23 citations · 34 across the 31 of their papers we have counts for
13 papers · 1 filter
Few-Shot Calibration for Sim-to-Real Single-Channel Speaker Distance Estimation
Michael Neri, Archontis Politis, Tuomas Virtanen
Speaker distance estimators are trained almost exclusively on simulated room acoustics, because real recordings annotated with the true talker-to-microphone distance are scarce. We…
Overview and Meta-Analysis of DCASE 2026 Challenge Task 6: Audio Moment Retrieval from Long Audio
Hokuto Munakata, Tatsuya Komatsu, Keisuke Imoto +3
This paper presents an overview of the Detection and Classification of Acoustic Scenes and Events (DCASE) 2026 Challenge Task 6, Audio Moment Retrieval (AMR) from Long Audio. Given…
Dynamic Clustering for Cross-Segment Permutation Alignment in Long Speech Separation
Yuzhu Wang, Archontis Politis, Konstantinos Drossos +1
Long speech separation typically employs a segment-separation-stitch paradigm where recordings are divided into short segments, processed independently, and stitched together. Its…
Neural Array-Generic Direction-of-Arrival Estimation Exploiting Array Transfer Functions
Mikko Heikkinen, Archontis Politis, Konstantinos Drossos +1
Direction-of-arrival (DoA) estimation is a key component of multichannel audio processing, yet many deep learning approaches remain tied to the microphone arrays used during traini…
Speaker head orientation estimation with a single microphone array using phase spectrogram features
Balint Turi, Archontis Politis, Parthasaarathy Sudarsanam +1
Estimating a speaker's head orientation from audio can provide valuable information in smart environments, meetings, and driver monitoring. We propose a novel approach that leverag…
Few-Shot Open-Set Audio Classification Using Attention Information-Fused Prototypes
Yanxiong Li, Jiaxin Tan, Qianqian Li +3
Most existing audio classification methods suppose that each query (testing) sample belongs to a class of support (training) samples, and misrecognize samples of unseen classes as…
CNN Models for Microphone Array Covariance Matrix Upsampling and Acoustic Imaging
Marianthi Adamopoulou, Parthasaarathy Sudarsanam, David Diaz-Guerra +5
Acoustic imaging visualization is a core methodology in acoustics, enabling spatial analysis of sound sources and acoustic scenes. However, limited sensor availability in practical…
Dependence on Early and Late Reverberation of Single-Channel Speaker Distance Estimation
Michael Neri, Archontis Politis, Tuomas Virtanen
Single-channel speaker distance estimation has recently achieved centimeter-level accuracy in simulated environments, yet it remains unclear which components of the room impulse re…
Inter-Speaker Relative Cues for Two-Stage Text-Guided Target Speech Extraction
Wang Dai, Archontis Politis, Tuomas Virtanen
This paper investigates the use of relative cues for text-based target speech extraction (TSE). We first provide a theoretical justification for relative cues from the perspectives…
Moving Speaker Separation via Parallel Spectral-Spatial Processing
Yuzhu Wang, Archontis Politis, Konstantinos Drossos +1
Multi-channel speech separation in dynamic environments is challenging as time-varying spatial and spectral features evolve at different temporal scales. Existing methods typically…
Multi-Channel Replay Speech Detection using Acoustic Maps
Michael Neri, Tuomas Virtanen
Replay attacks remain a critical vulnerability for automatic speaker verification systems, particularly in real-time voice assistant applications. In this work, we propose acoustic…
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…
Discriminating real and synthetic super-resolved audio samples using embedding-based classifiers
Mikhail Silaev, Konstantinos Drossos, Tuomas Virtanen
Generative adversarial networks (GANs) and diffusion models have recently achieved state-of-the-art performance in audio super-resolution (ADSR), producing perceptually convincing…