Cocktail Party Research Articles

A new graph theoretic analytical method for nonlinear distributed order fractional ordinary differential equations by clique polynomial of cocktail party graph

In this paper, we presented a new analytical method for one of the rapidly emerging branches of fractional calculus, the distributed order fractional differential equations (DFDE). Due to its significant applications in modeling complex physical systems, researchers have shown profound interest in developing various analytical and numerical methods to study DFDEs. With this motivation, we proposed an easy computational technique with the help of graph theoretic polynomials from algebraic graph theory for nonlinear distributed order fractional ordinary differential equations (NDFODE). In the method, we used clique polynomials of the cocktail party graph as an approximation solution. With operational integration and fractional differentiation in the Caputo sense, the NDFODEs transformed into a system of algebraic equations and then solved by Newton–Raphson's method to determine the unknowns in the Clique polynomial approximation. The proficiency of the proposed Clique polynomial collocation method (CCM) is illustrated with four numerical examples. The convergence and error analysis are discussed in tabular and graphical depictions by comparing the CCM results with the results of existing numerical methods.

Minimum Injective Eccentric Dominating Energy of Graphs

The minimum injective eccentric dominating energy of a graph is defined. The minimum injective eccentric dominating energy for star, complete and cocktail party graphs are computed. Inspired by McClelland’s bounds for energy of a graph, the upper and lower bounds of minimum injective eccentric dominating energy for star, complete and cocktail party graphs are discussed. Properties of eigenvalues of minimum injective eccentric dominating matrix for star, complete and cocktail party graphs are discussed.

Solve Cocktail Party Problem Based on Hybrid Method

Solve Cocktail Party Problem Based on Hybrid Method

Peace needs constant reproduction: The temporality of the diplomatic system

If a diplomatic cocktail party lasts two hours, does it equal the duration of peace? Or are there less simplistic conceptualizations of ‘peace’ and ‘time’ for the theorization of diplomatic practices? This article draws on a concept of temporality based on an irreversible before/after distinction, and combines it with the modern systems theoretical premise that every event within the diplomatic system occurs under the medium of peace, finding that: (a) peace is not a state of affairs, but a medium of communication; (b) peace has no chronometric duration, but it is temporally minimal, vanishing as soon as it appears; (c) peace needs constant reproduction, i.e. the system of diplomacy regenerates itself by continuously triggering further peace-mediated events; and (d) peace is both negative and positive, as it denotes a restraint of violent capacities but needs active communication. These insights offer a universal concept of ‘peace’ that is abstract enough to cover every interpolity tie. They also suggest further research opportunities, including into what the rapid acceleration of society means for the proliferation of ever-quicker, ever-more-trivial diplomatic practices.

Sound masking by a low-pitch speech-shaped noise improves a social robot's talk in noisy environments.

Introduction: There has been a surge in the use of social robots for providing information, persuasion, and entertainment in noisy public spaces in recent years. Considering the well-documented negative effect of noise on human cognition, masking sounds have been introduced. Masking sounds work, in principle, by making the intrusive background speeches less intelligible, and hence, less distracting. However, this reduced distraction comes with the cost of increasing annoyance and reduced cognitive performance in the users of masking sounds. Methods: In a previous study, it was shown that reducing the fundamental frequency of the speech-shaped noise as a masking sound significantly contributes to its being less annoying and more efficient. In this study, the effectiveness of the proposed masking sound was tested on the performance of subjects listening to a lecture given by a social robot in a noisy cocktail party environment. Results: The results indicate that the presence of the masking sound significantly increased speech comprehension, perceived understandability, acoustic satisfaction, and sound privacy of the individuals listening to the robot in an adverse listening condition. Discussion: To the knowledge of the authors, no previous work has investigated the application of sound masking technology in human-robot interaction designs. The future directions of this trend are discussed.

A Bio-Inspired Spiking Attentional Neural Network for Attentional Selection in the Listening Brain.

Humans show a remarkable ability in solving the cocktail party problem. Decoding auditory attention from the brain signals is a major step toward the development of bionic ears emulating human capabilities. Electroencephalography (EEG)-based auditory attention detection (AAD) has attracted considerable interest recently. Despite much progress, the performance of traditional AAD decoders remains to be improved, especially in low-latency settings. State-of-the-art AAD decoders based on deep neural networks generally lack the intrinsic temporal coding ability in biological networks. In this study, we first propose a bio-inspired spiking attentional neural network, denoted as BSAnet, for decoding auditory attention. BSAnet is capable of exploiting the temporal dynamics of EEG signals using biologically plausible neurons and an attentional mechanism. Experiments on two publicly available datasets confirm the superior performance of BSAnet over other state-of-the-art systems across various evaluation conditions. Moreover, BSAnet imitates realistic brain-like information processing, through which we show the advantage of brain-inspired computational models.

The effect of gaze on EEG measures of multisensory integration in a cocktail party scenario.

Seeing the speaker's face greatly improves our speech comprehension in noisy environments. This is due to the brain's ability to combine the auditory and the visual information around us, a process known as multisensory integration. Selective attention also strongly influences what we comprehend in scenarios with multiple speakers-an effect known as the cocktail-party phenomenon. However, the interaction between attention and multisensory integration is not fully understood, especially when it comes to natural, continuous speech. In a recent electroencephalography (EEG) study, we explored this issue and showed that multisensory integration is enhanced when an audiovisual speaker is attended compared to when that speaker is unattended. Here, we extend that work to investigate how this interaction varies depending on a person's gaze behavior, which affects the quality of the visual information they have access to. To do so, we recorded EEG from 31 healthy adults as they performed selective attention tasks in several paradigms involving two concurrently presented audiovisual speakers. We then modeled how the recorded EEG related to the audio speech (envelope) of the presented speakers. Crucially, we compared two classes of model - one that assumed underlying multisensory integration (AV) versus another that assumed two independent unisensory audio and visual processes (A+V). This comparison revealed evidence of strong attentional effects on multisensory integration when participants were looking directly at the face of an audiovisual speaker. This effect was not apparent when the speaker's face was in the peripheral vision of the participants. Overall, our findings suggest a strong influence of attention on multisensory integration when high fidelity visual (articulatory) speech information is available. More generally, this suggests that the interplay between attention and multisensory integration during natural audiovisual speech is dynamic and is adaptable based on the specific task and environment.

Dementia is an auditory brain disorder

AbstractBackgroundWhile impaired hearing has emerged as a major potentiating factor for dementia, the basis for this relationship has not been defined. Most studies have emphasised the role of peripheral hearing loss. However, we hear with our brains: natural listening places immense computational demands on neural circuitry, and the neural networks pre‐eminently targeted by major dementias are essential for decoding and responding appropriately to the auditory environment. Auditory brain dysfunction is therefore predicted both to contribute importantly to hearing impairment in Alzheimer’s and other dementias and to be integral to the expression of neurodegenerative pathologies. Here I present an overview of evidence that speaks to this hypothesis.MethodsIn a series of linked experiments, we have assessed aspects of auditory cognition – the processes whereby the brain perceives, interprets and acts upon sounds ‐ in patient cohorts with Alzheimer’s disease and major syndromes of frontotemporal dementia, relative to healthy older individuals. We designed novel psychoacoustic tests to assess aspects of auditory scene analysis (the ‘cocktail party effect’ and localisation of sounds in space), comprehension of acoustically degraded speech and the processing of semantic and emotional information in sound in cognitively impaired people. Neuroanatomical mechanisms were assessed using voxel‐based morphometry and functional MRI.ResultsAcross experiments, after taking peripheral hearing function and general cognitive performance into account, patients with Alzheimer’s disease and frontotemporal dementias showed characteristic ‘auditory phenotypes’ or profiles of auditory cognitive impairment. Alzheimer’s disease is associated with impaired auditory scene analysis, linked to atrophy and dysfunction of temporo‐parietal cortical regions in the core ‘default mode network’ targeted by Alzheimer pathology. Frontotemporal dementia syndromes produce distinct impairments of auditory feature analysis, sound recognition and emotional valuation.ConclusionsAuditory brain dysfunction plays a key role in everyday hearing impairment and reflects core pathophysiology in major dementias. These findings raise the exciting prospect that auditory cognitive measures might be used in the early diagnosis of dementia, in guiding novel hearing interventions and as dynamic markers of therapeutic response in the dawning era of disease modification.

Free-Field Hearing Test in Noise with Free Head Rotation for Evaluation of Monaural Hearing.

There is a discrepancy between the hearing test results in patients with single-sided deafness (SSD) and their reported outcome measures. This is probably due to the presence of two elements in everyday situations: noise and head movements. We developed a stereo-audiometric test in noise with free head movements to evaluate movements and auditory performance in monaural and binaural conditions in normal hearing volunteers with one occluded ear. Tests were performed in the binaural condition (BIN), with the left ear (LEO) or the right ear occluded (REO). The signal was emitted by one of the seven speakers, placed every 30° in a semicircle, and the noise (cocktail party) by all speakers. Subjects turned their head freely to obtain the most comfortable listening position, then repeated 10 sentences in this position. In monaural conditions, the sums of rotations (head rotations for an optimal hearing position in degrees, random signal azimuth, 1 to 15 signal ad lib signal presentations) were higher (LEO 255 ± 212°, REO 308 ± 208° versus BIN 74 ± 76, p < 0.001, ANOVA) than those in the BIN condition and the discrimination score (out of 10) was lower than that in the BIN condition (LEO 5 ± 1, REO 7 ± 1 versus BIN 8 ± 1, respectively p < 0.001 and p < 0.05 ANOVA). In the monaural condition, total rotation and discrimination in noise were negatively correlated with difficulty (Pearson r = -0.68, p < 0.01 and -0.51, p < 0.05, respectively). Subjects' behaviors were different in optimizing their hearing in noise via head rotation. The evaluation of head movements seems to be a significant parameter in predicting the difficulty of monaural hearing in noisy environments.

Detecting a periodic signal by a population of spiking neurons in the weakly nonlinear response regime

Motivated by experimental observations, we investigate a variant of the cocktail party problem: the detection of a weak periodic stimulus in the presence of fluctuations and another periodic stimulus which is stronger than the periodic signal to be detected. Specifically, we study the response of a population of stochastic leaky integrate-and-fire (LIF) neurons to two periodic signals and focus in particular on the question, whether the presence of one of the stimuli can be detected from the population activity. As a detection criterion, we use a simple threshold-crossing of the population activity over a certain time window. We show by means of the receiver operating characteristics (ROC) that the detectability depends only weakly on the time window of observation but rather strongly on the stimulus amplitude. Counterintuitively, the detection of the weak periodic signal can be facilitated by the presence of a strong periodic input current depending on the frequencies of the two signals and on the dynamical regime in which the neurons operate. Beside numerical simulations of the model, we present an analytical approximation for the ROC curve that is based on the weakly nonlinear response theory for a stochastic LIF neuron.Graphic abstract

Pentadic Criticism of T.S. Eliot’s Plays

This study applies Burke’s Pentadic Criticism on the study of selected plays (the Family Reunion and the Cocktail Party by T.S. Eliot) to explore the pentadic elements inherent in each of them. From the perspective of pentadic criticism, the five elements of act, agent, agency, scene, and purpose in the plays, as well as the ten pairs of ratios between them are probed into to figure out the rhetors’ motives individually. Through the analyses of both pentadic criticism, the researcher finds out that the rhetors’ motives can be discerned by analyzing their choices in shaping the acts, scenes, agents, agencies, and purposes within the play.

A Facial Feature and Lip Movement Enhanced Audio-Visual Speech Separation Model.

The cocktail party problem can be more effectively addressed by leveraging the speaker's visual and audio information. This paper proposes a method to improve the audio's separation using two visual cues: facial features and lip movement. Firstly, residual connections are introduced in the audio separation module to extract detailed features. Secondly, considering the video stream contains information other than the face, which has a minimal correlation with the audio, an attention mechanism is employed in the face module to focus on crucial information. Then, the loss function considers the audio-visual similarity to take advantage of the relationship between audio and visual completely. Experimental results on the public VoxCeleb2 dataset show that the proposed model significantly enhanced SDR, PSEQ, and STOI, especially 4 dB improvements in SDR.

EEG-based speaker-listener neural coupling reflects speech-selective attentional mechanisms beyond the speech stimulus.

When we pay attention to someone, do we focus only on the sound they make, the word they use, or do we form a mental space shared with the speaker we want to pay attention to? Some would argue that the human language is no other than a simple signal, but others claim that human beings understand each other because they form a shared mental ground between the speaker and the listener. Our study aimed to explore the neural mechanisms of speech-selective attention by investigating the electroencephalogram-based neural coupling between the speaker and the listener in a cocktail party paradigm. The temporal response function method was employed to reveal how the listener was coupled to the speaker at the neural level. The results showed that the neural coupling between the listener and the attended speaker peaked 5s before speech onset at the delta band over the left frontal region, and was correlated with speech comprehension performance. In contrast, the attentional processing of speech acoustics and semantics occurred primarily at a later stage after speech onset and was not significantly correlated with comprehension performance. These findings suggest a predictive mechanism to achieve speaker-listener neural coupling for successful speech comprehension.

Statistical learning at a virtual cocktail party

Statistical learning – the ability to extract distributional regularities from input – is suggested to be key to language acquisition. Yet, evidence for the human capacity for statistical learning comes mainly from studies conducted in carefully controlled settings without auditory distraction. While such conditions permit careful examination of learning, they do not reflect the naturalistic language learning experience, which is replete with auditory distraction – including competing talkers. Here, we examine how statistical language learning proceeds in a virtual cocktail party environment, where the to-be-learned input is presented alongside a competing speech stream with its own distributional regularities. During exposure, participants in the Dual Talker group concurrently heard two novel languages, one produced by a female talker and one by a male talker, with each talker virtually positioned at opposite sides of the listener (left/right) using binaural acoustic manipulations. Selective attention was manipulated by instructing participants to attend to only one of the two talkers. At test, participants were asked to distinguish words from part-words for both the attended and the unattended languages. Results indicated that participants’ accuracy was significantly higher for trials from the attended vs. unattended language. Further, the performance of this Dual Talker group was no different compared to a control group who heard only one language from a single talker (Single Talker group). We thus conclude that statistical learning is modulated by selective attention, being relatively robust against the additional cognitive load provided by competing speech, emphasizing its efficiency in naturalistic language learning situations.

Solving the cocktail party problem using Multi-modal Hearing Assistive Technology Prototype

Hearing loss is a major global health problem, affecting over 1.5 billion people. According to estimations by the World Health Organization, 83% of those who could benefit from hearing assistive devices do not use them. The limited adoption of hearing aids can be attributed to the suboptimal performance in acoustically challenging environments, such as cocktail parties, where there are multiple competing speakers and noise sources leading to poor speech intelligibility for hearing impaired listeners. This work presents a first-of-its-kind real-time, multi-modal speech enhancement system that can effectively enhance speech in challenging real noisy environments. The system exploits both audio and visual cues to isolate the target speaker's voice from interfering background noises. The system is developed using deep neural networks and is integrated with the Open Master Hearing Aid (openMHA) platform. The integrated prototype was evaluated in a cocktail party setting to isolate the target speaker's voice from interfering speakers, music, and other non-speech noise sources and was able to significantly improve the speech intelligibility of hearing impaired listeners. This work has the potential to improve the quality of life for hearing impaired listeners by facilitating effective communication in cocktail party environments.

Towards audiovisual scene analysis and object formation

The neural mechanisms underpinning auditory scene analysis and object formation have been of intense research interest in the past two decades. Fundamentally, however, we live in a multisensory environment. Even Cherry in his original paper posited that “lip reading” as a way for us to solve the cocktail party problem. Yet, how different aspects of visual cues (e.g., timing, linguistic information) help listeners follow conversation in a complex acoustic scene is still not well understood. In this talk, we present a theoretical framework to study audiovisual scene analysis that has been extrapolated from the unisensory object-based attention literature and posit the following questions: How do we define a multi-modal object? What are the predictions from unisensory object-based attention theory when we apply to the audiovisual domain? What are the conceptual models to test the different neural mechanisms that underpin audiovisual scene analysis? Answering these questions would move us closer to addressing the cocktail party problem in the real-world setting as well as help us create, de novo, audiovisual scenes that are more engaging in the augmented/virtual reality world.

An Ethical Literary Analysis of Edward’s Ethical Choices in The Cocktail Party

This paper examines Edward's ethical choices in T.S. Eliot's play, "The Cocktail Party," through the lens of ethical literary criticism. Edward, the protagonist, faces an emotional crisis in his relationships with his wife, Lavinia, and his lover, Celia, which sets the stage for his ethical dilemma. The study utilizes a qualitative research design, employing literary analysis and interpretation to delve deeper into Edward's ethical choices and their appropriateness within his particular situations and ethical environment. Drawing from previous scholarly work, particularly from scholars in China who have explored the ethical fables and perspectives within "The Cocktail Party," this paper builds upon the existing research by offering further insights into Edward's ethical journey. The analysis considers the interplay between Edward's marital and romantic ethical identities and his professional identity as a lawyer, which results in contradictions and conflicts, leading to ethical dilemmas. The study also explores the factors influencing Edward's ethical choices, including the disruption of ethical relationships and order within the play. By applying ethical literary criticism, the paper argues that Edward's ethical choices are not arbitrary but appropriate responses to his circumstances. Situational ethics and love norms are examined to understand the motivations and justifications behind Edward's decisions. Ultimately, the analysis provides a comprehensive exploration of the ethical themes within the play, shedding light on the complexities of decision-making processes and the moral dimensions of literary works.

A robust and compact population code for competing sounds in auditory cortex.

Cortical circuits encoding sensory information consist of populations of neurons, yet how information aggregates via pooling individual cells remains poorly understood. Such pooling may be particularly important in noisy settings where single-neuron encoding is degraded. One example is the cocktail party problem, with competing sounds from multiple spatial locations. How populations of neurons in auditory cortex code competing sounds have not been previously investigated. Here, we apply a novel information-theoretic approach to estimate information in populations of neurons in mouse auditory cortex about competing sounds from multiple spatial locations, including both summed population (SP) and labeled line (LL) codes. We find that a small subset of neurons is sufficient to nearly maximize mutual information over different spatial configurations, with the labeled line code outperforming the summed population code and approaching information levels attained in the absence of competing stimuli. Finally, information in the labeled line code increases with spatial separation between target and masker, in correspondence with behavioral results on spatial release from masking in humans and animals. Taken together, our results reveal that a compact population of neurons in auditory cortex provides a robust code for competing sounds from different spatial locations.NEW & NOTEWORTHY Little is known about how populations of neurons within cortical circuits encode sensory stimuli in the presence of competing stimuli at other spatial locations. Here, we investigate this problem in auditory cortex using a recently proposed information-theoretic approach. We find a small subset of neurons nearly maximizes information about target sounds in the presence of competing maskers, approaching information levels for isolated stimuli, and provides a noise-robust code for sounds in a complex auditory scene.

A novel analytical method for the multi-delay fractional differential equations through the matrix of clique polynomials of the cocktail party graph

This paper provides a unique graph matrix approach based on the Clique polynomials of the Cocktail party graph to effectively solve multi-delay fractional differential equations (MDFDE) with variable coefficients. Clique polynomials of the cocktail party graph’s basis are used as a trial function for the solution of MDFDE. An operational matrix of Caputo fractional derivative of polynomial approximation is employed to transform the MDFDEs into a system of algebraic equations. The unknowns in the system are determined by Newton’s method in Mathematica. The productivity of the suggested strategy is examined with five numerical examples. From all the discussed examples, it is observed that the proposed Clique polynomial collocation method (CPCM) has excellent compatibility with linear MDFDEs by attaining an exact solution. To substantiate the validity of the recommended method, obtained results with comparisons, computation time, convergence analysis, error estimations, and graphical illustrations are offered.

A Hardware-Friendly Real-Time Implementation of the Auditory Attention Based on a Novel Spiking Winner-Take-All Network

In recent decades, the modeling and designing of neuromorphic systems have received considerable attention, leading to the development of electrophysiological devices that can mimic the dynamic behavior of cortical networks. Some features such as parallel processing, real-time performance, reconfigurability, low production cost, and good accuracy, make field programmable gate arrays (FPGAs) an ideal hardware platform for implementing spiking neural networks (SNN), which has become very popular in the field of neural computing. In this work, we investigated a high-performance FPGA design of the auditory attention to simulate the on-chip ‘cocktail party’ effect similar to what happens in the brain. In the first step, we introduce a novel spiking winner-take-all (SWTA) network consisting of a hardware-friendly Izhikevich neuron model and explore its biological characteristics and stability. We then use this network as a receptive field in the primary auditory cortex, which is tuned by attention signals. The desired sound frequency will be selected as the target and transmitted to the higher layers of the auditory cortex for further processing, while other frequencies are severely suppressed. Experimental results show that the proposed network accurately follows the dynamic behavior defined in the auditory attention theory, and emphasizes the resource consumption after post place and routes on a fully efficient hardware implementation, where less than 4% of the resources were used to implement a network with 1856 neurons.