"Can you hear me now?" : Automatic assessment of background noise intrusiveness and speech intelligibility in telecommunications

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The evolution of airborne mapping witnesses the introduction of hybrid lidar-camera systems to enhance data collection, i.e. to obtain simultaneously high-density point-cloud and texture. Yet, the common adjustment of both optical data streams is a nontriv ...

Low-light photography produces images with low signal-to-noise ratios due to limited photons. In such conditions, common approximations like the Gaussian noise model fall short, and many denoising techniques fail to remove noise effectively. Although deep- ...

The current machine learning paradigm relies on continuous representations and fixed neural network architectures to approximate environmental structures, leading to challenges with continual learning, internal structure design, and goal-directed behavior ...

Atypical aspects in speech concern speech that deviates from what is commonly considered normal or healthy. In this thesis, we propose novel methods for detection and analysis of these aspects, e.g. to monitor the temporary state of a speaker, diseases tha ...

Speech recognition-based applications upon the advancements in artificial intelligence play an essential role to transform most aspects of modern life. However, speech recognition in real-life conditions (e.g., in the presence of overlapping speech, varyin ...

This paper introduces Wireless IoT-based Noise Cancellation (WINC) which defines a framework for leveraging a wireless network of IoT microphones to enhance active noise cancellation in noise-canceling headphones. The IoT microphones forward ambient noise ...

The past decades have witnessed rapid growth in imaging as a major form of communication between individuals. Due to recent advances in capture, storage, delivery and display technologies, consumers demand improved perceptual quality while requiring reduce ...

As large, data-driven artificial intelligence models become ubiquitous, guaranteeing high data quality is imperative for constructing models. Crowdsourcing, community sensing, and data filtering have long been the standard approaches to guaranteeing or imp ...

Marmoset monkeys encode vital information in their calls and serve as a surrogate model for neuro-biologists to understand the evolutionary origins of human vocal communication. Traditionally analyzed with signal processing-based features, recent approache ...

Previous studies have shown that access to a satisfactory view to the outside with sufficient daylight is essential for building occupants' health and well-being. It has also been suggested that certain features of visual content improve view-out quality, ...

Federated Learning by nature is susceptible to low-quality, corrupted, or even malicious data that can severely degrade the quality of the learned model. Traditional techniques for data valuation cannot be applied as the data is never revealed. We present ...

Mechanical resonators are widely used in sensors, transducers and optomechanical systems, where mechanical dissipation sets the ultimate limit to performance. Over the past 15 years, the quality factors in strained mechanical resonators have increased by f ...

We prove global in time well-posedness for perturbations of the 2D stochastic Navier-Stokes equations partial derivative( t)u + u center dot del u = Delta u - del p + sigma + xi, u(0, center dot ) = u(0),div (u) = 0, driven by additive space-time white noi ...

A crucial building block of responsible artificial intelligence is responsible data governance, including data collection. Its importance is also underlined in the latest EU regulations. The data should be of high quality, foremost correct and representati ...

Indoor environmental quality (IEQ) has a profound impact on occupant health, comfort, and performance. Various methods are employed to collect feedback from building users, ranging from conventional questionnaires, increasingly utilized physiological monit ...

Visual data play a crucial role in modern society, and the rate at which images and videos are acquired, stored, and exchanged every day is rapidly increasing. Image compression is the key technology that enables storing and sharing of visual content in an ...

Statistical (machine-learning, ML) models are more and more often used in computational chemistry as a substitute to more expensive ab initio and parametrizable methods. While the ML algorithms are capable of learning physical laws implicitly from data, ad ...

We are used to defining network neutrality as absence of traffic differentiation, like policing or shaping. These mechanisms, however, are often not what determines end-users’ quality of experience (QoE). Most content today is accessed through edge caches, ...

At room temperature, mechanical motion driven by the quantum backaction of light has been observed only in pioneering experiments in which an optical restoring force controls the oscillator stiffness1,2. For solid-state mechanical resonators in which oscil ...

Self-supervised learning (SSL) models use only the intrinsic structure of a given signal, independent of its acoustic domain, to extract essential information from the input to an embedding space. This implies that the utility of such representations is no ...

"Can you hear me now?" : Automatic assessment of background noise intrusiveness and speech intelligibility in telecommunications

Chattez avec Graph Search

On the Perspectives of Image-to-Lidar Constraints in Dynamic Network Optimisation

Dark Noise Diffusion: Noise Synthesis for Low-Light Image Denoising

Modelleyen: Continual Learning and Planning via Structured Modelling of Environment Dynamics

Novel Methods For Detection And Analysis Of Atypical Aspects In Speech

Sparse Autoencoders for Speech Modeling and Recognition

WINC: A Wireless IoT Network for Multi-Noise Source Cancellation

On the Performance of Subjective Visual Quality Assessment Protocols for Nearly Visually Lossless Image Compression

Extensions of Peer Prediction Incentive Mechanisms

On the Utility of Speech and Audio Foundation Models for Marmoset Call Analysis

Dynamism in the context of views out: A literature review

A Practical Influence Approximation for Privacy-Preserving Data Filtering in Federated Learning

Ultrahigh-quality-factor micro- and nanomechanical resonators using dissipation dilution

Global existence for perturbations of the 2D stochastic Navier-Stokes equations with space-time white noise

incentive Mechanism Design for Responsible Data Governance: A Large-Scale Field Experiment

Exploring indoor environmental perception through questionnaires, physiological monitoring, and facial expression recognition

JPEG AIC-3 Dataset: Towards Defining the High Quality to Nearly Visually Lossless Quality Range

Encoding quantum-chemical knowledge into machine-learning models of complex molecular properties

Caching and Neutrality

Room-temperature quantum optomechanics using an ultralow noise cavity

Can Self-Supervised Neural Representations Pre-Trained on Human Speech distinguish Animal Callers?