23 citations · 34 across the 31 of their papers we have counts for
33 papers
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…
The Spheres Dataset: Multitrack Orchestral Recordings for Music Source Separation and Information Retrieval
Jaime Garcia-Martinez, David Diaz-Guerra, John Anderson +5
This paper introduces The Spheres dataset, multitrack orchestral recordings designed to advance machine learning research in music source separation and related MIR tasks within th…
Acoustic Simulation Framework for Multi-channel Replay Speech Detection
Michael Neri, Tuomas Virtanen
Replay speech attacks pose a significant threat to voice-controlled systems, especially in smart environments where voice assistants are widely deployed. While multi-channel audio…
Stereo Sound Event Localization and Detection with Onscreen/offscreen Classification
Kazuki Shimada, Archontis Politis, Iran R. Roman +10
This paper presents the objective, dataset, baseline, and metrics of Task 3 of the DCASE2025 Challenge on sound event localization and detection (SELD). In previous editions, the c…
Multi-Utterance Speech Separation and Association Trained on Short Segments
Yuzhu Wang, Archontis Politis, Konstantinos Drossos +1
Current deep neural network (DNN) based speech separation faces a fundamental challenge -- while the models need to be trained on short segments due to computational constraints, r…
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,…
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…
Representation Learning for Semantic Alignment of Language, Audio, and Visual Modalities
Parthasaarathy Sudarsanam, Irene Martín-Morató, Tuomas Virtanen
This paper proposes a single-stage training approach that semantically aligns three modalities - audio, visual, and text using a contrastive learning framework. Contrastive trainin…
Knowledge Distillation for Speech Denoising by Latent Representation Alignment with Cosine Distance
Diep Luong, Mikko Heikkinen, Konstantinos Drossos +1
Speech denoising is a generally adopted and impactful task, appearing in many common and everyday-life use cases. Although there are very powerful methods published, most of those…
Impact of Microphone Array Mismatches to Learning-based Replay Speech Detection
Michael Neri, Tuomas Virtanen
In this work, we investigate the generalization of a multi-channel learning-based replay speech detector, which employs adaptive beamforming and detection, across different microph…
Score-informed Music Source Separation: Improving Synthetic-to-real Generalization in Classical Music
Eetu Tunturi, David Diaz-Guerra, Archontis Politis +1
Music source separation is the task of separating a mixture of instruments into constituent tracks. Music source separation models are typically trained using only audio data, alth…
Multi-channel Replay Speech Detection using an Adaptive Learnable Beamformer
Michael Neri, Tuomas Virtanen
Replay attacks belong to the class of severe threats against voice-controlled systems, exploiting the easy accessibility of speech signals by recorded and replayed speech to grant…