Complex Acoustic Environments Research Articles

Making transformer hear better: Adaptive feature enhancement based multi-level supervised acoustic signal fault diagnosis

Acoustic signal fault diagnosis has been receiving increasing attention in the field of engine health management due to its effectiveness and non-invasiveness. Despite the progress made in fault diagnosis models, challenges still exist due to the complexity of acoustic signals and environmental factors. (1) End-to-end deep networks for fault diagnosis are at risk of underperformance or overfitting due to complex models and imbalanced data. (2) The complex acoustic environment within the vehicle power compartment poses obstacles to extracting subtle fault features. (3) Time–Frequency (TF) analysis has been proven to be an effective tool for characterizing the nonlinear features of fault signals, but it falls short in achieving ideal fidelity and resolution. To address these issues, an engine acoustic signal fault diagnosis method based on multi-level supervised learning and time–frequency transformation was proposed. First, adopting a multi-level supervised learning paradigm decomposes the fault diagnosis task into three stages: feature enhancement, fault detection, and fault identification, thereby incorporating additional experiential knowledge to mitigate overfitting. Second, an adaptive fault feature band extraction algorithm based on the fusion of multiple time–frequency analyses is proposed, specifically for extracting unique features from different vehicle datasets. Finally, a frequency band attention module was designed to focus on the frequency range most relevant to the characteristics of engine fault. The proposed method was validated on various audio signal fault datasets, and the results indicated its superior performance compared to other state-of-art fault detection and identification methods.

A sound event detection support system for smart home based on “two-to-one” teacher–student learning

Sound event detection (SED) is a core technology in smart home projects that rely on detected sound events to trigger specific actions. SED systems face two major challenges: high labeling costs and complex acoustic environments. To reduce labeling costs, some semi-supervised systems extract both global and local features for classification. However, these methods treat global and local features equally, not accounting for their varying importance when recognizing different types of sound events. Furthermore, to address complex acoustic environments, some studies use multitask learning frameworks to introduce SED-related tasks as auxiliaries to improve detection performance. However, these methods fail to align tasks within the framework, leading to conflicting outputs that may limit system performance. To address these issues, in this paper we propose a “two-to-one” teacher-student learning based semi-supervised SED system. This system employs a gating mechanism to selectively enhance global and local features, improving adaptability to different types of sound events, and incorporates a cross-task alignment module to interact SED with related tasks, reducing the risk of performance degradation caused by conflicting outputs. Experimental results on two datasets demonstrate that our system achieves the best performance in all metrics, with EB-F1 scores of 48.1 % and 64.7 %, representing improvements of 15.3 % and 10.6 % over the baseline ConformerSED system, respectively. Our work offers an effective SED solution for smart home projects by providing a semi-supervised SED system that performs well while reducing labeling costs.

Distributed extended Kalman filtering for acoustic simultaneous localization and environment mapping

The localization accuracy of Acoustic Simultaneous Localization and Mapping (ASLAM) often suffers from environmental noise and room reverberation. To solve this problem, an ASLAM method based on distributed extended Kalman filter is proposed. Specifically, the distance between the sound source and the robot is effectively estimated by the gating mechanism method in the case of unknown location of the sound source. Then, the Time Difference of Arrival (TDOA) between robots, the Direction of Arrival (DOA) and the distance between the sound source and the robot are presented as observation. Next, the robots' trajectories and the sound source's position are tracked by multiple extended Kalman filters. Finally, the ASLAM localization is completed by fusing the sound source and the robots' positioning information through average consensus algorithm, respectively. The proposed method can efficiently promote the ASLAM localization accuracy in complex acoustic environments. The experimental results verify the effectiveness of the proposed method.

Normoacusia y discriminación verbal en entornos sonoros reales

IntroductionHuman beings are constantly exposed to complex acoustic environments every day, which even pose challenges for individuals with normal hearing. Speech perception relies not only on fixed elements within the acoustic wave but is also influenced by various factors. These factors include speech intensity, environmental noise, the presence of other speakers, individual specific characteristics, spatial separatios of sound sources, ambient reverberation, and audiovisual cues. The objective of this study is twofold: to determine the auditory capacity of normal hearing individuals to discriminate spoken words in real-life acoustic conditions and perform a phonetic analysis of misunderstood spoken words. Materials and methodsThis is a descriptive observational cross-sectional study involving 20 normal hearing individuals. Verbal audiometry was conducted in an open-field environment, with sounds masked by simulated real-word acoustic environment at various sound intensity levels. To enhance sound emission, 2D visual images related to the sounds were displayed on a television. We analyzed the percentage of correct answers and performed a phonetic analysis of misunderstood spanish bisyllabic words in each environment. Results14 women (70%) and 6 men (30%), with an average age of 26±5,4 years and a mean airway hearing threshold in the right ear of 10,56±3,52dB SPL and in the left ear of 10,12±2,49dB SPL. The percentage of verbal discrimination in the ‘Ocean’ sound environment was 97,2±5,04%, ‘Restaurant’ was 94±4,58%, and ‘Traffic’ was 86,2±9,94% (p=0,000). Regarding the phonetic analysis, the allophones that exhibited statistically significant differences were as follows: [o] (p=0,002) within the group of vocalic phonemes, [n] (p=0,000) of voiced nasal consonants, [ɾ] (p=0,0016) of voiced fricatives, [b] (p=0,000) and [g] (p=0,045) of voiced stops. ConclusionsThe dynamic properties of the acoustic environment can impact the ability of a normal hearing individual to extract information from a voice signal. Our study demonstrates that this ability decreases when the voice signal is masked by one or more simultaneous interfering voices, as observed in a ‘Restaurant’ environment, and when it is masked by a continuous and intense noise environment such as ‘Traffic’. Regarding the phonetic analysis, when the sound environment was composed of continuous-low frequency noise, we found that nasal consonants were particularly challenging to identify. Furthermore, in situations with distracting verbal signals, vowels and vibrating consonants exhibited the worst intelligibility.

Normal hearing and verbal discrimination in real sounds environments

IntroductionHuman beings are constantly exposed to complex acoustic environments every day, which even pose challenges for individuals with normal hearing. Speech perception relies not only on fixed elements within the acoustic wave but is also influenced by various factors. These factors include speech intensity, environmental noise, the presence of other speakers, individual specific characteristics, spatial separatios of sound sources, ambient reverberation, and audiovisual cues. The objective of this study is twofold: to determine the auditory capacity of normal hearing individuals to discriminate spoken words in real-life acoustic conditions and perform a phonetic analysis of misunderstood spoken words. Materials and methodsThis is a descriptive observational cross-sectional study involving 20 normal hearing individuals. Verbal audiometry was conducted in an open-field environment, with sounds masked by simulated real-word acoustic environment at various sound intensity levels. To enhance sound emission, 2D visual images related to the sounds were displayed on a television. We analyzed the percentage of correct answers and performed a phonetic analysis of misunderstood Spanish bisyllabic words in each environment. Results14 women (70%) and 6 men (30%), with an average age of 26 ± 5,4 years and a mean airway hearing threshold in the right ear of 10,56 ± 3,52 dB SPL and in the left ear of 10,12 ± 2,49 dB SPL. The percentage of verbal discrimination in the “Ocean” sound environment was 97,2 ± 5,04%, “Restaurant” was 94 ± 4,58%, and “Traffic” was 86,2 ± 9,94% (p = 0,000). Regarding the phonetic analysis, the allophones that exhibited statistically significant differences were as follows: [o] (p = 0,002) within the group of vocalic phonemes, [n] (p = 0,000) of voiced nasal consonants, [r] (p = 0,0016) of voiced fricatives, [b] (p = 0,000) and [g] (p = 0,045) of voiced stops. ConclusionThe dynamic properties of the acoustic environment can impact the ability of a normal hearing individual to extract information from a voice signal. Our study demonstrates that this ability decreases when the voice signal is masked by one or more simultaneous interfering voices, as observed in a “Restaurant” environment, and when it is masked by a continuous and intense noise environment such as “Traffic”. Regarding the phonetic analysis, when the sound environment was composed of continuous-low frequency noise, we found that nasal consonants were particularly challenging to identify. Furthermore in situations with distracting verbal signals, vowels and vibrating consonants exhibited the worst intelligibility.

A novel transformer-enhanced and acoustic-based approach for wind turbine blade fault detection with integrated system implementation

Rising global wind power capacity urgently requires effective real-time turbine monitoring. Complex installations, high maintenance costs, and the occasional need for turbine shutdown hinder conventional monitoring methods. Acoustic-based techniques, while cost-efficient for health assessments, currently face challenges with detection precision and signal processing capabilities in complex acoustic environments. To overcome these challenges, this study proposes a low-cost, AI-driven acoustic-based health monitoring system framework for wind turbine blades, featuring enhanced detection accuracy and signal processing capabilities in complex sound environments. Firstly, a microphone array is employed to capture blade sounds with rich spatial attributes, while beamforming algorithms with a fixed orientation integrate prior spatial information. Furthermore, to further strengthen signal processing and fault detection capabilities, the Transformer model based on self-attention mechanisms is employed for feature extraction and fault diagnosis. An actual wind turbine blade health monitoring system is designed and developed to validate the usability of the proposed framework. Experimental results based on a scaled-down wind turbine model validate the proposed algorithm's effectiveness and practicality, presenting an effective approach in the wind turbine blade health monitoring domain.

A Review of Auditory Attention: Neural Mechanisms, Theories, and Affective Disorders.

Attention is a fundamental aspect of human cognitive function and is crucial for essential activities such as learning, social interaction, and routine tasks. Notably, Auditory attention involves complex interactions and collaboration among multiple brain networks. Recognizing the impairment of auditory attention, comprehending its underlying mechanisms, and identifying the activated brain regions essential for the development of treatments and interventions for individuals facing auditory attention deficits, emphasizes the significance of investigating these matters. In the current study, we conducted a review by searching for the full text of 53 articles published related to auditory attention, mechanisms, and networks in databases like Science Direct, Google Scholar, ProQuest, and PubMed using the keywords Attention, Auditory Attention, Auditory Attention Impairment, theories of attention were investigated in the years 2000 to 2023 And focused on articles that provided discussions within this research domain. The studies have demonstrated that auditory attention exceeds being an acoustic attribute and assumes a fundamental role in complex acoustic environments, information processing, and even speech comprehension. In the context of this study, we have conducted a review and summary of the proposed theories related to attention and the brain networks involved in different forms of auditory attention. In conclusion, the integration of auditory attention assessments, behavioral observations, and an understanding of the neural mechanisms and brain regions implicated in auditory attention proves to be an effective approach for the diagnosis and treatment of attention-related disorders.

Comparison of 2D and 3D multichannel audio rendering methods for hearing research applications using technical and perceptual measures

Virtual reality with multichannel audio playback is increasingly used in hearing aid research. The purpose of this study is to compare horizontal (2D) and periphonic (3D) rendering methods in terms of localization, minimum audible angle, and perceptual ratings related to spatial quality. Higher Order Ambisonics, Vector-Base Amplitude Panning, and Nearest Speaker Selection were used, with playback through 16, 29 and 45 speakers. The results show that an improvement in vertical localization can be obtained by using periphonic rendering instead of horizontal rendering. The perceptual advantage of periphonic rendering depends on the spatial complexity of the scene; it disappears in complex acoustic environments. Scenes with low acoustic complexity, such as a single primary sound source in a room, benefit from Nearest Speaker Selection rendering. For more complex scenes with multiple sound sources, such as a symphony orchestra in a concert hall with many primary sources, or traffic on a road with moving sources, horizontal rendering methods such as 2D Higher Order Ambisonics will provide similar or better performance.

Development of an adaptive test of musical scene analysis abilities for normal-hearing and hearing-impaired listeners

Auditory scene analysis (ASA) is the process through which the auditory system makes sense of complex acoustic environments by organising sound mixtures into meaningful events and streams. Although music psychology has acknowledged the fundamental role of ASA in shaping music perception, no efficient test to quantify listeners’ ASA abilities in realistic musical scenarios has yet been published. This study presents a new tool for testing ASA abilities in the context of music, suitable for both normal-hearing (NH) and hearing-impaired (HI) individuals: the adaptive Musical Scene Analysis (MSA) test. The test uses a simple ‘yes–no’ task paradigm to determine whether the sound from a single target instrument is heard in a mixture of popular music. During the online calibration phase, 525 NH and 131 HI listeners were recruited. The level ratio between the target instrument and the mixture, choice of target instrument, and number of instruments in the mixture were found to be important factors affecting item difficulty, whereas the influence of the stereo width (induced by inter-aural level differences) only had a minor effect. Based on a Bayesian logistic mixed-effects model, an adaptive version of the MSA test was developed. In a subsequent validation experiment with 74 listeners (20 HI), MSA scores showed acceptable test–retest reliability and moderate correlations with other music-related tests, pure-tone-average audiograms, age, musical sophistication, and working memory capacities. The MSA test is a user-friendly and efficient open-source tool for evaluating musical ASA abilities and is suitable for profiling the effects of hearing impairment on music perception.

A novel audio-visual based beamformer using a 360° camera and planar microphone array system

Beamforming systems that rely only on microphone arrays may suffer from poor performance in complex acoustic environments with multiple sources and room reverberation. To overcome this limitation, we propose a novel method that combines a planar microphone array and a 360° camera to steer the beamformer. The camera provides visual information about the location and orientation of sound sources, which can be used to adjust the beamformer parameters. We will present results that compare the signal-to-noise ratio (SNR) of the proposed method with a conventional beamforming microphone-based method in a simulated room with different source positions, orientations, and noise levels to investigate the benefit of visual information for beamforming in different environments. The proposed method has the potential to improve the performance of beamforming systems in applications such as speech enhancement, speech recognition, and speaker localization.

Subcortical measures of multi-talker speech processing

Communication in everyday acoustic environments is facilitated by the ability to locate, separate, and process speech from different locations. We do this by combining information received by both ears. Typically, the auditory system does not simply relay information delivered by both ears; rather, bilateral information is combined through elaborate binaural pathways in both the brainstem and cortex to allow us to communicate in complex acoustic environments. But traditionally it has been difficult to evaluate the subcortical underpinnings of speech communication using more complex, naturalistic continuous speech stimuli. Recently, the “peaky” speech method was created that uses stories to evoke brainstem responses using EEG. We have recorded brainstem responses from adults with normal hearing who listen to one or multiple narrators, and narrators coming from one or different perceived spatial locations. This talk will highlight the brainstem work undertaken towards creating subcortical measures of speech processing and spatial hearing.

A binaural room impulse response dataset and Shorelining psychophysical task for the evaluation of auditory sensory augmentation

Sensory augmentation using spatial sound presented in augmented-reality (AR) can assist people with low vision or blindness in navigating their environment (Katz et al., 2012). Nonetheless, in many situations, the poor quality of the binaural sound rendered using current tool sets limits the potential capability of the assistive technology. In particular, acoustic environments with near-field sources and reflections pose significant challenges. In this work, we provide a reference binaural room impulse response (BRIR) dataset with near-field sources and reflections and an associated shorelining psychophysical task that is useful for the evaluation of AR spatial audio. The dataset consists of 12∼small loudspeakers arranged on a 3-by-4 grid in a complex acoustic environment. BRIR measurements are recorded using the Head and Torso Simulator (HATS) for 17∼different receiver positions with a 5o angular resolution. Room impulse response measurements are also recorded using the Eigenmike for each of the 17 receiver positions. Using the Razer Anzu smart glasses to render the binaural AR spatial audio, we compare psychophysical performance on the shorelining navigation task using the recorded dataset and various existing binaural AR tool sets.

The relationship between extended high-frequency hearing and the binaural spatial advantage in young to middle-aged firefightersa).

Relationships between extended high-frequency (EHF) thresholds and speech-in-spatialized noise were examined in firefighters with a history of occupational noise and airborne toxin exposure. Speech recognition thresholds were measured for co-located and spatially separated (±90° azimuth) sentences in a competing signal using the Listening in Spatialized Noise-Sentences test. EHF hearing was significantly correlated with the spatial advantage, indicating that firefighters with poorer EHF thresholds experienced less benefit from spatial separation. The correlation between EHF thresholds and spatial hearing remained significant after controlling for age. Deficits in EHF and spatial hearing suggest firefighters may experience compromised speech understanding in job-related complex acoustic environments.

Neural dynamics underlying successful auditory short-term memory performance.

Listeners often operate in complex acoustic environments, consisting of many concurrent sounds. Accurately encoding and maintaining such auditory objects in short-term memory is crucial for communication and scene analysis. Yet, the neural underpinnings of successful auditory short-term memory (ASTM) performance are currently not well understood. To elucidate this issue, we presented a novel, challenging auditory delayed match-to-sample task while recording MEG. Human participants listened to 'scenes' comprising three concurrent tone pip streams. The task was to indicate, after a delay, whether a probe stream was present in the just-heard scene. We present three key findings: First, behavioural performance revealed faster responses in correct versus incorrect trials as well as in 'probe present' versus 'probe absent' trials, consistent with ASTM search. Second, successful compared with unsuccessful ASTM performance was associated with a significant enhancement of event-related fields and oscillatory activity in the theta, alpha and beta frequency ranges. This extends previous findings of an overall increase of persistent activity during short-term memory performance. Third, using distributed source modelling, we found these effects to be confined mostly to sensory areas during encoding, presumably related to ASTM contents per se. Parietal and frontal sources then became relevant during the maintenance stage, indicating that effective STM operation also relies on ongoing inhibitory processes suppressing task-irrelevant information. In summary, our results deliver a detailed account of the neural patterns that differentiate successful from unsuccessful ASTM performance in the context of a complex, multi-object auditory scene.

Rapid, Activity-Dependent Intrinsic Plasticity in the Developing Zebra Finch Auditory Cortex.

The acoustic environment an animal experiences early in life shapes the structure and function of its auditory system. This process of experience-dependent development is thought to be primarily orchestrated by potentiation and depression of synapses, but plasticity of intrinsic voltage dynamics may also contribute. Here, we show that in juvenile male and female zebra finches, neurons in a cortical-level auditory area, the caudal mesopallium (CM), can rapidly change their firing dynamics. This plasticity was only observed in birds that were reared in a complex acoustic and social environment, which also caused increased expression of the low-threshold potassium channel Kv1.1 in the plasma membrane and endoplasmic reticulum (ER). Intrinsic plasticity depended on activity, was reversed by blocking low-threshold potassium currents, and was prevented by blocking intracellular calcium signaling. Taken together, these results suggest that Kv1.1 is rapidly mobilized to the plasma membrane by activity-dependent elevation of intracellular calcium. This produces a shift in the excitability and temporal integration of CM neurons that may be permissive for auditory learning in complex acoustic environments during a crucial period for the development of vocal perception and production.SIGNIFICANCE STATEMENT Neurons can change not only the strength of their connections to other neurons, but also how they integrate synaptic currents to produce patterns of action potentials. In contrast to synaptic plasticity, the mechanisms and functional roles of intrinisic plasticity remain poorly understood. We found that neurons in the zebra finch auditory cortex can rapidly shift their spiking dynamics within a few minutes in response to intracellular stimulation. This plasticity involves increased conductance of a low-threshold potassium current associated with the Kv1.1 channel, but it only occurs in birds reared in a rich acoustic environment. Thus, auditory experience regulates a mechanism of neural plasticity that allows neurons to rapidly adapt their firing dynamics to stimulation.

Interspecific avoidance of song overlap in tropical songbirds: species-specific responses to acoustically similar and different intruders

To ensure effective acoustic communication, signals should reach receivers in the least distorted form possible. Animals use various short- and long-term strategies to avoid signal degradation and masking. However, we still have an insufficient understanding of how animals’ vocal behaviour is impacted by the vocalisations of other animals in their acoustic communities. We experimentally examined how two tropical, sedentary, territorial songbirds in Western Uganda—the scaly-breasted illadopsis (Illadopsis albipectus) and the green-backed camaroptera (Camaroptera brachyura)—modify their singing behaviour after the simulated appearance of new, unfamiliar acoustic competitors, whose songs vary in similarity to those of the species studied. We found that scaly-breasted illadopsis sang significantly less during the playback of songs of acoustically similar species than of acoustically different species or silence and avoided song overlapping with acoustically similar species but not with acoustically different species. Green-backed camaroptera sang significantly more during the playback of both acoustically similar and different simulated intruders than during the control containing silence, and patterns of overlap with the songs of both the acoustically similar and different species were random. Our results show that even a single-point noise source present within a territory can modify a bird’s singing behaviour. The new sound may affect species differently, depending in part on the level of acoustic similarity with the species’ song. To mitigate the effect of song masking, different species may use different strategies, such as temporal avoidance or signal redundancy. Studies examining the adaptive abilities of species in natural and modified habitats are needed to predict the consequences of changes in acoustic community structure.Significance statementTo ensure effective communication, birds may use different strategies to avoid signal masking in common acoustic space, particularly in the complex acoustic environment of a tropical forest. While multiple studies have focused on responses to interference caused by anthropogenic noise, the effect of new individual species on the acoustic community structure has received little attention. We simulated intrusions by unfamiliar species with different levels of song similarity into the territories of two tropical songbird species. The appearance of new simulated acoustic intruders modified the birds’ singing behaviour, but the two study species responded differently. These results suggest that the level of acoustic similarity, as well as the species ecology, may affect the species response, which may be particularly important when predicting the effects of new species appearance as a result of changes in habitat and climate.

Attentional modulation of neural sound tracking in children with and without dyslexia.

Auditory selective attention forms an important foundation of children's learning by enabling the prioritisation and encoding of relevant stimuli. It may also influence reading development, which relies on metalinguistic skills including the awareness of the sound structure of spoken language. Reports of attentional impairments and speech perception difficulties in noisy environments in dyslexic readers are also suggestive of the putative contribution of auditory attention to reading development. To date, it is unclear whether non-speech selective attention and its underlying neural mechanisms are impaired in children with dyslexia and to which extent these deficits relate to individual reading and speech perception abilities in suboptimal listening conditions. In this EEG study, we assessed non-speech sustained auditory selective attention in 106 7-to-12-year-old children with and without dyslexia. Children attended to one of two tone streams, detecting occasional sequence repeats in the attended stream, and performed a speech-in-speech perception task. Results show that when children directed their attention to one stream, inter-trial-phase-coherence at the attended rate increased in fronto-central sites; this, in turn, was associated with better target detection. Behavioural and neural indices of attention did not systematically differ as a function of dyslexia diagnosis. However, behavioural indices of attention did explain individual differences in reading fluency and speech-in-speech perception abilities: both these skills were impaired in dyslexic readers. Taken together, our results show that children with dyslexia do not show group-level auditory attention deficits but these deficits may represent a risk for developing reading impairments and problems with speech perception in complex acoustic environments. RESEARCH HIGHLIGHTS: Non-speech sustained auditory selective attention modulates EEG phase coherence in children with/without dyslexia Children with dyslexia show difficulties in speech-in-speech perception Attention relates to dyslexic readers' speech-in-speech perception and reading skills Dyslexia diagnosis is not linked to behavioural/EEG indices of auditory attention.

Computation-efficient solution for fully-connected active noise control window: Analysis and implementation of multichannel adjoint least mean square algorithm

The multichannel active noise control (MCANC) system, in which multiple reference sensors and actuators are used to enlarge the noise-cancellation zone, is widely utilized in complex acoustic environments. However, as the number of channels increases, the practicality decreases due to the exponential rise in computational complexity. This paper, therefore, revisits the adjoint least mean square (ALMS) algorithm and its multichannel applications. The computational analysis reveals that the multichannel adjoint least mean square (McALMS) algorithm11The code is shared on https://www.mathworks.com/matlabcentral/fileexchange/127554-multichannel-adjoint-lms-algorithm-for-multichannel-anc. has a significantly lower computation cost when implementing the fully connected active noise control (ANC) structure. In addition to this advantage, the theoretical analysis presented in this paper demonstrates that the McALMS algorithm can achieve the same optimal solution as the standard adaptive algorithm without the assumptions of input independence and white Gaussian noise. In addition, a practical step-size estimation strategy based on the Golden-section search (GSS) method is proposed to predict the fast step size of the McALMS algorithm. The numerical simulations in a multichannel ANC system demonstrate the effectiveness of the McALMS algorithm and validate the derived theoretical analysis. Furthermore, the McALMS algorithm with proposed step-size approach is used to implement a multichannel noise cancellation window that achieves satisfactory global noise reduction performance for tonal, broadband, and even real-world noises.

Intensity discrimination and neural representation of a masked tone in the presence of three types of masking release.

Hearing ability is usually evaluated by assessing the lowest detectable intensity of a target sound, commonly referred to as a detection threshold. Detection thresholds of a masked signal are dependent on various auditory cues, such as the comodulation of the masking noise, interaural differences in phase, and temporal context. However, considering that communication in everyday life happens at sound intensities well above the detection threshold, the relevance of these cues for communication in complex acoustical environments is unclear. Here, we investigated the effect of three cues on the perception and neural representation of a signal in noise at supra-threshold levels. First, we measured the decrease in detection thresholds produced by three cues, referred to as masking release. Then, we measured just-noticeable difference in intensity (intensity JND) to quantify the perception of the target signal at supra-threshold levels. Lastly, we recorded late auditory evoked potentials (LAEPs) with electroencephalography (EEG) as a physiological correlate of the target signal in noise at supra-threshold levels. The results showed that the overall masking release can be up to around 20 dB with a combination of these three cues. At the same supra-threshold levels, intensity JND was modulated by the masking release and differed across conditions. The estimated perception of the target signal in noise was enhanced by auditory cues accordingly, however, it did not differ across conditions when the target tone level was above 70 dB SPL. For the LAEPs, the P2 component was more closely linked to the masked threshold and the intensity discrimination than the N1 component. The results indicate that masking release affects the intensity discrimination of a masked target tone at supra-threshold levels, especially when the physical signal-to-noise is low, but plays a less significant role at high signal-to-noise ratios.

Anti-interference self-powered acoustic fabric for complex acoustic environments

Traditional airborne microphones are at risk of failure due to their dependence on airborne media in complex acoustic environments (CAEs). Here, we report an anti-interference self-powered acoustic fabric (ASAF) that can shield the interfering factors in the process of sound production and propagation to serve as a precise and wearable sound receiver. The use of the soft and safe woven structure polyvinylidene fluoride (PVDF) as a vibration-sensitive layer enables the ASAF to record human speech at wide vibration frequencies (0–5000 Hz). A speech recognition system is established which can recognize 25 words related to extreme weather conditions, with more than 95.8% accuracy. This speech recognition is carried out in CAEs such as wearing masks, silent communication, windstorms, and rainstorms, with corresponding losses of accuracy less than 1.6%, 6.7%, 6.3%, and 5.8%, respectively. The ASAF is expected to facilitate outdoor rescuers, journalists, students, and other professionals working in CAEs.