1 citations · 3 across the 8 of their papers we have counts for
9 papers
Domain-Incremental Learning for Generative Speech Enhancement
Manjunath Mulimani, Annamaria Mesaros, Minje Kim +1
We propose a domain-incremental learning framework for generative speech enhancement (SE) that learns from a sequence of datasets or domains recorded under diverse acoustic conditi…
Domain-Agnostic Incremental Learning for Sound Classification. A DCASE 2026 Challenge task
Riccardo Casciotti, Manjunath Mulimani, Manu Harju +2
This paper presents the Domain-Agnostic Incremental Learning for Audio Classification Task of the DCASE 2026 Challenge. Incremental learning refers to sequentially learning new tas…
Online incremental learning for audio classification using a pretrained audio model
Manjunath Mulimani, Annamaria Mesaros
Incremental learning aims to learn new tasks sequentially without forgetting the previously learned ones. Most of the existing incremental learning methods for audio focus on train…
Domain-Incremental Learning for Audio Classification
Manjunath Mulimani, Annamaria Mesaros
In this work, we propose a method for domain-incremental learning for audio classification from a sequence of datasets recorded in different acoustic conditions. Fine-tuning a mode…
Class-Incremental Learning for Sound Event Localization and Detection
Ruchi Pandey, Manjunath Mulimani, Archontis Politis +1
This paper investigates the feasibility of class-incremental learning (CIL) for Sound Event Localization and Detection (SELD) tasks. The method features an incremental learner that…
Online Domain-Incremental Learning Approach to Classify Acoustic Scenes in All Locations
Manjunath Mulimani, Annamaria Mesaros
In this paper, we propose a method for online domain-incremental learning of acoustic scene classification from a sequence of different locations. Simply training a deep learning m…
Class-Incremental Learning for Multi-Label Audio Classification
Manjunath Mulimani, Annamaria Mesaros
In this paper, we propose a method for class-incremental learning of potentially overlapping sounds for solving a sequence of multi-label audio classification tasks. We design an i…
Incremental Learning of Acoustic Scenes and Sound Events
Manjunath Mulimani, Annamaria Mesaros
In this paper, we propose a method for incremental learning of two distinct tasks over time: acoustic scene classification (ASC) and audio tagging (AT). We use a simple convolution…
Evaluating robustness of You Only Hear Once(YOHO) Algorithm on noisy audios in the VOICe Dataset
Soham Tiwari, Kshitiz Lakhotia, Manjunath Mulimani
Sound event detection (SED) in machine listening entails identifying the different sounds in an audio file and identifying the start and end time of a particular sound event in the…