相关论文: Erie: A Declarative Grammar for Data Sonification
Event extraction (EE) is a critical direction in the field of information extraction, laying an important foundation for the construction of structured knowledge bases. EE from text has received ample research and attention for years, yet…
Explainable AI has the potential to support more interactive and fluid co-creative AI systems which can creatively collaborate with people. To do this, creative AI models need to be amenable to debugging by offering eXplainable AI (XAI)…
We introduce STRAUSS (Sonification Tools and Resources for Analysis Using Sound Synthesis) a modular, self-contained and flexible Python sonification package, operating in a free and open source (FOSS) capacity. STRAUSS is intended to be a…
We introduce an extensive new dataset of MIDI files, created by transcribing audio recordings of piano performances into their constituent notes. The data pipeline we use is multi-stage, employing a language model to autonomously crawl and…
Sonification is the transformation of data into acoustic signals, achievable through different techniques. Sonification can be defined as a way to represent data values and relations as perceivable sounds, aiming at facilitating their…
Sonification and audification create auditory displays of datasets. Audification translates data points into digital audio samples and the auditory display's duration is determined by the playback rate. Like audification, auditory graphs…
Speaker embedding extractors (EEs), which map input audio to a speaker discriminant latent space, are of paramount importance in speaker diarisation. However, there are several challenges when adopting EEs for diarisation, from which we…
Sound - the oft-neglected sense for Software Engineering - is a crucial component of our daily lives, playing a vital role in how we interact with the world around us. In this paper, we challenge the traditional boundaries of Software…
This article describes a collaborative project between researchers in the Mathematics and Computer Science Division at Argonne National Laboratory and the Computer Music Project of the University of Illinois at Urbana-Champaign. The project…
This paper introduces Synthetic Enclosed Echoes (SEE), a novel dataset designed to enhance robot perception and 3D reconstruction capabilities in underwater environments. SEE comprises high-fidelity synthetic sonar data, complemented by a…
Sonification, or conveying data using non-verbal audio, is a relatively niche but growing approach for presenting data across multiple specialist domains including astronomy, climate science, and beyond. The STRAUSS Python package aims to…
Recent speech-to-speech (S2S) models generate intelligible speech but still lack natural expressiveness, largely due to the absence of a reliable evaluation metric. Existing approaches, such as subjective MOS ratings, low-level acoustic…
Image datasets serve as the foundation for machine learning models in computer vision, significantly influencing model capabilities, performance, and biases alongside architectural considerations. Therefore, understanding the composition…
Most tools for astrophysical research was centered on visual display. Even after some studies shows that the use of sound could help the data analysis, and on the other hand generate more accessibility. This fact motivates the creation of a…
Effectively steering hearable devices requires understanding the acoustic environment around the user. In the computational analysis of sound scenes, foundation models have emerged as the state of the art to produce high-performance,…
Explainable Artificial Intelligence (XAI) aims to make machine learning models transparent and trustworthy, yet most current approaches communicate explanations visually or through text. This paper introduces an information theoretic…
Auditory display is concerned with the use of non-speech sound to communicate information. If the term seems at first oxymoronic, then consider auditory display as an activity of perceptualization, that is, the process of making perceptible…
The development of AI-driven generative audio mirrors broader AI trends, often prioritizing immediate accessibility at the expense of explainability. Consequently, integrating such tools into sustained artistic practice remains a…
Dynamic languages often employ reflection primitives to turn dynamically generated text into executable code at run-time. These features make standard static analysis extremely hard if not impossible because its essential data structures,…
There has been a surge of interest in leveraging speech as a marker of health for a wide spectrum of conditions. The underlying premise is that any neurological, mental, or physical deficits that impact speech production can be objectively…