The TCP Control Block Interdependence in Fixed Networks - Some Performance Results

For every TCP connection a TCP sender has a control block in which the current values of the variables and parameters of the connection are stored, e.g., the congestion window size, the slow start threshold, or the (smoothed) round trip time. The information stored in the control blocks of some TCP connections might be useful for other TCP connections, e.g., starting a new TCP connection with more adequate initial values of the variables and parameters than it is designated in standard TCP to increase the throughput of the new TCP connection. This is the idea behind the TCP Control Block Interdependence (TCBI) [1]. Which of the information stored in the control blocks of some TCP connections and how these information are used for a new TCP connection is dependent on the TCBI controller in the TCP sender with TCBI capabilities

Impact of non-individualised head related transfer functions on speech-in-noise performances within a synthesised virtual environment

When performing binaural spatialisation, it is widely accepted that the choice of the head related transfer functions (HRTFs), and in particular the use of individually measured ones, can have an impact on localisation accuracy, externalization, and overall realism. Yet the impact of HRTF choices on speech-in-noise performances in cocktail party-like scenarios has not been investigated in depth. This paper introduces a study where 22 participants were presented with a frontal speech target and two lateral maskers, spatialised using a set of non-individual HRTFs. Speech reception threshold (SRT) was measured for each HRTF. Furthermore, using the SRT predicted by an existing speech perception model, the measured values were compensated in the attempt to remove overall HRTF-specific benefits. Results show significant overall differences among the SRTs measured using different HRTFs, consistently with the results predicted by the model. Individual differences between participants related to their SRT performances using different HRTFs could also be found, but their significance was reduced after the compensation. The implications of these findings are relevant to several research areas related to spatial hearing and speech perception, suggesting that when testing speech-in-noise performances within binaurally rendered virtual environments, the choice of the HRTF for each individual should be carefully considered

The SONICOM Project: artificial intelligence-driven immersive audio, from personalization to modeling

Every individual perceives spatial audio differently, due in large part to the unique and complex shape of ears and head. Therefore, high-quality, headphone-based spatial audio should be uniquely tailored to each listener in an effective and efficient manner. Artificial intelligence (AI) is a powerful tool that can be used to drive forward research in spatial audio personalization. The SONICOM project aims to employ a data-driven approach that links physiological characteristics of the ear to the individual acoustic filters, which allows us to localize sound sources and perceive them as being located around us. A small amount of data acquired from users could allow personalized audio experiences, and AI could facilitate this by offering a new perspective on the matter. A Bayesian approach to computational neuroscience and binaural sound reproduction will be linked to create a metric for AI-based algorithms that will predict realistic spatial audio quality. Being able to consistently and repeatedly evaluate and quantify the improvements brought by technological advancements, as well as the impact these have on complex interactions in virtual environments, will be key for the development of new techniques and for unlocking new approaches to understanding the mechanisms of human spatial hearing and communication

Specifying the Representation of Non-geometric Information in 3D Virtual Environments

In 3D virtual environments (3DVE), we need to know what an object looks like (i.e. geometric information) and what the object is, what are its properties and characteristics and how it relates to other objects (i.e. non-geometric information). Several interactive presentation techniques have been devised to incorporate non-geometric information into 3DVEs. The relevance of a technique depends on the context. Therefore, the choice of an appropriate representation technique cannot be done once for all and must be adapted to the context. In this paper, we first present a preliminary classification of representation techniques for non-geometric information in 3DVE. Then we propose a formalism, based on description logics, to describe the usability of a technique in a given context. We show how these descriptions can be processed to select appropriate techniques when automatically or semi-automatically generating a 3DVE

3D Tune-In Toolkit: An open-source library for real-time binaural spatialisation

The 3D Tune-In Toolkit (3DTI Toolkit) is an open-source standard C++ library which includes a binaural spatialiser. This paper presents the technical details of this renderer, outlining its architecture and describing the processes implemented in each of its components. In order to put this description into context, the basic concepts behind binaural spatialisation are reviewed through a chronology of research milestones in the field in the last 40 years. The 3DTI Toolkit renders the anechoic signal path by convolving sound sources with Head Related Impulse Responses (HRIRs), obtained by interpolating those extracted from a set that can be loaded from any file in a standard audio format. Interaural time differences are managed separately, in order to be able to customise the rendering according the head size of the listener, and to reduce comb-filtering when interpolating between different HRIRs. In addition, geometrical and frequency-dependent corrections for simulating near-field sources are included. Reverberation is computed separately using a virtual loudspeakers Ambisonic approach and convolution with Binaural Room Impulse Responses (BRIRs). In all these processes, special care has been put in avoiding audible artefacts produced by changes in gains and audio filters due to the movements of sources and of the listener. The 3DTI Toolkit performance, as well as some other relevant metrics such as non-linear distortion, are assessed and presented, followed by a comparison between the features offered by the 3DTI Toolkit and those found in other currently available open- and closed-source binaural renderers