23 citations · 34 across the 31 of their papers we have counts for
13 papers · 1 filter
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…
Automatic Live Music Song Identification Using Multi-level Deep Sequence Similarity Learning
Aapo Hakala, Trevor Kincy, Tuomas Virtanen
This paper studies the novel problem of automatic live music song identification, where the goal is, given a live recording of a song, to retrieve the corresponding studio version…
Gen-A: Generalizing Ambisonics Neural Encoding to Unseen Microphone Arrays
Mikko Heikkinen, Archontis Politis, Konstantinos Drossos +1
Using deep neural networks (DNNs) for encoding of microphone array (MA) signals to the Ambisonics spatial audio format can surpass certain limitations of established conventional m…