7 citations · 23 across the 11 of their papers we have counts for
12 papers
BEANS-Next and ROOTS: Broadening Audio-Language Capabilities for Bioacoustics
Christos Plachouras, David Robinson, Marius Miron +17
Bioacoustics and ethology encompass a wide range of audio understanding tasks, many of which stand to benefit from recent advances in large audio-language models. However, progress…
Woosh: A Sound Effects Foundation Model
Gaëtan Hadjeres, Marc Ferras, Khaled Koutini +7
The audio research community depends on open generative models as foundational tools for building novel approaches and establishing baselines. In this report, we present Woosh, Son…
HumMusQA: A Human-written Music Understanding QA Benchmark Dataset
Benno Weck, Pablo Puentes, Andrea Poltronieri +2
The evaluation of music understanding in Large Audio-Language Models (LALMs) requires a rigorously defined benchmark that truly tests whether models can perceive and interpret musi…
CrossMuSim: A Cross-Modal Framework for Music Similarity Retrieval with LLM-Powered Text Description Sourcing and Mining
Tristan Tsoi, Jiajun Deng, Yaolong Ju +3
Music similarity retrieval is fundamental for managing and exploring relevant content from large collections in streaming platforms. This paper presents a novel cross-modal contras…
The language of sound search: Examining User Queries in Audio Search Engines
Benno Weck, Frederic Font
This study examines textual, user-written search queries within the context of sound search engines, encompassing various applications such as foley, sound effects, and general aud…
The Role of Large Language Models in Musicology: Are We Ready to Trust the Machines?
Pedro Ramoneda, Emilia Parada-Cabaleiro, Benno Weck +1
In this work, we explore the use and reliability of Large Language Models (LLMs) in musicology. From a discussion with experts and students, we assess the current acceptance and co…
MuChoMusic: Evaluating Music Understanding in Multimodal Audio-Language Models
Benno Weck, Ilaria Manco, Emmanouil Benetos +3
Multimodal models that jointly process audio and language hold great promise in audio understanding and are increasingly being adopted in the music domain. By allowing users to que…
WikiMuTe: A web-sourced dataset of semantic descriptions for music audio
Benno Weck, Holger Kirchhoff, Peter Grosche +1
Multi-modal deep learning techniques for matching free-form text with music have shown promising results in the field of Music Information Retrieval (MIR). Prior work is often base…
The Song Describer Dataset: a Corpus of Audio Captions for Music-and-Language Evaluation
Ilaria Manco, Benno Weck, SeungHeon Doh +10
We introduce the Song Describer dataset (SDD), a new crowdsourced corpus of high-quality audio-caption pairs, designed for the evaluation of music-and-language models. The dataset…
Data leakage in cross-modal retrieval training: A case study
Benno Weck, Xavier Serra
The recent progress in text-based audio retrieval was largely propelled by the release of suitable datasets. Since the manual creation of such datasets is a laborious task, obtaini…
Dynamic Voltage Stiffness Control Technique for a Virtual Oscillator based Grid-forming Controller
Ritwik Ghosh, Narsa Reddy Tummuru, Bharat Singh Rajpuohit
Virtual oscillator control is the latest control technique for grid-forming inverters. Virtual Oscillator based Controllers (VOCs) provide all the steady-state droop functionalitie…
Evaluating Off-the-Shelf Machine Listening and Natural Language Models for Automated Audio Captioning
Benno Weck, Xavier Favory, Konstantinos Drossos +1
Automated audio captioning (AAC) is the task of automatically generating textual descriptions for general audio signals. A captioning system has to identify various information fro…