Search

Speech translation systems have become indispensable in facilitating seamless communication across language barriers. This paper presents a cascade speech translation system tailored specifically for translating speech from the Kazakh language to Russian. The system aims to enable effective cross-lingual communication between Kazakh and Russian speakers, addressing the unique challenges posed by these languages. To develop the cascade speech translation system, we first created a dedicated speech translation dataset ST-kk-ru based on the ISSAI Corpus. The ST-kk-ru dataset comprises a large collection of Kazakh speech recordings along with their corresponding Russian translations. The automatic speech recognition (ASR) module of the system utilizes deep learning techniques to convert spoken Kazakh input into text. The machine translation (MT) module employs state-of-the-art neural machine translation methods, leveraging the parallel Kazakh-Russian translations available in the dataset to generate accurate translations. By conducting extensive experiments and evaluations, we have thoroughly assessed the performance of the cascade speech translation system on the ST-kk-ru dataset. The outcomes of our evaluation highlight the effectiveness of incorporating additional datasets for both the ASR and MT modules. This augmentation leads to a significant improvement in the performance of the cascade speech translation system, increasing the BLEU score by approximately 2 points when translating from Kazakh to Russian. These findings underscore the importance of leveraging supplementary data to enhance the capabilities of speech translation systems. [ABSTRACT FROM AUTHOR]

The acoustic conditions of open-plan office spaces influence the well-being and productivity perceived by users. However, with an inadequate evaluation of the workspace, acoustic design in open-plan offices can be a factor that alters user performance. Such is the case in Mexico, where there are no adequate standards to evaluate specific acoustic conditions such as intelligibility. For this reason, this case study aims to evaluate different types of measurement methods for intelligibility. This study was carried out at a university in northern Mexico. The sound measurements were based on the Mexican standard for noise analysis and the ISO 3382-part 3 standards for acoustic measurements for open-plan offices. The psychoacoustic parameters evaluated were reverberation and intelligibility, using objective methods determined on S/N and subjective methods based on loss of consonant, where it was analyzed the distance between the sound source and zones classified by building design characteristics. The results indicated at which points the intelligibility effects increased. We also observed that reverberation remained stable in this office and that the subjective methods presented a larger measured sound effect than the objective methods. This finding establishes that subjective methods conform to Lognormal behavior, which is applicable to other linguistic elements describing speech behavior. [ABSTRACT FROM AUTHOR]

Estimating the rupture process of a quake constrains the tectonic setting of its source region. In terrestrial seismology, the rupture process can be described with a classical ω2 model. In this study, we focus on one key source parameter of S1222a, the corner frequency, to investigate its origin. However, estimating the corner frequency of S1222a is complicated by S1222a's non‐classical spectra which deviate from the ω2 model. To explain S1222a's spectra, we take into account the site effect at the InSight landing site. Through numerical simulation, we demonstrate that the spectral fitting is greatly improved after considering the site effect. We further estimated the source spectrum and stress drop of S1222a. The obtained stress drop resembles the values for regional tectonic earthquakes and shallow moonquakes but differs from the Cerberus Fossae marsquakes, which favors a different tectonic origin from the Cerberus Fossae marsquakes for S1222a. Plain Language Summary: The source of a quake is a key piece of information to uncover the dynamic process at the source region. In terrestrial seismology, the source of a quake can be described with a classical model in which the spectra decay with frequency at a certain speed. In this study, we focus on one key source parameter of S1222a, the corner frequency, to explore the generating process of S1222a. However, S1222a exhibits non‐classical spectra which cannot be explained by the classical model, making it difficult to estimate S1222a's source spectrum. To explain S1222a's spectra, we hypothesized that the seismic records are contaminated by wave reverberations in the subsurface layers, namely site effect. We validated our hypothesis with a numerical method. After considering site effect, S1222a's source spectrum and stress drop can be better estimated. The obtained stress drop value is close to those for regional tectonic earthquakes and shallow moonquakes but differs from the values observed for some marsquakes located at Cerberus Fossae, a seismically active region on Mars. Thus, we conclude that S1222a has a different tectonic origin from the Cerberus Fossae marsquakes. Key Points: We constructed a numerical model to simulate the site effect at the InSight landing site to better explain the spectra of S1222aWe estimated the corner frequency of S1222a to be 0.76 (0.58–1.07) Hz, which corresponds to a stress drop of 3.62 (0.80–20.26) MPaThe corner frequency and stress drop estimation favor that S1222a has a different tectonic origin from the Cerberus Fossae marsquakes [ABSTRACT FROM AUTHOR]

The detection performance of active sonar is often hindered by the presence of seabed reverberation in shallow water. Separating the reverberations from the target echo and noise in the received signal is a crucial challenge in the field of underwater acoustic signal processing. To address this issue, an improved Go-SOR decomposition method is proposed based on the subspace-orbit-randomized singular value decomposition (SOR-SVD). This method successfully extracts the low-rank structure with a certain striation pattern. The results demonstrate that the proposed algorithm outperforms both the original Go algorithm and the current state-of-the-art (SOTA) algorithm in terms of the definition index of the low-rank structure and computational efficiency. Based on the monostatic reverberation theory of the normal mode, it is established that the low-rank structure is consistent with the low-frequency reverberation interference striation. This study examines the interference characteristics of the low-rank structure in the experimental sea area and suggests that the interferences of the fifth and seventh modes mainly control the low-rank structure. The findings of this study can be applied to seafloor exploration, reverberation waveguide invariant (RWI) extraction, and data-driven reverberation suppression methods. [ABSTRACT FROM AUTHOR]

Many fishes use sounds to communicate in a wide range of behavioral contexts. In monitoring studies, these sounds can be used to detect and identify species. However, being able to confidently link a sound to the correct emitting species requires precise acoustical characterization of the signals in controlled conditions. For practical reasons, this characterization is often performed in small sized aquaria, which, however, may cause sound distortion, and prevents an accurate description of sound characteristics that will ultimately impede sound-based species identification in open-water environments. This study compared the sounds features of five specimens of the silverspot squirrelfish Sargocentron caudimaculatum recorded at sea and in aquaria of different sizes and materials. Our results point out that it is preferable to record fish sounds in an open-water environment rather than in small aquaria because acoustical features are affected (sound duration and dominant frequency) when sounds are recorded in closed environments as a result of reverberation and resonance. If not possible, it is recommended that (1) sound recordings be made in plastic or plexiglass aquaria with respect to glass aquaria and (2) aquaria with the largest dimensions and volumes be chosen. [ABSTRACT FROM AUTHOR]

Accreting black holes commonly exhibit hard X-ray emission, originating from a region of hot plasma near the central engine referred to as the corona. The origin and geometry of the corona are poorly understood, and models invoking either inflowing or outflowing material (or both) can successfully explain only parts of the observed phenomenology. In particular, recent works indicate that the time-averaged and variability property might originate in different regions of the corona. In this paper we present a model designed to move beyond the lamppost paradigm, with the goal of accounting for the vertical extent of the corona. In particular, we highlight the impact of including self-consistently a second lamppost, mimicking, for example, an extended jet base. We fully include the effect that the second source has on the time-dependent disk ionization, reflection spectrum, and reverberation lags. We also present an application of this new model to NICER observations of the X-ray binary MAXI J1820+070 near its hard-to-soft state transition. We demonstrate that in these observations, a vertically extended corona can capture both spectral and timing properties, while a single-lamppost model can not. In this scenario, the illumination responsible for the time-averaged spectrum originates close to the black hole, while the variability is likely associated with the ballistic jet. [ABSTRACT FROM AUTHOR]

Copyright of Investigación e Innovación en Ingenierías is the property of Universidad Simon Bolivar and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

When chaotic systems are used for speech encryption, their chaotic performance largely determines the security of speech encryption. However, traditional chaotic systems have problems such as parameter discontinuity, easy occurrence of chaos degradation, low complexity, and the existence of periodic windows in chaotic intervals. In real applications, chaotic mappings may fall into periodic windows, which is extremely unfavorable for security. In this paper, a new chaotic mapping 2D-LMSM is proposed by improving the chaotic logistic and sine mappings, and applied to speech encryption. Performance evaluation shows that this map can effectively generate robust chaotic signals in a wide parameter range. The 2D-LMSM achieves better robustness and desired chaotic properties than several existing two-dimensional chaotic maps. We propose a novel speech encryption algorithm using this map. First, it performs Fast Fourier Transform (FFT) on the input speech signal to obtain real and imaginary values, which are encrypted by one-time scrambling encryption and XOR diffusion encryption with pseudorandom numbers generated by chaos; then, it performs secondary scrambling encryption by Discrete Wavelet Transform (DWT) and 2D-LMSM; finally, it obtains encrypted speech data by Discrete Wavelet Inverse Transform (IDWT) and Fast Fourier Inverse Transform (IFFT). Experimental results show that this algorithm has good encryption and decryption performances and ensures system security. [ABSTRACT FROM AUTHOR]

Speech Emotion Recognition (SER) is the process of recognizing emotions by extracting few features of speech signals. It is becoming very popular in Human Computer Interaction (HCI) applications. The challenge is to extract relevant features of speech to recognize emotions with a low computational cost. In this paper, a lightweight Convolutional Neural Network (LCNN) based model has been proposed which extracts useful features automatically. The speech samples are converted into spectrograms of size 224 × 224 for LCNN input. 5 CNN layers and stride are used for down-sampling the feature maps in place of pooling layers which reduces the computational cost. It has been evaluated for accuracy on publicly available benchmark datasets EMOVO (81%), EMODB (87%), and SAVEE (80%). The accuracy of proposed model is also found to be better than SER CNN-assisted model, ResNet-18 and ResNet-34 models. Very few speech datasets are available in Indian ascent. So, authors have created a new Indian Emotional Speech Corpora (IESC) in English language with 600 speech samples recorded from 8 speakers using 2 sentences in 5 emotions. It will be made publicly available for researchers. The accuracy of the proposed LCNN model on IESC is found to be 95% which is better than existing datasets. [ABSTRACT FROM AUTHOR]

Classrooms are important learning spaces, however, the acoustic conditions in these spaces can often be suboptimal. The aim of this scoping review, which used the PRISMA-ScR protocol, was to understand what is known from the literature about the effect of classroom acoustic treatment on students' listening, learning, and well-being. Thirteen papers from the database searches were deemed relevant for the review. Information on the years of publication of the papers, the population studied, the types of acoustic treatment used, the measures and methods used to assess the effect of acoustic treatment, and the outcomes of the papers was gathered. Seven of the 13 studies reported positive effects of classroom acoustic treatment on student's speech perception, attention, and well-being. Five studies reported both positive effects and no effect depending on the measure, condition, or population. The remaining study reported a negative effect of classroom acoustic treatment on children's speech perception and listening effort. These findings suggest that the effect of ceiling and/or wall absorbers/diffusers on sound and reverberation in the room can help students' speech perception, attention, reading, and well-being, but they may also reduce the speech transmission index resulting in increased listening effort. The limitations of the reviewed studies and avenues for future research on the effect of acoustic treatment on a broader range of listening, learning, and well-being outcomes for students are discussed. [ABSTRACT FROM AUTHOR]

To simulate the indoor air distribution accurately and quickly, this paper proposed a turbulence calculation model based on the zero-equation model and the SUPG finite element method. The optimal calculation parameters were investigated. The effects of air outlet positions, Reynolds numbers, and obstacle positions on indoor air distribution were studied. The results show that the ranges of Reynolds numbers which satisfy the summer and winter demands of indoor air velocity as the outlet at the right down position are larger than those when the outlet locates left down. When the air outlet locates at the left down position, the velocity non-uniformity coefficients are less than those under the other two conditions. Regardless of whether the air outlet is at the left or right position, the obstacle in the middle of a room can lead to worse velocity uniformity when air velocities in the working zone can meet the velocity demand. [ABSTRACT FROM AUTHOR]

For robust vocalization perception, the auditory system must generalize over variability in vocalization production as well as variability arising from the listening environment (e.g., noise and reverberation). We previously demonstrated using guinea pig and marmoset vocalizations that a hierarchical model generalized over production variability by detecting sparse intermediate-complexity features that are maximally informative about vocalization category from a dense spectrotemporal input representation. Here, we explore three biologically feasible model extensions to generalize over environmental variability: (1) training in degraded conditions, (2) adaptation to sound statistics in the spectrotemporal stage and (3) sensitivity adjustment at the feature detection stage. All mechanisms improved vocalization categorization performance, but improvement trends varied across degradation type and vocalization type. One or more adaptive mechanisms were required for model performance to approach the behavioral performance of guinea pigs on a vocalization categorization task. These results highlight the contributions of adaptive mechanisms at multiple auditory processing stages to achieve robust auditory categorization. A computational model for categorizing vocalizations from marmosets and guinea pigs highlights the contributions of adaptive mechanisms at multiple auditory processing stages to achieve robust auditory categorization. [ABSTRACT FROM AUTHOR]

The Earth, in large portions, is covered in oceans, sediments, and glaciers. High‐resolution body wave imaging in such environments often suffers from severe reverberations, that is, repeating echoes of the incoming scattered wavefield trapped in the reverberant layer, making interpretation of lithospheric layering difficult. In this study, we propose a systematic data‐driven approach, using autocorrelation and homomorphic analysis, to solve the twin problem of detection and elimination of reverberations without a priori knowledge of the elastic structure of the reverberant layers. We demonstrate, using synthetic experiments and data examples, that our approach can effectively identify the signature of reverberations even in cases where the recording seismic array is deployed in complex settings, for example, using data from (a) a land station sitting on Songliao basin, (b) an ocean bottom station in the fore‐arc setting of the Alaska amphibious community seismic experiment, and (c) a station deployed on ice‐sediment strata in the glaciers of Antarctica. The elimination of the reverberation is implemented by a frequency domain filter whose parameters are automatically tuned using seismic data alone. On glaciers where the reverberating sediment layer is sandwiched between the lithosphere and an overlying ice layer, homomorphic analysis is preferable in detecting the signature of reverberation. We expect that our technique will see wide application for high‐resolution body wave imaging across a wide variety of conditions. Plain Language Summary: The Earth, in large portions, is covered in oceans, sediments, and glaciers. Because of the large differences in rock properties between these layers and the solid Earth underneath, waves get trapped in them which hampers the successful investigation of deeper layers. This is often referred to as "reverberation," waves that "echo" or "sing" again and again. In this study, we propose a systematic approach to detect and eliminate this "singing" effect using only observed data, without any knowledge of the local geological structure. Our approach extends the autocorrelation analysis, a widely used method to detect repeating patterns in time series, and also takes advantage of the homomorphic analysis, a popular technique in speech and audio processing. We demonstrate the effectiveness of our approach using both human‐generated and real seismic data, collected from complex geosettings around the world, including in the oceans to the south of the Alaska Peninsula, sedimentary basin in northeast China, and Antarctica. On glaciers where the reverberation comes from the complicated coupled effect of ice and sediment, homomorphic analysis is preferable in detecting the signature of reverberation. We expect that our technique will greatly improve the imaging of deep Earth structure across a wide variety of conditions. Key Points: A data‐driven approach using autocorrelation and homomorphic analysis is proposed to detect the signature of reverberations in seismic dataThe proposed approach can be applied to various geological settings where reverberations are present; that is, sediments, oceans, and glaciersSignal enhancement using either approach is best in single‐layer systems, while homomorphic analysis is preferred for ice‐sediment systems [ABSTRACT FROM AUTHOR]

In acoustics, time-reversal processing is commonly used to exploit multiple scatterings in reverberant environments to focus sound to a specific location. Recently, the nonlinear characteristics of time-reversal focusing at amplitudes as high as 200 dB have been reported [Patchett and Anderson, J. Acoust. Soc. Am. 151(6), 3603–3614 (2022)]. These studies were experimental in nature and suggested that converging waves nonlinearly interact in the focusing of waves, leading to nonlinear amplification. This study investigates the nonlinear interactions and subsequent characteristics from a model-based approach. Utilizing both finite difference and finite-element models, it is shown that nonlinear interactions between high-amplitude waves lead to free-space Mach-wave coalescence of the converging waves. The number of waves used in both models represents a small piece of the full aperture of converging waves experimentally. Limiting the number of waves limits the number of Mach-stem formations and reduces the nonlinear growth of the focus amplitudes when compared to experiment. However, limiting the number of waves allows the identification of individual Mach waves. Mach wave coalescence leading to Mach-stem formation appears to be the mechanism behind nonlinear amplification of peak focus amplitudes observed in high-amplitude time-reversal focusing. [ABSTRACT FROM AUTHOR]

We utilize SuperCam's Mars microphone to provide information on wind speed and turbulence at high frequencies on Mars. To do so, we first demonstrate the sensitivity of the microphone signal level to wind speed, yielding a power law dependence. We then show the relationship between the microphone signal level and pressure, air and ground temperatures. A calibration function is constructed using Gaussian process regression (a machine learning technique) taking the microphone signal and air temperature as inputs to produce an estimate of the wind speed. This provides a high rate wind speed estimate on Mars, with a sample every 0.01 s. As a result, we determine the fast fluctuations of the wind at Jezero crater which highlights the nature of wind gusts over the Martian day. To analyze the turbulent behavior of this wind speed estimate, we calculate its normalized standard deviation, known as gustiness. To characterize the behavior of this high frequency turbulent intensity at Jezero crater, correlations are shown between the evaluated gustiness statistic and pressure drop rates/sizes, temperature and energy fluxes. This has implications for future atmospheric models on Mars, taking into account turbulence at the finest scales. Plain Language Summary: The NASA Perseverance mission sent microphones to the surface of Mars. This microphone has recorded signals due to the wind. We examine how these recorded signals vary with other sensor data from Perseverance, which shows a link between the microphone signal, the dedicated wind speed sensor and air temperature. Based on this finding, we develop a way to predict the wind speed from the microphone data using a machine learning technique. The microphone records data at a very high rate compared with sensors so far sent to Mars. This means that the wind speed predicted from the microphone data can be used to study the chaotic and variable wind behavior on Mars to a level never seen before. We show that this chaotic and variable behavior has links to temperature and the number of whirlwinds observed. This will lead us to better weather models for Mars. Key Points: Wind‐induced noise is observed by the SuperCam Mars microphone on PerseveranceMicrophone and air temperature data are used to estimate the wind speed at high frequencies, using a machine learning modelThe wind speed estimate is used to examine the relationships between turbulent intensity, pressure drops, temperature, and energy flux [ABSTRACT FROM AUTHOR]

Robust sound source localization for environments with noise and reverberation are increasingly exploiting deep neural networks fed with various acoustic features. Yet, state-of-the-art research mainly focuses on optimizing algorithmic accuracy, resulting in huge models preventing edge-device deployment. The edge, however, urges for real-time low-footprint acoustic reasoning for applications such as hearing aids and robot interactions. Hence, we set off from a robust CNN-based model using SRP-PHAT features, Cross3D [16], to pursue an efficient yet compact model architecture for the extreme edge. For both the SRP feature representation and neural network, we propose respectively our scalable LC-SRP-Edge and Cross3D-Edge algorithms which are optimized towards lower hardware overhead. LC-SRP-Edge halves the complexity and on-chip memory overhead for the sinc interpolation compared to the original LC-SRP [19]. Over multiple SRP resolution cases, Cross3D-Edge saves 10.32%∼73.71% computational complexity and 59.77%∼94.66% neural network weights against the Cross3D baseline. In terms of the accuracy-efficiency tradeoff, the most balanced version (EM) requires only 127.1 MFLOPS computation, 3.71 MByte/s bandwidth, and 0.821 MByte on-chip memory in total, while still retaining competitiveness in state-of-the-art accuracy comparisons. It achieves 8.59 ms/frame end-to-end latency on a Rasberry Pi 4B, which is 7.26× faster than the corresponding baseline. [ABSTRACT FROM AUTHOR]

The article presents research studies on the impact of perforation of the outer lining layer of an acoustic panel used for the construction of road noise reduction devices on its absorbing properties. The research included measurements of the reverberation time in the laboratory conditions of diffusion field, on the basis of which the values of sound absorption coefficient as a function of frequency were determined. In addition, for various solutions of acoustic panels based on a corrugated fiber cement board on the top surface and on two types of mineral wool inside the panel, the αw and αp indices as well as sound absorption rating index DLαNRD were calculated. Then, computer simulations were carried out to show the influence of laboratory-determined acoustic parameters of the panels on the acoustic climate in the vicinity of a selected transport system. The key aspects of the modeling process are presented, the characteristics of the noise source and the analysis of the results are described. An important goal of traffic noise modeling is to strive to develop more friendly and sustainable material solutions that will reduce the negative effects of noise on people and the environment. [ABSTRACT FROM AUTHOR]

Mechanical vibration of plates have applications in many fields of science and industry including synthesis of artificial reverberation – one of the most important signal processors in audio engineering. The paper presents a concept for study and measurements of reverberating plates that contains an initial numerical solution with a goal of predicting behaviours of the vibrating plate as its response for physically affecting its vibration. The concept also considers experimental measurements of selected simplified solutions as well as their comparison with numerical simulation. In addition the paper contains evidence for perceptible differences between audio signals obtained from the initial experiments, which suggests the viability of adjustable mechanical reverberation mechanism. Moreover, the paper includes concept for test stand for experimental study of reverberating plates in order to achieve signals differing in perceptually significant way. The test stand and study will allow to increase knowledge of vibrating plates as parts of plate reverberation devices. [ABSTRACT FROM AUTHOR]

The article discusses the requirements for determining airborne sound insulation according to ISO 10140-2, which involves measuring sound pressure levels in the source (L1) and receiving (L2) rooms, as well as reverberation time measurements in the receiving room. The size of the free test opening and the equivalent sound absorption area in the receiving room affect the value of L2. While ISO 10140-5 specifies the dimensions of a full-size test opening, reduced-size openings can also be used. However, testing reduced-size baffles with specific dimensions may be necessary, and measurements on rectangular-shaped baffles may yield higher sound reduction indices than square-shaped ones. The article presents a comparative analysis of the spectral characteristics of different types of single homogeneous baffles with various dimensions using experimental methods. It examines the measurement methodology's influence on determining sound insulation spectra and the weighted sound reduction index Rw. The article also calculates the combined uncertainty in determining the sound insulation properties and partial uncertainties in determining L1 and L2. [ABSTRACT FROM AUTHOR]

Due to the small sample size of underwater acoustic data and the strong noise interference caused by seabed reverberation, recognizing underwater targets in Side-Scan Sonar (SSS) images is challenging. Using a transfer-learning-based recognition method to train the backbone network on a large optical dataset (ImageNet) and fine-tuning the head network with a small SSS image dataset can improve the classification of sonar images. However, optical and sonar images have different statistical characteristics, directly affecting transfer-learning-based target recognition. In order to improve the accuracy of underwater sonar image classification, a style transformation method between optical and SSS images is proposed in this study. In the proposed method, objects with the SSS style were synthesized through content image feature extraction and image style transfer to reduce the variability of different data sources. A staged optimization strategy using multi-modal data effectively captures the anti-noise features of sonar images, providing a new learning method for transfer learning. The results of the classification experiment showed that the approach is more stable when using synthetic data and other multi-modal datasets, with an overall accuracy of 100%. [ABSTRACT FROM AUTHOR]

Equipment, sound sources, operators, microphone placement, calculation techniques, and thermal–humidity measurement conditions all have an impact on the measurement of impulse responses when several channels are present. However, the thermal–humidity variable, which is a significant component of these factors impacting the assessment of acoustic characteristics, is commonly overlooked in research. The effects of altering temperature, relative humidity, and air velocity on acoustic parameters are investigated in this paper through experimental activities carried out in an experimental room. The patterns of fluctuation of a range of room acoustic characteristics are examined, data are acquired, and statistical analyses based on R (language and environment for statistical computing and graphics) are generated in order to ascertain the relationship between the variation of acoustic parameters and the variation of thermo-hygrometric parameters. Finally, a statistical analysis reveals relationships between thermal and hygrometric variables and interior acoustic characteristics. [ABSTRACT FROM AUTHOR]

Copyright of Control Theory & Applications / Kongzhi Lilun Yu Yinyong is the property of Editorial Department of Control Theory & Applications and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In this paper, a speech enhancement method based on correlation canceling approach associated with the Log- minimum mean-square-error estimator is presented. Unlike the conventional statistical-model methods based on the nonlinear estimation of the enhanced speech signal, such as Maximum-Likelihood estimator (ML), Maximum A Posteriori (MAP) estimator, Minimum Mean Square Error (MMSE) estimator and log MMSE estimator, in the proposed hybrid method (CC/Log-MMSE), the nonlinear estimation is transformed into a linear estimation by exploiting the orthogonal projection of clean signal into the noisy signal. Thus, the enhanced signal represents the best "copy," or estimate, of clean signal that can be made on the basis of the noisy signal vector. This is also seen as a canceling of the component of the noisy vector residing in the noise subspace, which therefore leads to improve the intelligibility of the enhanced signal. Extensive simulations are carried out using speech files corrupted by different noises available in the NOIZEUS corpus, show that the proposed hybrid method CC/Log-MMSE consistently outperforms the baseline methods of speech enhancement at different levels of SNR in terms of objective and subjective measures, spectrogram analysis and the overall SNR improvement. [ABSTRACT FROM AUTHOR]

It is difficult to imagine a better guide to Meltzer's work than Meg Harris Williams, a former analysand and intellectual collaborator of Meltzer. Early chapters address Meltzer's Kleinian roots, the significance of dream life, and the post-Kleinian view of projective identification and containment. Donald Meltzer (1922-2004) was an American-born psychiatrist who came to England to have an analysis with Klein. [Extracted from the article]

Background: Noise reduction across spatial regions of limited size in large enclosures is a practically useful application of global active noise control (ANC). ANC systems based on Multi-channel filtered-x least mean square (MC-FxLMS) algorithm are employed to spatially extend the quiet zone beyond cancellation points. Purpose: Analytical expressions are available that give the maximum achievable reduction in acoustic potential energy across an enclosure and the minimum mean square residual noise achievable at error microphone locations using MC-FxLMS algorithm. However, such expressions are not available to determine the maximum achievable average noise reduction across a quiet zone in an arbitrary region situated within the enclosure. The present study performs numerical simulations to estimate maximum achievable global noise reduction across the chosen quiet zone using MC-FxLMS algorithm. Methods: Simulation of a room environment having reverberation in three-dimensional space is done. Noise reduction performance is evaluated at uniformly placed grid points across a two-dimensional square zone of quiet having an area of 1 m2. This paper reports a systematic simulation study of MC-FxLMS algorithm in which the numbers of control sources and residue sensors are progressively increased and analysis of asymptotic performance of the ANC system is done. Results and Conclusions: The study shows that after a certain point, further increase in the number of components does not yield appreciable improvement in global noise reduction across the chosen quiet zone, and the performance of MC-FxLMS algorithm saturates. The number of components so obtained is significantly less than that required as per modal analysis. [ABSTRACT FROM AUTHOR]

We propose a multi-threaded algorithm that can improve the performance of geometric acoustic (GA)-based sound propagation algorithms in mobile devices. In general, sound propagation algorithms require high computational cost because they perform based on ray tracing algorithms. For this reason, it is difficult to operate sound propagation algorithms in mobile environments. To solve this problem, we processed the early reflection and late reverberation steps in parallel and verified the performance in four scenes based on eight sound sources. The experimental results showed that the performance of the proposed method was on average 1.77 times better than that of the single-threaded method, demonstrating that our algorithm can improve the performance of mobile devices. [ABSTRACT FROM AUTHOR]

A hexahedron reverberation box has been developed through reverse engineering to study the reverberation time of fibrous felts in diffuse acoustic field condition. The study reinstated the frequency as a prime factor to understand the relation between noise control performance of a sample in transfer matrix method and diffused acoustic field condition. A new non-linear, bi-variant frequency dependent model was formulated through synchronization of impedance tube data and noise absorption coefficient calculated from reverberation time of the felts tested in the hexahedron box. The empirical model was validated for particle board based perforated absorber which yielded a comparable noise absorption value with a mean absolute error as low as 0.02. The reverberation box substantially reduces the size of samples for trial in nondestructive mode. The frequency dependent model for different absorber predicted the noise absorption property from calculated reverberation time (RT60), which would help in engineering specified samples for noise control. The novelty of the work lies in the fabrication of the reverberation box to work with frequency levels as low as 250 Hz i.e., above Schroeder frequency. [ABSTRACT FROM AUTHOR]

In this paper, we present a novel scheme for enhancing the security of speech information in communication systems. We build a hybridization of three approaches: Chaotic logistic and tent maps for generating an arbitrary vector by some primarily initiated values to be joined in the original speech signal, an integrated watermark image within the encrypted signal in order to verify, through decryption process, that the encrypted signal is authentic as well as does not suffer from eventual attacks, and the third approach is using an Arnold scrambling key (cat map) to spread signal samples by means of a secret key, then recuperate the original signal from samples which is not possible without this key. Obtained correlation value in the proposed scheme is closer to null which proves that original and encrypted signals are completely dissimilar. Moreover, we recovered the original speech without disturbing the quality. Numerical results of the Signal to Noise Ratio (SNR) and Correlation Coefficient (CC) reported below, and the comparison between the proposed approach to seven recently published works, also reported, reveal the superiority of the proposed scheme and validate our design to be considered amongst the best methods compared to other recently existing strong approaches. [ABSTRACT FROM AUTHOR]

Textile materials used without any other structures show low absorption throughout the operating frequency range, and they are currently used for interior decoration. These fabrics can play an important role in the development of acoustic materials considering folding techniques in the design phase. The folding of a cotton fabric not only affects the esthetic appearance but also directly influences the total absorption surface and the volumetric density. The aim of this research was to establish the influence of geometric design parameters, such as the number of folds and the textile length on the sound absorption properties. Experimental measurements were performed by using an impedance tube considering only incident plane waves. The diffuse-field sound absorption coefficient of several fabric configurations placed in front of a rigid backing forming an air-cavity between them was also measured in the small-sized reverberation chamber. A semi-empirical model based on the spacing between the fabric to the backing wall and the folding geometry was used in order to predict the diffuse-field sound absorption in reverberation room. Results showed a very good agreement between measured and predicted sound absorption coefficients. [ABSTRACT FROM AUTHOR]

Marine crustaceans produce broadband sounds that have been mostly characterized in tanks. While tank physical impacts on such signals are documented in the acoustic community, they are overlooked in the bioacoustic literature with limited empirical comparisons. Here, we compared broadband sounds produced at 1 m from spiny lobsters (Panulirus argus) in both tank and in situ conditions. We found significant differences in all sound features (temporal, power, and spectral) between tank and in situ recordings, highlighting that broadband sounds, such as those produced by marine crustaceans, cannot be accurately characterized in tanks. We then explained the three main physical impacts that distort broadband sounds in tanks, respectively known as resonant frequencies, sound reverberation, and low frequency attenuation. Tank resonant frequencies strongly distort the spectral shape of broadband sounds. In the high frequency band (above the tank minimum resonant frequency), reverberation increases sound duration. In the low frequency band (below the tank minimum resonant frequency), low frequencies are highly attenuated due to their longer wavelength compared to the tank size and tank wall boundary conditions (zero pressure) that prevent them from being accurately measured. Taken together, these results highlight the importance of understanding tank physical impacts when characterizing broadband crustacean sounds. [ABSTRACT FROM AUTHOR]

The auditory signals at the ear can be affected by components arriving both directly from a sound source and indirectly via environmental reverberation. Previous studies have suggested that the perceptual separation of these contributions can be aided by expectations of likely reverberant qualities. Here, we investigated whether vision can provide information about the auditory properties of physical locations that could also be used to develop such expectations. We presented participants with audiovisual stimuli derived from 10 simulated real-world locations via a head-mounted display (HMD; n = 44) or a web-based (n = 60) delivery method. On each trial, participants viewed a first-person perspective rendering of a location before hearing a spoken utterance that was convolved with an impulse response that was from a location that was either the same as (congruent) or different to (incongruent) the visually-depicted location. We find that audiovisual congruence was associated with an increase in the probability of participants reporting an audiovisual match of about 0.22 (95% credible interval: [ 0.17 , 0.27 ]), and that participants were more likely to confuse audiovisual pairs as matching if their locations had similar reverberation times. Overall, this study suggests that human perceivers have a capacity to form expectations of reverberation from visual information. Such expectations may be useful for the perceptual challenge of separating sound sources and reverberation from within the signal available at the ear. [ABSTRACT FROM AUTHOR]

Remote acoustic sensing can be used to estimate the error signals in human ears without placing any physical microphones there. In this paper, the coherence between the signals picked up by physical microphones over a sphere surface and the signal obtained at the sphere center is investigated. Based on the multiple channel coherence formulas in the time domain and frequency domain, the relationship between the coherence and the placement of physical microphones is analyzed by numerical simulations first, then the experimental results obtained in a reverberation chamber and a car cabin are presented to verify the simulation results. Finally, a placement of physical microphones for active control of road noise in car cabins is discussed. Both the numerical and experimental results show that an upper limit frequency exists for accurate sound pressure estimation at the center of a sphere with the sound pressure on the sphere surface. For a sufficiently complex sound field such as that in a reverberation room or in a car, half the wavelength of the upper limit frequency is about the average distance among the physical microphones. [ABSTRACT FROM AUTHOR]

• Build a system that integrates salient object detection, voice interaction, holographic computation, and reconstruction modules, ultimately creating a holographic voice-interactive system. • The proposed U-blocks and U-net based reverse attention residual algorithm are used to generate more effective and accurate point cloud datasets during the acquisition phase. • In our holographic voice-interactive system, the ChatGLM model serves as the core module for voice interaction, used within our holographic display system. It converts user speech input into text information and executes corresponding operations or provides feedback based on the text content, enabling further system processing or response. • In a comparison between the wavefront-recording plane (WRP) and point cloud gridding (PCG) methods, the computation speeds of the proposed Taylor Rayleigh-Sommerfeld diffraction point cloud gridding algorithm (TRS-PCG) are faster. In recent years, intelligent voice interaction technology and holographic display technology have garnered significant attention. We propose a holographic voice-interactive system. The holographic voice interaction system can provide users with a virtual assistant proficient in accurately handling user voice queries, facilitating smoother interactions. Additionally, users can interact with virtual objects via holographic projection, enhancing realism and engagement. In this research, we introduce the U-blocks and U-net based reverse attention residual algorithm to generate more effective and accurate point cloud datasets during the acquisition phase. Furthermore, we integrate the ChatGLM pre-trained language model as the core module for voice interaction in the holographic display system, covering aspects such as text interaction and output control. Additionally, we propose a Taylor Rayleigh-Sommerfeld point cloud gridding method aimed at improving the computational speed of hologram generation. We validate the feasibility of our proposed methods through numerical simulations and optical experiments. [ABSTRACT FROM AUTHOR]

We build a multi-output generative model for quasar spectra and the properties of their black hole engines, based on a Gaussian process latent-variable model. This model treats every quasar as a vector of latent properties such that the spectrum and all physical properties of the quasar are associated with non-linear functions of those latent parameters; the Gaussian process kernel functions define priors on the function space. Our generative model is trained with a justifiable likelihood function that allows us to treat heteroscedastic noise and missing data correctly, which is crucial for all astrophysical applications. It can simultaneously predict unobserved spectral regions and the physical properties of quasars in held-out test data. We apply the model to rest-frame ultraviolet and optical quasar spectra for which precise black hole masses (based on reverberation-mapping measurements) are available. Unlike reverberation-mapping studies that require multi-epoch data, our model predicts black hole masses from single-epoch spectraâ€"even with limited spectral coverage. We demonstrate the capabilities of the model by predicting black hole masses and unobserved spectral regions. We find that we predict black hole masses at close to the best possible accuracy. [ABSTRACT FROM AUTHOR]

Crowd noise is usually the primary noise in large waiting halls, and it is difficult to predict because it is influenced by several factors such as room acoustics and crowd characteristics. This study developed a crowd noise prediction model based on the superposition of direct and reverberant sound energy using the factors of the spatial layout of waiting halls, number and distribution of crowds, behavior ratio (ratio of vocal passengers to the total number of passengers), and average crowd sound power. To verify the model, on-site measurements were conducted in two large waiting halls to obtain the necessary input parameters. The crowd noise levels in one of the waiting halls were obtained from 1-s noise level data after excluding broadcast periods. A method for determining an individual's average sound power based on the model was also presented and found to be approximately 70.6 dB. Finally, the model was verified using measured data, and it showed that the model could accurately predict the average crowd noise level and changing trend of crowd noise in temporal and spatial dimensions with an average R-square of approximately 0.55 and average difference of approximately 1.1 dBA between the predicted and measured results. [ABSTRACT FROM AUTHOR]

Part II of this paper discusses experimental validations of the reconstructed excitation forces acting inside a vibrating structure with the fluid-loading effect taken into consideration. Specifically, the characteristics of the excitation forces such as their locations, types, amplitudes, and spectra are reconstructed by using the modified Helmholtz Equation Least Squares (HELS) method, based on a single set of measurements of the normal surface velocity on the exterior surfaces, as if one could see through such a solid structure. Since the fluid-loading effect has a direct impact on the vibration responses of a structure, it is not possible to derive analytic solutions to vibration responses of the structure. Therefore, numerical solutions are sought by using the boundary element method (BEM). The fluid-loading effect, a.k.a., the reverberation sound field inside the structure is calculated based on the absorption coefficients and surface areas of the interior objects. The reconstructed excitation forces are then compared to the benchmark values and satisfactory agreements are obtained. [ABSTRACT FROM AUTHOR]

This paper reviews some of the highlights of selected topics in ocean acoustics during the thirty years that have passed since the founding of the Journal of Theoretical and Computational Acoustics. Advances in computational methods and computers helped to make computational ocean acoustics a vibrant area of research during that period. The parabolic equation method provides an unrivaled combination of accuracy and efficiency for propagation problems in which the bathymetry, sound speed, and other environmental parameters vary in the horizontal directions. The extension of this approach to cases involving layers that support shear waves has been an active area of research throughout the thirty year period. Interest in basin-scale and global-scale propagation was stimulated by the Heard Island Feasibility Test for monitoring climate change in terms of changes in travel time that occur as the temperature of the ocean rises. Diminishing ice cover in the Arctic, which is one of the consequences of climate change, has stimulated renewed interest in Arctic acoustics during the past decade. Reverberation is a challenging problem that was the topic of a major research program during the beginning of the thirty year period. An innovative approach for making it feasible to solve such problems was applied to data for reverberation from the seafloor and from schools of fish, and some of the findings were featured in Science and Nature. Source localization is one of the core problems in ocean acoustics. When applied on a 2-D array of receivers, an approach based on the eigenvectors of the covariance matrix is capable of separating the signals from different sources from each other, determining when this partitioning step is successful, and tracking sources that cross each other in bearing; one of the advantages of this approach is that it does not require environmental information or solutions of the wave equation. Geoacoustic inversion for estimating the layer structure, wave speeds, density, and other parameters of ocean bottoms has also been a topic of interest throughout the thirty year period. [ABSTRACT FROM AUTHOR]

This paper explores the notion of infrapolitics as the political dimension of reverberation and architectural acoustics. This aim is approached through a media-archaeological counterreading of the history of poor acoustics in the former chamber of the US House of Representatives supplied by historian Emily Thompson, as well as through juxtaposition of other cases of reverberation envelopes from the history of architectural acoustics. A media archaeological approach to reverberation and architectural acoustics, it is argued, approaches infrapolitics as a speculative understanding of the effect of architectural acoustics on early American democracy, and of architectural acoustics on discourse in general. [ABSTRACT FROM AUTHOR]

Indeed, when Sophocles arranged for Antigone to be hanged from a noose, he chose to designate it by the term I brochos i which also signifies a snare for birds.[26] Antigone's death deprives her of air. Brought before Creon after being caught burying her brother for the second time, the voice, the wailing sound of the crying bird, is how Antigone's appearance as a whole is described: "And when after a long time this went away", says the guard, "we saw the girl" (422-423).[8] She is made visible through her voice; Antigone is introduced to the king as an agent, a criminal transgressing his edicts, by means of a sound, rather than a word or an action. Placing, figuratively and concretely, "a body at the drama's center" (p. 16), Cavarero turns to Antigone's body and to the body in I Antigone i as a force that challenges what she elsewhere calls "the devocalization of logos" ([5]), characteristic of the history of metaphysics. In other words, the body, which in Polynices's case designates a particular individual - Cavarero thinks of Polynices's body in almost Lacanian terms, calling it "the substance of the individual" (p. 24) - becomes, in Antigone's case, a placeholder for "carnal excess" (p. 27). [Extracted from the article]

The serrated ventilation dampers for regulation of airflow volume were tested. The computer fluid flow analysis was conducted using the Comsol program. The nature of the flow through the serrated ventilation damper was analyzed to identify the different turbulence regions formed on the airflow field. Additionally, the aerodynamical and acoustical parameters of these blades of ventilation dampers with different serrated trailing and/or leading-edge were studied. The aeroacoustic studies were done in the reverberation room. The sound power level and loss coefficient were determined for the studied models. [ABSTRACT FROM AUTHOR]

In modern communication system, speech communication is almost utilized in vast range of applications. Usually, during transmission of speech signal, environment interference causes degradation of signal. Few speech interference which affects quality of speech signal are acoustic noise, acoustic reverberation or white noise. In this research work, it is aimed to estimate the noise in the speech signal using Recurrent Function Network (RFN). The proposed technique is termed as Recurrent RATS Function Network (RRFN). The proposed network estimates the different noise exists in the input noisy speech signal. Once the noises are identified in speech signal, features are estimated using novel radial based RATS (Robust Automatic Transcription of Speech) approach. Further to enhance the clarity of speech signal, a novel generalized recursive singular value technique integrated in elliptic filter is used to effectively remove noises in the speech signal. Simulation analysis is performed for proposed RFN and compared with existing techniques in terms of PESQ and STOI. The proposed method exhibits good performance improvement over the existing techniques for different SNR levels. [ABSTRACT FROM AUTHOR]

The use of model-based numerical simulations of wave propagation in rooms for engineering applications requires that acoustic conditions for multiple parameters are evaluated iteratively, which is computationally expensive. We present a reduced basis method (RBM) to achieve a computational cost reduction relative to a traditional full-order model (FOM) for wave-based room acoustic simulations with parametrized boundaries. The FOM solver is based on the spectral-element method; however, other numerical methods could be applied. The RBM reduces the computational burden by solving the problem in a low-dimensional subspace for parametrized frequency-independent and frequency-dependent boundary conditions. The problem is formulated in the Laplace domain, which ensures the stability of the reduced-order model (ROM). We study the potential of the proposed RBM in terms of computational efficiency, accuracy, and storage requirements, and we show that the RBM leads to 100-fold speedups for a two-dimensional case and 1000-fold speedups for a three-dimensional case with an upper frequency of 2 and 1 kHz, respectively. While the FOM simulations needed to construct the ROM are expensive, we demonstrate that the ROM has the potential of being 3 orders of magnitude faster than the FOM when four different boundary conditions are simulated per room surface. [ABSTRACT FROM AUTHOR]