7 papers
Evaluating Inference-time Algorithms for Semantic Sound Scene Segmentation
Sripathi Sridhar, Gordon Wichern, Yoshiki Masuyama +2
Spatial semantic segmentation of sound scenes (S5) involves the detection and extraction of target sound events in audio files. However, in typical detection-extraction pipelines,…
An Evaluation Framework for Structured Audio Captions Validated by Controlled Perturbations
Liang-Yuan Wu, Sripathi Sridhar, Mark Cartwright +1
Recent advances in automated audio captioning (AAC) are driving a shift from monolithic sentences toward structured formats that disentangle acoustic and semantic properties, such…
Audiocards: Structured Metadata Improves Audio Language Models For Sound Design
Sripathi Sridhar, Prem Seetharaman, Oriol Nieto +2
Sound designers search for sounds in large sound effects libraries using aspects such as sound class or visual context. However, the metadata needed for such search is often missin…
Compositional Audio Representation Learning
Sripathi Sridhar, Mark Cartwright
Human auditory perception is compositional in nature -- we identify auditory streams from auditory scenes with multiple sound events. However, such auditory scenes are typically re…
Multi-label Open-set Audio Classification
Sripathi Sridhar, Mark Cartwright
Current audio classification models have small class vocabularies relative to the large number of sound event classes of interest in the real world. Thus, they provide a limited vi…
Helicality: An Isomap-based Measure of Octave Equivalence in Audio Data
Sripathi Sridhar, Vincent Lostanlen
Octave equivalence serves as domain-knowledge in MIR systems, including chromagram, spiral convolutional networks, and harmonic CQT. Prior work has applied the Isomap manifold lear…
Learning the helix topology of musical pitch
Vincent Lostanlen, Sripathi Sridhar, Brian McFee +2
To explain the consonance of octaves, music psychologists represent pitch as a helix where azimuth and axial coordinate correspond to pitch class and pitch height respectively. Thi…