Multiple Source Environment Research Articles

The effect of rhythm on selective listening in multiple-source environments for young and older adults

Understanding continuous speech with competing background sounds is challenging, particularly for older adults. One stimulus property that may aid listeners understanding of to-be-attended (target) material is temporal regularity (rhythm). In the context of speech-in-noise understanding, McAuley and colleagues recently showed a target rhythm effect whereby recognition of target speech was better when natural speech rhythm of a target talker was intact than when it was temporally altered. The current study replicates the target rhythm effect using a synthetic vowel sequence paradigm in young adults (Experiment 1) and then uses this paradigm to investigate potential age-related changes in the effect of rhythm on recognition (Experiment 2). Listeners identified the last three vowels of temporally regular (isochronous) and irregular (anisochronous) synthetic vowel sequences in quiet and with a competing background sequence of vowel-like harmonic tone complexes presented at various tempos. The results replicated the target rhythm effect whereby temporal regularity in the vowel sequences improved identification accuracy of young listeners compared to irregular vowel sequences. The magnitude of the effect was not found to be influenced by background tempo, but faster background tempos led to greater vowel identification accuracy independent of regularity. Older listeners also demonstrated a target rhythm effect but received less benefit from the temporal regularity of the target sequences than did young listeners. This study highlights the importance of rhythm for understanding age-related differences in selective listening in complex environments and provides a novel paradigm for investigating effects of rhythm on perception.

Secure cloud‐based e‐learning system with access control and group key mechanism

SummaryThere are lot of research works carried out in the field of Information Technology (IT), which have more impact on the education throughout the world. The main contribution from IT in today's education world is e‐learning. There are several institutions implemented the mechanism and several technologies of e‐learning in different countries. E‐learning provides more flexibility in education. Although there are several organizations and institutions had come up with the e‐learning system, the cost of investment involved for the infrastructure setup is much higher for e‐learning applications. Cloud Computing is one of the important technology, which provides different services, which plays a vital role in the education domain and e‐learning mechanism. In addition, the security factor in sharing the content is also much important nowadays as the content is shared among different countries with multiple source environments. In this paper, cloud‐based e‐learning is implemented using access control mechanism, which prevents the cloud resources from illegal user access. The key management schemes combined with access control technique is discussed for secure content sharing and to protect the e‐learning environment. The traditional e‐learning mechanism is compared with the cloud e‐learning for the better understanding of the cloud usage and advantages. Findings indicate that cloud‐based e‐learning utilizes cloud services in a secure way and also more flexible and scalable in accessing the e‐learning content.

Application of an improved discretisation method for the rotor‐bearing assembly in the radiated noise analysis using Riccati transfer matrix method

An improved discretisation method relative to the geometric dimensions of the rotor-bearing system in the calculation of its critical speeds using the transfer matrix method (TMM) is introduced to enhance the computation precision. This work is motivated by the noise analysis of the power system, wherein the noise source identification in a multiple source environment is challenging and hence the need for a higher degree of accuracy. This new discretisation method is derived according to the principles of the equivalence of mass properties with lumped mass and moment of inertia included. The efficiency of the proposed discretisation method is tested via both simulation studies and real noise data. The Riccati TMM is applied on the equivalent discrete models obtained from the proposed geometric dimension discretisation method (abbreviated to GDDM in this study) as well as the empirical discretisation formula, the comparison of which indicates that the analysis of the rotor-bearing assembly discretised appropriately enough under the GDDM is capable of providing solutions of critical speed and predictions of vibration modes and noise with better precision.

Relay selection Algorithm for wireless cooperative networks: a learning‐based approach

Relay selection in cooperative communication is a crucial task for achieving the spatial diversity since the improper relay selection can decrease the overall capacity of the network. In this study, the authors use a reinforcement learning technique, called as Q-learning (QL), to solve the relay selection problem. They propose a ‘QL-based relay selection algorithm’ (QL-RSA) for wireless cooperative networks that maximises the total capacity of the network. QL-RSA receives the reward (feedback) in terms of the capacity by learning a multi-node amplify-and-forward cooperative environment with time-varying Rayleigh fading channels. The advantages of QL-RSA are that it is less complex, requires less channel feedback information and it is distributed in a multiple-sources environment as it provides each source a self-learning capability to find the optimal relay without exchanging information with other source nodes.

Blind Synchronization in Wireless Acoustic Sensor Networks

The challenge of blindly resynchronizing the data acquisition processes in a wireless acoustic sensor network (WASN) is addressed in this paper. The sampling rate offset (SRO) is precisely modeled as a time scaling. The applicability of a wideband correlation processor for estimating the SRO, even in a reverberant and multiple source environment, is presented. An explicit expression for the ambiguity function, which in our case involves time scaling of the received signals, is derived by applying truncated band-limited interpolation. We then propose the recursive band-limited interpolation (RBI) algorithm for recursive SRO estimation. A complete resynchronization scheme utilizing the RBI algorithm, in parallel with the SRO compensation module, is presented. The resulting resynchronization method operates in the time domain in a sequential manner and is, thus, capable of tracking a potentially time-varying SRO. We compared the performance of the proposed RBI algorithm to other available methods in a simulation study. The importance of resynchronization in a beamforming application is demonstrated by both a simulation study and experiments with a real WASN. Finally, we present an experimental study evaluating the expected SRO level between typical data acquisition devices.

2P1-V09 少素子マイクロフォンアレーを有する音源追尾ロボットの複数音源環境下における音源分離特性

2P1-V09 少素子マイクロフォンアレーを有する音源追尾ロボットの複数音源環境下における音源分離特性

Estimation of multiple sound source directions using artificial robot ears

Estimating the direction of a sound source is an important technique used in various engineering fields, including intelligent robots and surveillance systems. In a household where a user’s voice and noises emitted from electric appliances originate from arbitrary directions in 3-D space, robots need to recognize the directions of multiple sound sources in order to effectively interact with the user.This paper proposes an ear-based estimation (localization) system using two artificial robot ears, each consisting of a spiral-shaped pinna and two microphones, for application in humanoid robots. Four microphones are asymmetrically placed on the left and right sides of the head. The proposed localization algorithm is based on a spatially mapped generalized cross-correlation function which is transformed from the time domain to the space domain by using a measured inter-channel time difference map. For validation of the proposed localization method, two experiments (single- and multiple-source cases) were conducted using male speech. In the case of a single source, with the exception of laterally biased sources, the localization was achieved with an error of less than 10°. In a multiple-source environment, one source was fixed at the front side and the other source changed its direction; from the experimental results, the error rates on the localization of the fixed and varying sources are 0% and 36.9% respectively within an error bound of 15°.

Historical lead isotope record of a sediment core from the Derwent River (Tasmania, Australia): A multiple source environment

A 105cm sediment core from the Derwent River (Tasmania, Australia) was collected in 2004 and was characterised considering both physical (loss on ignition at 550°C and grain size) and chemical (Fe, Cu, Zn, Cd and Pb concentrations, Pb isotope ratios and 210Pb dating) properties. The core was analysed to (i) investigate the historical profiles of some important elements associated with the Risdon zinc refinery adjacent to the Derwent River, (ii) determine Pb isotopic signatures of sediment samples, and (iii) assess the veracity of Pb isotope ratios as indicators of contaminant Pb input. Extractable metal concentrations were (all values as mgkg−1, non-normalised for grain size) Fe: 20,000–35,000, Zn: 42–4500, Pb: 5–1090, Cu: 13–141, and Cd: 1–31; with a close correlation between Cu, Zn, Cd and Pb. Metal enrichment factors (normalised to Al) were Pb: 0.9–144, Zn: 0.8–93, Cd: 0.8–30, Cu: 0.8–8.9 and Fe: 0.9–1.3, confirming anthropogenic contributions of Cu, Zn, Pb and Cd to the sediments. The onset of metal contamination above background levels occurred at a depth between 43 and 49cm, with maximum concentrations noted near 20cm for Cu, Zn, Cd and Pb. Lead isotope ratios were determined in sediments using sector field ICP-MS, and were found to be 36.5–38.8, 16.5–18.7 and 1.07–1.20 for 208Pb/204Pb, 206Pb/204Pb and 206Pb/207Pb ratios, respectively. Major Australian ores processed at the refinery over the previous ~90years include those from Broken Hill, Rosebery, Mt Isa, Elura, Hellyer and Century deposits. Anthropogenic impact by Pb with Broken Hill type isotopic ratio was initially evident in the core at 43–49cm. The introduction of Rosebery and Elura ores to the refinery was also clearly noted. Pb isotope ratios further highlight that the Derwent River has been exposed to a greater impact by anthropogenic Pb in comparison to other major Tasmanian rivers, namely the Huon and Tamar.

Automatic accuracy assessment via hashing in multiple-source environment

Accuracy is a most important data quality dimension and its assessment is a key issue in data management. Most of current studies focus on how to qualitatively analyze accuracy dimension and the analysis depends heavily on experts’ knowledge. Seldom work is given on how to automatically quantify accuracy dimension. Based on Jensen–Shannon divergence (JSD) measure, we propose accuracy of data can be automatically quantified by comparing data with its entity’s most approximation in available context. To quickly identify most approximation in large scale data sources, locality-sensitive hashing ( LSH) is employed to extract most approximation at multiple levels, namely column, record and field level. Our approach can not only give each data source an objective accuracy score very quickly as long as context member is available but also avoid human’s laborious interaction. As an automatic accuracy assessment solution in multiple-source environment, our approach is distinguished, especially for large scale data sources. Theory and experiment show our approach performs well in achieving metadata on accuracy dimension.

ARTSTREAM: a neural network model of auditory scene analysis and source segregation

Multiple sound sources often contain harmonics that overlap and may be degraded by environmental noise. The auditory system is capable of teasing apart these sources into distinct mental objects, or streams. Such an ‘auditory scene analysis’ enables the brain to solve the cocktail party problem. A neural network model of auditory scene analysis, called the ARTSTREAM model, is presented to propose how the brain accomplishes this feat. The model clarifies how the frequency components that correspond to a given acoustic source may be coherently grouped together into a distinct stream based on pitch and spatial location cues. The model also clarifies how multiple streams may be distinguished and separated by the brain. Streams are formed as spectral-pitch resonances that emerge through feedback interactions between frequency-specific spectral representations of a sound source and its pitch. First, the model transforms a sound into a spatial pattern of frequency-specific activation across a spectral stream layer. The sound has multiple parallel representations at this layer. A sound's spectral representation activates a bottom-up filter that is sensitive to the harmonics of the sound's pitch. This filter activates a pitch category which, in turn, activates a top-down expectation that is also sensitive to the harmonics of the pitch. Resonance develops when the spectral and pitch representations mutually reinforce one another. Resonance provides the coherence that allows one voice or instrument to be tracked through a noisy multiple source environment. Spectral components are suppressed if they do not match harmonics of the top-down expectation that is read-out by the selected pitch, thereby allowing another stream to capture these components, as in the ‘old-plus-new heuristic’ of Bregman. Multiple simultaneously occurring spectral-pitch resonances can hereby emerge. These resonance and matching mechanisms are specialized versions of Adaptive Resonance Theory, or ART, which clarifies how pitch representations can self-organize during learning of harmonic bottom-up filters and top-down expectations. The model also clarifies how spatial location cues can help to disambiguate two sources with similar spectral cues. Data are simulated from psychophysical grouping experiments, such as how a tone sweeping upwards in frequency creates a bounce percept by grouping with a downward sweeping tone due to proximity in frequency, even if noise replaces the tones at their intersection point. Illusory auditory percepts are also simulated, such as the auditory continuity illusion of a tone continuing through a noise burst even if the tone is not present during the noise, and the scale illusion of Deutsch whereby downward and upward scales presented alternately to the two ears are regrouped based on frequency proximity, leading to a bounce percept. Since related sorts of resonances have been used to quantitatively simulate psychophysical data about speech perception, the model strengthens the hypothesis that ART-like mechanisms are used at multiple levels of the auditory system. Proposals for developing the model to explain more complex streaming data are also provided.

Comparisons of multi-source localization and spatial filtering techniques

Localization of moving sources in a multiple source environment has been investigated with simulated annealing algorithms. Results obtained, both by classical annealing and by fast simulated annealing using a rotated coordinate basis, are presented. The fast annealing method varies from the classical method in that each parameter is varied only once per temperature reduction, resulting in many fewer iteration calls per inversion. Accuracy and efficiency for these methods as a function of signal-to-noise ratio are examined using simulated data containing a weak source in the presence of a loud interferer. A method for filtering element level data prior to inversion is compared to subarray processing for effectiveness in localizing the source of interest. The effect of varying the level of the weak source relative to the level of the interferer, as well as the sources azimuthal separation, is also presented. Comparisons between an equally spaced horizontal line array (HLA) and an HLA with nonuniform sensor spacing are made. Finally, comparisons of the inversion techniques for a real data set from a nonuniformly spaced HLA at a Gulf of Mexico site, where ground truth bottom properties have been established, are discussed. [Work sponsored by ONR.]

Hybrid tool for quickly estimating the radiated acoustic power from a vibrating structure in a multiple-source environment

This paper presents a new hybrid method for predicting overestimating and underestimating indicators of the acoustic power radiated by a vibrating surface even in the presence of other surrounding acoustic sources. This method is applicable to plates or low curvature surfaces radiating in open acoustic fields. The method is hybrid in the sense that the vibration field is measured and the parietal pressure field is predicted considering two extreme academic cases "baffled" and "unbaffled." Many simplifications are made and justified in order to save running time. The method is successfully validated in comparison with experimental results on both laboratory and real life structures. This method has led to a quick tool, allowing one to obtain a good approximation of the radiated power in a few minutes. It provides a natural extension of a classical analyzer for vibroacoustics engineering.

A neural model of auditory scene analysis and source segregation

In environments with multiple sound sources, the auditory system is capable of teasing apart the impinging jumbled signal into different mental objects or streams. A neural model of auditory scene analysis is presented that groups different frequency components based on pitch and spatial location cues, and selectively allocates the components to different streams. Grouping is accomplished through a resonance that develops between a given object’s pitch, its harmonic spectral components, and (to a lesser extent) its spatial location. Those spectral components that are not reinforced by being matched with the top-down prototype read-out by the selected object’s pitch representation are suppressed, thereby allowing another stream to capture these components. The model simulates data from psychophysical grouping experiments, such as how an upward sweeping tone creates a bounce percept by grouping with a downward sweeping tone due to frequency proximity, even if noise replaces the tones at their intersection point. The model also simulates illusory auditory percepts such as the auditory continuity illusion, and the Deutsch scale illusion whereby downward and upward scales presented alternately to two ears regroup based on frequency proximity. Stream resonances provide the coherence whereby one voice or instrument is tracked through a multiple source environment.

The two source maximum likelihood function

The maximum likelihood method is designed to yield high resolution estimates in a multiple source environment. The article derive a simplified representation of the maximum likelihood function for the two source case. This case is instructive to understand when and why the full power of the maximum likelihood method should be used. This approach extends the results of a previous paper (see J. Piper, IEEE Trans. Signal Processing, vol.42, no.2, p.412, 1994) that showed how the maximum likelihood function calculation can be transformed from a matrix problem to a vector product. The maximum likelihood function for spectral estimation is given. >

Acoustic binaural correspondence used for localization of natural acoustic signals

The left-right signal correspondence problem, that is considered as one of the most prominent problems by visual stereoscopic computational models, is much ignored by computational auditory stereophonic models. The correspondence problem, which is trivial if only one acoustic source is present, is highly complicated for a multiple sources environment. We present a computational model able to perform localization of natural complex acoustic signals (one or two human speakers). The model relies mainly on computing the cross-correlation functions of selected frequency channels arriving at the two ears, and performing a weighted integration on these functions. Thus, first attempts are made to establish a correspondence between acoustic features of the two channels. Preliminary results show that this model, which might be compared to “early vision” models in computational vision research, can serve as a first step in analyzing the acoustic scene.

Self-cohering conditionally constrained minimum variance matched-field processing in a random ocean environment

In recent work, minimum variance (MV) beamforming with sound-speed perturbation constraints (MV–SPC) [J. L. Krolik, J. Acoust. Soc. Am. 92, 1408–1419 (1992)] was proposed as a means of improving the robustness of MV matched-field source localization methods to random sound-speed profile inhomogeneities in the ocean channel. In this paper, an extension of the approach is developed that uses wave-front measurements from a source-of-opportunity to substantially improve MV–SPC beamformer performance. The proposed method consists of MV–SPC beamforming with constraints derived from the statistics of hypothesized point-source wave-front replica vectors conditioned on the measurement of a source-of-opportunity wave front at a particular point in time and/or space. Using apriori knowledge of the space-time correlation of sound-speed inhomogeneities, optimal prediction of the conditional signal wave-front correlation matrix is used to compute more precise MV–SPC beamformer constraints. The method also includes an accurate procedure for estimating a source-of-opportunity wave front in a multiple source environment. [Work supported by ONR.]

The identification of the source of machine noises contained within a multiple-source environment

For the purpose of monitoring the condition of machine components there is evidence to suggest that the logging of sound spectra and comparison with a reference spectrum can aid in the formation of decisions regarding individual components of a machine. Since most machines operate in enclosures among other machinery, it is important to assess the problems involved in isolating individual sound sources under such conditions. This investigation explored the response of six machine tools in a workshop when operating individually (solo) and together (simultaneously). Studies are made of the respective time-domain wave forms, decibel-frequency spectra (sound signatures) and power spectral density-frequency spectra. A comparison has been made between the resulting power spectral density spectra when all machines are working together and the computer-summated spectra of the machines when running individually. There is reason to believe that the discrete frequencies of separate components within a machine can be separated from the sound in a multiple-source sound environment. Results suggest that the greatest sensitivity is likely to be achieved within the frequency range 100 to 600 Hz and that higher frequency effects may be influenced by field reverberation effects of the enclosure.