2026
Speaker Anonymization for Children
AAAI 2026technical
Speaker anonymization aims to modify the speech signal in order to protect the identity of a speaker while preserving the linguistic content. Despite the increasing use of children
5 accepted papers
Speaker anonymization aims to modify the speech signal in order to protect the identity of a speaker while preserving the linguistic content. Despite the increasing use of children
Existing neural network-based speech dereverberation approaches use a fixed-length early reflection part of the reverberant signal as the target for estimation, irrespective of the severity of reverberation. Such an approach often leads to distortions in the enhanced signals in highly reverberant sc…
We propose a Beamformer-guided Target Speaker Extraction (BG-TSE) method to extract a target speaker’s voice from a multi-channel recording informed by the direction of arrival of the target. The proposed method employs a front-end beamformer steered towards the target speaker to pro-vide an auxilia…
We consider the task of region-based source separation of reverberant multi-microphone recordings. We assume pre-defined spatial regions with a single active source per region. The objective is to estimate the signals from the individual spatial regions as captured by a reference microphone while re…
The Second Diagnosis of COVID-19 using Acoustics (DiCOVA) Challenge aimed at accelerating the research in acoustics based detection of COVID-19, a topic at the intersection of acoustics, signal processing, machine learning, and healthcare. This paper presents the details of the challenge, which was…