where subjects passively listened to 5 h of natural language stimuli, which allowed us to analyze language processing in the cerebellum with higher precision than previous work. We used these data to fit voxelwise encoding models with five different feature spaces that span the hierarchy of language processing from acoustic input to high-level conceptual processing. Examining the prediction performance of these models on separate BOLD data shows that cerebellar responses to language are almost entirely explained by high-level conceptual language features rather than low-level acoustic or phonemic features. Additionally, we found that the cerebellum has a higher proportion of voxels that represent social semantic categories, which include “social” and “people” words, and lower representations of all other semantic categories, including “mental,” “concrete,” and “place” words, than cortex. This suggests that the cerebellum is representing language at a conceptual level with a preference for social information.SIGNIFICANCE STATEMENT Recent work has demonstrated that, beyond its typical role in motor planning, the cerebellum is implicated in a wide variety of tasks, including language. However, little is known about the language representations in the cerebellum, or how those representations compare to cortex. Using voxelwise encoding models and natural language fMRI data, we demonstrate here that language representations are significantly different in the cerebellum compared with cortex. Cerebellum language representations are almost entirely semantic, and the cerebellum contains overrepresentation of social semantic information compared with cortex. These results suggest that the cerebellum is not involved in language processing per se, but cognitive processing more generally.

Temporary Unilateral Hearing Loss Impairs Spatial Auditory Information Processing in Neurons in the Central Auditory System.

Temporary conductive hearing loss (CHL) can lead to hearing impairments that persist beyond resolution of the CHL. In particular, unilateral CHL leads to deficits in auditory skills that rely on binaural input (e.g., spatial hearing). Here, we asked whether single neurons in the auditory midbrain, which integrate acoustic inputs from the two ears, are altered by a temporary CHL. We introduced 6 weeks of unilateral CHL to young adult chinchillas via foam earplug. Following CHL removal and restoration of peripheral input, single-unit recordings from inferior colliculus (ICC) neurons revealed the CHL decreased the efficacy of inhibitory input to the ICC contralateral to the earplug and increased inhibitory input ipsilateral to the earplug, effectively creating a higher proportion of monaural responsive neurons than binaural. Moreover, this resulted in a ∼10 dB shift in the coding of a binaural sound location cue (interaural-level difference, ILD) in ICC neurons relative to controls. The direction of the shift was consistent with a compensation of the altered ILDs due to the CHL. ICC neuron responses carried ∼37% less information about ILDs after CHL than control neurons. Cochlear peripheral-evoked responses confirmed that the CHL did not induce damage to the auditory periphery. We find that a temporary CHL altered auditory midbrain neurons by shifting binaural responses to ILD acoustic cues, suggesting a compensatory form of plasticity occurring by at least the level of the auditory midbrain, the ICC.

Acoustically Driven Sorption Heat Pump

Recent years have seen a dramatic rise in global cooling demand, driven by economic growth and climate change, and resulting in an increasing share of the total electric power consumption. Meanwhile, the ubiquitous vapor-compression air conditioners use refrigerants, which contribute greatly to global emission of greenhouse gases. In order to reduce the strain on electric grids, heat-driven technologies must be developed. Here, an acoustic driven sorption cooling device is examined experimentally and theoretically. The device can potentially utilize heat or electricity as a power input, uses environmentally benign working fluids, and offers simple, reliable construction with little to no moving parts. The results demonstrate the sorption-mediated, time-averaged heat-transfer mechanism, driven by the acoustic field. An unoptimized, proof-of-concept device is operated using a mixture of atmospheric air and either water or methanol, with cordierite and zeolite sorbents. The device is able to achieve temperature differentials $>30{\phantom{\rule{0.1em}{0ex}}}^{\ensuremath{\circ}}\mathrm{C}$. Moreover, a coefficient of performance of approximately 3 (based on the acoustic power input) is achieved at a temperature difference of $10{\phantom{\rule{0.1em}{0ex}}}^{\ensuremath{\circ}}\mathrm{C}$. Theoretical calculations provide an outlook on the operation of such technology, compared with existing cooling technologies, demonstrating its potential for achieving high efficiencies. Finally, prospects for further development are discussed.

Understanding dual-frequency ultrasonic melt treatment on grain refinement and mechanical properties improvement of AZ80 magnesium alloy: experiment and simulation

This work investigated the acoustic pressure distribution and relevant cavitation area of the dual-frequency ultrasonic field (DUF) in magnesium melt using numerical simulation. Associated experiments were also implemented to understand the grain refinement of DUF. DUF weakens the acoustic attenuation and then enlarges the potential cavitation area than the single-frequency ultrasonic field (SUF). Such improvement promotes its grain refinement efficiency, which is 17.7% and 24% higher than 15 kHz and 20 kHz SUF, respectively. Both yield strength and ultimate tensile strength are improved by DUF melt treatment. The improvement of mechanical properties for ultrasonic melt treated alloy is attributed to the grain refinement and the texture evolution. To optimize the grain refinement of DUF melt treatment, choosing the appropriate input acoustic pressure ratio is important. Under the premise of relevant symmetrical distribution of the cavitation area, increasing the acoustic pressure input for 15 kHz ultrasonic is beneficial to improve the grain refinement efficiency.

Damping of vibration-isolated structures: A review

Vibration presents a major challenge to advanced experiments in physics and life sciences, as well as to precise manufacturing processes. A vibration-isolated platform had become an indispensable element of precision experimental and manufacturing systems. Ideally, the platform should behave as an absolutely rigid body; unfortunately, absolutely rigid bodies do not exist: any structure deviates from the rigid behavior at its resonance frequencies. Resonance vibrations of the platform carrying precision optomechanical or acoustical equipment can be excited by acoustical inputs, residual vibrations coming from the floor through vibration isolators, and atmospheric turbulence. These vibrations must be mitigated by dissipation of mechanical energy, or damping. This paper summarizes current methods and achievements in active and passive damping of optical tables and breadboards, applicable also to other types of structures. Dynamic response of an isolated platform is analyzed. Physical principles of active damping systems, multiple tuned dynamic absorbers, and elastomeric constrained-layer damping links are presented; various designs of damping devices are considered, and their operation illustrated by experimental results; advantages and shortcomings of each method are discussed.

A naturalistic approach to studying temporal processing during music performance

In recent years, the push to embrace naturalistic stimuli over artificial designs has enriched what we know about the neural underpinnings of human attention, memory, and communication in real life. Previous work using natural stories scrambled (at the word, sentence, and paragraph level) has revealed a hierarchy of brain regions that organize natural acoustic input at these different timescales. While this approach has advanced our understanding of language processing, many fewer studies to date have explored the neural underpinnings of music perception, let alone music production, in naturalistic settings. In our novel paradigm, we asked expert pianists to play musical pieces, scrambled at different timescales (measure, phrase, section) on a non-ferromagnetic piano keyboard inside the fMRI scanner. This dataset provides unprecedented access to expert musicians’ brains starting from their first exposure to a novel piece and continuing over the course of learning to play it. We found distinct patterns of tuning to musical timescales across several clusters of brain regions (e.g., sensory/motor, parietal, and frontal/memory). We also found that musical predictability impacts functional connectivity between auditory, motor, and higher-order regions during performance. Finally, we applied several machine learning analyses to understand how the brain dynamically represents acoustic and musical features.

Calculation of the trumpet impedance with various mouthpieces

This project explored computationally how mouthpieces of various dimensions affect the acoustic input impedance for the entire trumpet. Theimpedance was calculated using a cone approximation. The trumpet was divided into cones shorter than the wavelengths considered. The measurements for the trumpet were taken from the literature. Each cone was further divided into 1 mm-long slices in order to get an accurate value for the thermal and viscous wall losses. The load impedance at the open bell was taken as zero. The input impedance of the trumpet with mouthpiece was calculated iteratively such that the input impedance of one cone was used as the load impedance for the next cone. Calculations were done for frequencies up to 2000 Hz and for a variety of mouthpiece geometries but with the same trumpet sections. The effect of the mouthpiece geometry on the instrument’s impedance spectrum will be discussed.

Acoustic Word Embeddings for End-to-End Speech Synthesis

The most recent end-to-end speech synthesis systems use phonemes as acoustic input tokens and ignore the information about which word the phonemes come from. However, many words have their specific prosody type, which may significantly affect the naturalness. Prior works have employed pre-trained linguistic word embeddings as TTS system input. However, since linguistic information is not directly relevant to how words are pronounced, TTS quality improvement of these systems is mild. In this paper, we propose a novel and effective way of jointly training acoustic phone and word embeddings for end-to-end TTS systems. Experiments on the LJSpeech dataset show that the acoustic word embeddings dramatically decrease both the training and validation loss in phone-level prosody prediction. Subjective evaluations on naturalness demonstrate that the incorporation of acoustic word embeddings can significantly outperform both pure phone-based system and the TTS system with pre-trained linguistic word embedding.

Numerical study on a heat-driven piston-coupled multi-stage thermoacoustic-Stirling cooler

This work investigates a novel heat-driven multi-stage thermoacoustic cooler that can satisfy cooling requirements in the applications of natural gas liquefaction and high-temperature superconductivity. The proposed system consists of a compressor, multiple thermoacoustic units (engines and coolers) coupled by piston-cylinder assemblies. The acoustic power input by the compressor is successively multiplied in the thermoacoustic engine units, and the amplified acoustic power is then consumed to produce cooling power in the thermoacoustic cooler units. The proposed system overcomes the limitations of the traditional thermoacoustic systems owing to high efficiency, compact size, and ease of control. Analyses are first performed to explore the influence of the number of stages. The design method of the pistons is presented based on acoustic impedance matching principle.Based on the optimized system, simulations are then conducted to investigate the axial distribution of the key parameters, which can explain the reason for improved thermodynamic performance. At heating and cooling temperatures of 873 K and 130 K, the system achieves a cooling power of 2.1 kW and a thermal-to-cooling relative Carnot efficiency of 23%. This represents significant increases by over 60% in efficiency and 80% in cooling capacity when compared to existing systems. Simulations further demonstrate how controlling the input acoustic power and frequency via the compressor enables control of the system under various conditions. Further discussions are made considering a potential combined cooling and power system, indicating an overall thermal-cooling-electricity efficiency of 34% without any external electric power required for the compressor.

The role of vocal learning in call acquisition of wild grey seal pups.

Pinnipeds have been identified as one of the best available models for the study of vocal learning. Experimental evidence for their learning skills is demonstrated with advanced copying skills, particularly in formant structure when copying human speech sounds and melodies. By contrast, almost no data are available on how learning skills are used in their own communication systems. We investigated the impact of playing modified seal sounds in a breeding colony of grey seals (Halichoerus grypus) to study how acoustic input influenced vocal development of eight pups. Sequences of two or three seal pup calls were edited so that the average peak frequency between calls in a sequence changed up or down. We found that seals copied the specific stimuli played to them and that copies became more accurate over time. The differential response of different groups showed that vocal production learning was used to achieve conformity, suggesting that geographical variation in seal calls can be caused by horizontal cultural transmission. While learning of pup calls appears to have few benefits, we suggest that it also affects the development of the adult repertoire, which may facilitate social interactions such as mate choice.This article is part of the theme issue ‘Vocal learning in animals and humans’.

Coupled-SEA Application to Full Vehicle with Numerical Turbulent Model Excitation for Wind Noise Improvement

<div class="section abstract"><div class="htmlview paragraph">Wind noise is becoming a higher priority in the automotive industry. Several past studies investigated whether Statistical Energy Analysis (SEA) can be utilized to predict wind noise. Because wind noise analysis requires both radiation and transmission modeling in a wide frequency band, turbulent-structure-acoustic-coupled-SEA is being used. Past research investigated coupled-SEA’s benefit, but the model is usually simplified to enable easier consideration on the input side. However, the vehicle is composed of multiple interior parts and possible interior countermeasure consideration is needed. To enable this, at first, a more detailed coupled-SEA model is built from the acoustic-SEA model which has a larger number of degrees of freedom for the interior side. Then, the model is modified to account for sound radiation effects induced by turbulent and acoustic pressure. Another concern about utilizing the coupled-SEA to wind noise development is the estimation of the turbulent and acoustic input. Several options are available for identifying the input, such as on-road data measurement, CFD simulation, and numerical turbulent model estimation. Because the turbulent model can be helpful to consider the countermeasure direction, the turbulent model application to coupled-SEA is considered. However, an appropriate turbulent model is still unclear whereas there are many kinds of turbulent models proposed. Due to this, as the next step, this paper performs a validation study in a wind tunnel to identify the suitable turbulent model for the wind noise simulation. Lastly, the entire method is validated with on-road measurements. A detailed coupled-SEA model under appropriate turbulent model input simulates test case conditions and its prediction accuracy is discussed along with a wind noise.</div></div>

Assessment of Sound Source Tracking Using Multiple Drones Equipped with Multiple Microphone Arrays.

Drone audition techniques are helpful for listening to target sound sources from the sky, which can be used for human searching tasks in disaster sites. Among many techniques required for drone audition, sound source tracking is an essential technique, and thus several tracking methods have been proposed. Authors have also proposed a sound source tracking method that utilizes multiple microphone arrays to obtain the likelihood distribution of the sound source locations. These methods have been demonstrated in benchmark experiments. However, the performance against various sound sources with different distances and signal-to-noise ratios (SNRs) has been less evaluated. Since drone audition often needs to listen to distant sound sources and the input acoustic signal generally has a low SNR due to drone noise, making a performance assessment against source distance and SNR is essential. Therefore, this paper presents a concrete evaluation of sound source tracking methods using numerical simulation, focusing on various source distances and SNRs. The simulated results captured how the tracking performance will change when the sound source distance and SNR change. The proposed approach based on location distribution estimation tended to be more robust against distance increase, while existing approaches based on directional estimation tended to be more robust against decreasing SNR.

Efficient Forced Response Computations of Acoustical Systems with a State-Space Approach

State-space models have been successfully employed for model order reduction and control purposes in acoustics in the past. However, due to the cubic complexity of the singular value decomposition, which makes up the core of many subspace system identification (SSID) methods, the construction of large scale state-space models from high-dimensional measurement data has been problematic in the past. Recent advances of numerical linear algebra have brought forth computationally efficient randomized rank-revealing matrix factorizations and it has been shown that these factorizations can be used to enhance SSID methods such as the Eigensystem Realization Algorithm (ERA). In this paper, we demonstrate the applicability of the so-called generalized ERA to acoustical systems and high-dimensional input data by means of an example. Furthermore, we introduce a new efficient method of forced response computation that relies on a state-space model in quasi-diagonal form. Numerical experiments reveal that our proposed method is more efficient than previous state-space methods and can even outperform frequency domain convolutions in certain scenarios.

Categorical perception of lexical tones based on acoustic-electric stimulation.

The effect of low-frequency acoustic input on the categorical perception of lexical tones was investigated with simulated electric-acoustic hearing. A synthesized T1-T2 (flat-rising) tone continuum of Mandarin monosyllables /i/ was used, and they were manipulated as five conditions: unprocessed, low-frequency acoustic-only, electric-only, electric-acoustic stimulation, and bimodal stimulation. Results showed the performance under electric-only condition was the significantly lowest, and the difference of other pairwise comparisons between conditions was quite small. These findings suggest that the low-frequency acoustic input can shape the categorical perception, and the combinations of acoustic and electric hearing within or across ears have no significant effect.

Auditory Pattern Representations Under Conditions of Uncertainty-An ERP Study.

The auditory system is able to recognize auditory objects and is thought to form predictive models of them even though the acoustic information arriving at our ears is often imperfect, intermixed, or distorted. We investigated implicit regularity extraction for acoustically intact versus disrupted six-tone sound patterns via event-related potentials (ERPs). In an exact-repetition condition, identical patterns were repeated; in two distorted-repetition conditions, one randomly chosen segment in each sound pattern was replaced either by white noise or by a wrong pitch. In a roving-standard paradigm, sound patterns were repeated 1–12 times (standards) in a row before a new pattern (deviant) occurred. The participants were not informed about the roving rule and had to detect rarely occurring loudness changes. Behavioral detectability of pattern changes was assessed in a subsequent behavioral task. Pattern changes (standard vs. deviant) elicited mismatch negativity (MMN) and P3a, and were behaviorally detected above the chance level in all conditions, suggesting that the auditory system extracts regularities despite distortions in the acoustic input. However, MMN and P3a amplitude were decreased by distortions. At the level of MMN, both types of distortions caused similar impairments, suggesting that auditory regularity extraction is largely determined by the stimulus statistics of matching information. At the level of P3a, wrong-pitch distortions caused larger decreases than white-noise distortions. Wrong-pitch distortions likely prevented the engagement of restoration mechanisms and the segregation of disrupted from true pattern segments, causing stronger informational interference with the relevant pattern information.

Updated Review of the Acoustic Modulation of Sleep: Current Perspectives and Emerging Concepts.

With growing interest in the use of acoustic stimuli in sleep research and acoustic interventions used therapeutically for sleep enhancement, there is a need for an overview of the current lines of research. This paper summarizes the various ways to use acoustic input before sleep or stimulation during sleep. It thereby focuses on the respective methodological requirements, advantages, disadvantages, potentials and difficulties of acoustic sleep modulation. It highlights differences in subjective and objective outcome measures, immediate and whole night effects and short versus long term effects. This recognizes the fact that not all outcome parameters are relevant in every research field. The same applies to conclusions drawn from other outcome dimensions, consideration of mediating factors, levels of stimulation processing and the impact of inter-individual differences. In addition to the deliberate influences of acoustic input on sleep, one paragraph describes adverse environmental acoustic influences. Finally, the possibilities for clinical and basic research-related applications are discussed, and emerging opportunities are presented. This overview is not a systematic review but aims to present the current perspective and hence summarizes the most up-to-date research results and reviews. This is the first review providing a summary of the broad spectrum of possibilities to acoustically influence sleep.

Neuronal selectivity to complex vocalization features emerges in the superficial layers of primary auditory cortex.

Early in auditory processing, neural responses faithfully reflect acoustic input. At higher stages of auditory processing, however, neurons become selective for particular call types, eventually leading to specialized regions of cortex that preferentially process calls at the highest auditory processing stages. We previously proposed that an intermediate step in how nonselective responses are transformed into call-selective responses is the detection of informative call features. But how neural selectivity for informative call features emerges from nonselective inputs, whether feature selectivity gradually emerges over the processing hierarchy, and how stimulus information is represented in nonselective and feature-selective populations remain open question. In this study, using unanesthetized guinea pigs (GPs), a highly vocal and social rodent, as an animal model, we characterized the neural representation of calls in 3 auditory processing stages-the thalamus (ventral medial geniculate body (vMGB)), and thalamorecipient (L4) and superficial layers (L2/3) of primary auditory cortex (A1). We found that neurons in vMGB and A1 L4 did not exhibit call-selective responses and responded throughout the call durations. However, A1 L2/3 neurons showed high call selectivity with about a third of neurons responding to only 1 or 2 call types. These A1 L2/3 neurons only responded to restricted portions of calls suggesting that they were highly selective for call features. Receptive fields of these A1 L2/3 neurons showed complex spectrotemporal structures that could underlie their high call feature selectivity. Information theoretic analysis revealed that in A1 L4, stimulus information was distributed over the population and was spread out over the call durations. In contrast, in A1 L2/3, individual neurons showed brief bursts of high stimulus-specific information and conveyed high levels of information per spike. These data demonstrate that a transformation in the neural representation of calls occurs between A1 L4 and A1 L2/3, leading to the emergence of a feature-based representation of calls in A1 L2/3. Our data thus suggest that observed cortical specializations for call processing emerge in A1 and set the stage for further mechanistic studies.

Speech Recognition System (Home Appliances Controller of Local & Remote System) using LPC & HMMs Methodologies

In this proposed work we have been presenting an efficient Hardware and Software Controller for controlling appliances of home using combination of network technology and speech recognition technology. For speech recognition Linear Predictive Coding (LPC) has been implemented for extraction of features from acoustic inputs while states are designed using Hidden Markov Models at backend processing. The proposed model is designed to control local as well as remote home appliances using parallel ports of computer hardware interface.