相关论文: Erie: A Declarative Grammar for Data Sonification
The Internet enables users to access vast resources, but it can also expose users to harmful cyber-attacks. This paper investigates human factors issues concerning the use of sounds in a cyber-security domain. It describes a methodology,…
New system for i-vector speaker recognition based on variational autoencoder (VAE) is investigated. VAE is a promising approach for developing accurate deep nonlinear generative models of complex data. Experiments show that VAE provides…
Sonification can provide valuable insights about data but most existing approaches are not designed to be controlled by the user in an interactive fashion. Interactions enable the designer of the sonification to more rapidly experiment with…
Semantic embeddings play a crucial role in natural language-based information retrieval. Embedding models represent words and contexts as vectors whose spatial configuration is derived from the distribution of words in large text corpora.…
Social robots are required not only to understand human intentions but also to effectively communicate their intentions or own internal states to users. This study explores the use of sonification to provide explicit auditory feedback,…
Machine learning techniques have proved useful for classifying and analyzing audio content. However, recent methods typically rely on abstract and high-dimensional representations that are difficult to interpret. Inspired by…
What audio embedding approach generalizes best to a wide range of downstream tasks across a variety of everyday domains without fine-tuning? The aim of the HEAR benchmark is to develop a general-purpose audio representation that provides a…
SoundSignature is a music application that integrates a custom OpenAI Assistant to analyze users' favorite songs. The system incorporates state-of-the-art Music Information Retrieval (MIR) Python packages to combine extracted…
Even when actual technologies present the potential to augment inclusion and the United Nations has been stablished the digital access to information as a human right, people with disabilities continuously faced barriers in their…
Based on a case study on 3D printing, we have been experimenting on the sonification of multidimensional data for peripheral process monitoring. In a previous paper, we tested the effectiveness of a soundscape which combined intentionally…
In recent years, the burgeoning interest in diffusion models has led to significant advances in image and speech generation. Nevertheless, the direct synthesis of music waveforms from unrestricted textual prompts remains a relatively…
In today's tech-driven world, significant advancements in artificial intelligence and virtual reality have emerged. These developments drive research into exploring their intersection in the realm of soundscape. Not only do these…
The task of audio-visual sound source localization has been well studied under constrained scenes, where the audio recordings are clean. However, in real-world scenarios, audios are usually contaminated by off-screen sound and background…
To build speech processing methods that can handle speech as naturally as humans, researchers have explored multiple ways of building an invertible mapping from speech to an interpretable space. The articulatory space is a promising…
The virtual world is being established in which digital humans are created indistinguishable from real humans. Producing their audio-related capabilities is crucial since voice conveys extensive personal characteristics. We aim to create a…
The research in Deep Learning applications in sound and music computing have gathered an interest in the recent years; however, there is still a missing link between these new technologies and on how they can be incorporated into real-world…
This work was developed aiming to employ Statistical techniques to the field of Music Emotion Recognition, a well-recognized area within the Signal Processing world, but hardly explored from the statistical point of view. Here, we opened…
High-stakes applications require AI-generated models to be interpretable. Current algorithms for the synthesis of potentially interpretable models rely on objectives or regularization terms that represent interpretability only coarsely…
Robotic perception is becoming a key technology for navigation aids, especially helping individuals with visual impairments through spatial sonification. This paper introduces a mapping representation that accurately captures scene geometry…
Data analysis in space sciences has been performed exclusively visually for years, despite the fact that the largest amount of data belongs to non-visible portions of the electromagnetic spectrum. This, on the one hand, limits the study of…