activity
20162026
most citedSpeaker Distance Estimation in Enclosures from Single-Channel Audio

23 citations · 38 across the 13 of their papers we have counts for

collaborators

13 papers

eess.AS2026

Beyond Omnidirectional: Neural Ambisonics Encoding for Arbitrary Microphone Directivity Patterns using Cross-Attention

Mikko Heikkinen, Archontis Politis, Konstantinos Drossos +1

We present a deep neural network approach for encoding microphone array signals into Ambisonics that generalizes to arbitrary microphone array configurations with fixed microphone…

eess.AS2025

Inter-Speaker Relative Cues for Text-Guided Target Speech Extraction

Wang Dai, Archontis Politis, Tuomas Virtanen

We propose a novel approach that utilizes inter-speaker relative cues to distinguish target speakers and extract their voices from mixtures. Continuous cues (e.g., temporal order,…

eess.AS2025

Attractor-Based Speech Separation of Multiple Utterances by Unknown Number of Speakers

Yuzhu Wang, Archontis Politis, Konstantinos Drossos +1

This paper addresses the problem of single-channel speech separation, where the number of speakers is unknown, and each speaker may speak multiple utterances. We propose a speech s…

eess.AS2024

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…

eess.AS2024

Gaunt coefficients for complex and real spherical harmonics with applications to spherical array processing and Ambisonics

Archontis Politis

Acoustical signal processing of directional representations of sound fields, including source, receiver, and scatterer transfer functions, are often expressed and modeled in the sp…

eess.AS2024

Reference Channel Selection by Multi-Channel Masking for End-to-End Multi-Channel Speech Enhancement

Wang Dai, Xiaofei Li, Archontis Politis +1

In end-to-end multi-channel speech enhancement, the traditional approach of designating one microphone signal as the reference for processing may not always yield optimal results.…