28 citations · 271 across the 94 of their papers we have counts for
60 papers · 1 filter
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…
Extending Music Annotation Schemas: Zero-Shot Prediction or Few-Shot Adaptation?
Christos Plachouras, Emmanouil Benetos, Johan Pauwels
Automatic music annotation is typically tackled under the assumption of a fixed annotation schema. In practice, commercial music catalogs often need to accommodate new musical attr…
Synthesis and editing of multi-instrument audio mixtures using scalar-quantised latents with MIDI Span conditioning
Sungkyun Chang, Keshav Bhandari, Simon Dixon +1
Music creation often involves iterative refinement, changing selected musical details while retaining the rest. To support such refinement, we introduce SpanSynth-Edit, a flow-matc…
Perceptible or Not? Diagnosing Passive Fingerprints for Speech Deepfake Attribution
Yupei Li, Qiyang Sun, Emmanouil Benetos +2
Passive fingerprints (intrinsic traces naturally left by generators) have been shown to enable attribution in speech deepfake detection, yet their persistence, reproducibility, and…
Finetuning Strategies for Querying Sounds by Vocal Imitation
Aditya Bhattacharjee, Christos Plachouras, Sungkyun Chang +1
This technical report describes our winning submission to the AES AIMLA 2025 Challenge on querying sound effects by vocal imitation. We investigate two complementary fine-tuning st…
Velocity Prediction in Automatic Guitar Transcription
Jackson Loth, Xavier Riley, Simon Dixon +1
Automatic Music Transcription (AMT) models have achieved a high level of success in polyphonic transcription of various instruments. Velocity, typically a measure of note intensity…
Quality Audio Prototyping: a prototype system for unified sound retrieval and procedural generation
Nelly Garcia, Aditya Bhattacharjee, Gabryel Mason-Williams +3
Sound design workflows frequently oscillate between time-consuming library searches and the complexity of procedural synthesis, with practitioners typically relying on disconnected…
Text2Score: Generating Sheet Music From Textual Prompts
Keshav Bhandari, Sungkyun Chang, Abhinaba Roy +4
Developing text-driven symbolic music generation models remains challenging due to the scarcity of aligned text-music datasets and the unreliability of automated captioning pipelin…
CMI-RewardBench: Evaluating Music Reward Models with Compositional Multimodal Instruction
Yinghao Ma, Haiwen Xia, Hewei Gao +9
While music generation models have evolved to handle complex multimodal inputs mixing text, lyrics, and reference audio, evaluation mechanisms have lagged behind. In this paper, we…
SCRAPL: Scattering Transform with Random Paths for Machine Learning
Christopher Mitcheltree, Vincent Lostanlen, Emmanouil Benetos +1
The Euclidean distance between wavelet scattering transform coefficients (known as paths) provides informative gradients for perceptual quality assessment of deep inverse problems…
AVMeme Exam: A Multimodal Multilingual Multicultural Benchmark for LLMs' Contextual and Cultural Knowledge and Thinking
Xilin Jiang, Qiaolin Wang, Junkai Wu +30
Internet audio-visual clips convey meaning through time-varying sound and motion, which extend beyond what text alone can represent. To examine whether AI models can understand suc…
Embryonic Exposure to VPA Influences Chick Vocalisations: A Computational Study
Antonella M. C. Torrisi, Inês Nolasco, Paola Sgadò +2
In young animals like poultry chicks (Gallus gallus), vocalisations convey information about affective and behavioural states. Traditional approaches to vocalisation analysis, rely…
Twenty-Five Years of MIR Research: Achievements, Practices, Evaluations, and Future Challenges
Geoffroy Peeters, Zafar Rafii, Magdalena Fuentes +4
In this paper, we trace the evolution of Music Information Retrieval (MIR) over the past 25 years. While MIR gathers all kinds of research related to music informatics, a large par…
SAR-LM: Symbolic Audio Reasoning with Large Language Models
Termeh Taheri, Yinghao Ma, Emmanouil Benetos
Large language models (LLMs) have advanced in text and vision, but their reasoning on audio remains limited. Most existing methods rely on dense audio embeddings, which are difficu…
Scalable Evaluation for Audio Identification via Synthetic Latent Fingerprint Generation
Aditya Bhattacharjee, Marco Pasini, Emmanouil Benetos
The evaluation of audio fingerprinting at a realistic scale is limited by the scarcity of large public music databases. We present an audio-free approach that synthesises latent fi…
RUMAA: Repeat-Aware Unified Music Audio Analysis for Score-Performance Alignment, Transcription, and Mistake Detection
Sungkyun Chang, Simon Dixon, Emmanouil Benetos
This study introduces RUMAA, a transformer-based framework for music performance analysis that unifies score-to-performance alignment, score-informed transcription, and mistake det…
Audio-JEPA: Joint-Embedding Predictive Architecture for Audio Representation Learning
Ludovic Tuncay, Etienne Labbé, Emmanouil Benetos +1
Building on the Joint-Embedding Predictive Architecture (JEPA) paradigm, a recent self-supervised learning framework that predicts latent representations of masked regions in high-…
Universal Music Representations? Evaluating Foundation Models on World Music Corpora
Charilaos Papaioannou, Emmanouil Benetos, Alexandros Potamianos
Foundation models have revolutionized music information retrieval, but questions remain about their ability to generalize across diverse musical traditions. This paper presents a c…
Refining music sample identification with a self-supervised graph neural network
Aditya Bhattacharjee, Ivan Meresman Higgs, Mark Sandler +1
Automatic sample identification (ASID), the detection and identification of portions of audio recordings that have been reused in new musical works, is an essential but challenging…
MMAR: A Challenging Benchmark for Deep Reasoning in Speech, Audio, Music, and Their Mix
Ziyang Ma, Yinghao Ma, Yanqiao Zhu +31
We introduce MMAR, a new benchmark designed to evaluate the deep reasoning capabilities of Audio-Language Models (ALMs) across massive multi-disciplinary tasks. MMAR comprises 1,00…
Learning Music Audio Representations With Limited Data
Christos Plachouras, Emmanouil Benetos, Johan Pauwels
Large deep-learning models for music, including those focused on learning general-purpose music audio representations, are often assumed to require substantial training data to ach…
Audio-FLAN: An Instruction-Following Dataset for Unified Audio Understanding and Generation of Speech, Music, and Sound
Liumeng Xue, Ziya Zhou, Jiahao Pan +20
Recent advancements in audio tokenization have significantly enhanced the integration of audio capabilities into large language models (LLMs). However, audio understanding and gene…
LHGNN: Local-Higher Order Graph Neural Networks For Audio Classification and Tagging
Shubhr Singh, Emmanouil Benetos, Huy Phan +1
Transformers have set new benchmarks in audio processing tasks, leveraging self-attention mechanisms to capture complex patterns and dependencies within audio data. However, their…
ST-ITO: Controlling Audio Effects for Style Transfer with Inference-Time Optimization
Christian J. Steinmetz, Shubhr Singh, Marco Comunità +4
Audio production style transfer is the task of processing an input to impart stylistic elements from a reference recording. Existing approaches often train a neural network to esti…