20 citations · 36 across the 15 of their papers we have counts for
20 papers
COSED: Setting the Bar for Open-Vocabulary Sound Event Detection
Florian Schmid, Sanjeel Parekh, Chi Ian Tang +5
Open-vocabulary Sound Event Detection detects and temporally localizes acoustic events described by arbitrary text queries. Progress in this emerging field is hard to assess: recen…
SPHERE: Automatic Music Upmixing via Audio Language Model Post-Training with Spatial Heuristic Rewards
Zixun Guo, Calvin Murdock, Sanjeel Parekh +4
In this paper, we study the task of automatic music upmixing, wherein a system predicts spatial mixing parameters from a multi-stem recording. Different from existing methods that…
Ambisonics Encoding of Room Impulse Responses using a Device-Agnostic Diffusion Model
Eloi Moliner, Christoph Hold, Juan Azcarreta Ortiz +5
We address the problem of encoding room impulse responses (RIRs) into high-order Ambisonics (HOA) representations from arbitrary and potentially insufficient or incomplete micropho…
Unlocking Spatial Grounding in Large Audio-Visual Retrieval models
Hugo Malard, Michel Olvera, Sanjeel Parekh +3
Weak supervision sets a practical regime for audio-visual sound source localization as dense spatial annotations are costly to obtain at scale. The task, however, remains challengi…
Spatial-Magnifier: Spatial upsampling for multichannel speech enhancement
Dongheon Lee, Ashutosh Pandey, Sanjeel Parekh +4
While the spatial directivity of multichannel speech enhancement algorithms improves with the number of microphones, fitting large capture arrays into real-world edge devices is ty…
Unified Diffusion Refinement for Multi-Channel Speech Enhancement and Separation
Zhongweiyang Xu, Ashutosh Pandey, Juan Azcarreta +4
We propose Uni-ArrayDPS, a novel diffusion-based refinement framework for unified multi-channel speech enhancement and separation. Existing methods for multi-channel speech enhance…
ArrayDPS-Refine: Generative Refinement of Discriminative Multi-Channel Speech Enhancement
Zhongweiyang Xu, Ashutosh Pandey, Juan Azcarreta +3
Multi-channel speech enhancement aims to recover clean speech from noisy multi-channel recordings. Most deep learning methods employ discriminative training, which can lead to non-…
Text-to-Stage: Spatial Layouts from Long-form Narratives
Jefferson Hernandez, Swarnadeep Saha, Chenxi Whitehouse +6
In this work, we probe the ability of a language model to demonstrate spatial reasoning from unstructured text, mimicking human capabilities and automating a process that benefits…
Conditional Flow Matching for Visually-Guided Acoustic Highlighting
Hugo Malard, Gael Le Lan, Daniel Wong +3
Visually-guided acoustic highlighting seeks to rebalance audio in alignment with the accompanying video, creating a coherent audio-visual experience. While visual saliency and enha…
Sound Event Detection with Boundary-Aware Optimization and Inference
Florian Schmid, Chi Ian Tang, Sanjeel Parekh +9
Temporal detection problems appear in many fields including time-series estimation, activity recognition and sound event detection (SED). In this work, we propose a new approach to…
More Than A Shortcut: A Hyperbolic Approach To Early-Exit Networks
Swapnil Bhosale, Cosmin Frateanu, Camilla Clark +7
Deploying accurate event detection on resource-constrained devices is challenged by the trade-off between performance and computational cost. While Early-Exit (EE) networks offer a…
Learning to Highlight Audio by Watching Movies
Chao Huang, Ruohan Gao, J. M. F. Tsang +5
Recent years have seen a significant increase in video content creation and consumption. Crafting engaging content requires the careful curation of both visual and audio elements.…
Efficient Audiovisual Speech Processing via MUTUD: Multimodal Training and Unimodal Deployment
Joanna Hong, Sanjeel Parekh, Honglie Chen +4
Building reliable speech systems often requires combining multiple modalities, like audio and visual cues. While such multimodal solutions frequently lead to improvements in perfor…
Tackling Interpretability in Audio Classification Networks with Non-negative Matrix Factorization
Jayneel Parekh, Sanjeel Parekh, Pavlo Mozharovskyi +2
This paper tackles two major problem settings for interpretability of audio processing networks, post-hoc and by-design interpretation. For post-hoc interpretation, we aim to inter…
Listen to Interpret: Post-hoc Interpretability for Audio Networks with NMF
Jayneel Parekh, Sanjeel Parekh, Pavlo Mozharovskyi +2
This paper tackles post-hoc interpretability for audio processing networks. Our goal is to interpret decisions of a network in terms of high-level audio objects that are also liste…
Emotion Transfer Using Vector-Valued Infinite Task Learning
Alex Lambert, Sanjeel Parekh, Zoltán Szabó +1
Style transfer is a significant problem of machine learning with numerous successful applications. In this work, we present a novel style transfer framework building upon infinite…
Identify, locate and separate: Audio-visual object extraction in large video collections using weak supervision
Sanjeel Parekh, Alexey Ozerov, Slim Essid +3
We tackle the problem of audiovisual scene analysis for weakly-labeled data. To this end, we build upon our previous audiovisual representation learning framework to perform object…
Weakly Supervised Representation Learning for Unsynchronized Audio-Visual Events
Sanjeel Parekh, Slim Essid, Alexey Ozerov +3
Audio-visual representation learning is an important task from the perspective of designing machines with the ability to understand complex events. To this end, we propose a novel…
Content-based Video Indexing and Retrieval Using Corr-LDA
Rahul Radhakrishnan Iyer, Sanjeel Parekh, Vikas Mohandoss +3
Existing video indexing and retrieval methods on popular web-based multimedia sharing websites are based on user-provided sparse tagging. This paper proposes a very specific way of…
Nyquist Filter Design using POCS Methods: Including Constraints in Design
Sanjeel Parekh, Pratik Shah
The problem of constrained finite impulse response (FIR) filter design is central to signal processing and arises in a variety of disciplines. This paper surveys the design of such…