Papers blind source separation
“blind source separation” 태그가 달린 논문 211편 · 필터 해제
Towards Reliable Objective Evaluation Metrics for Generative Singing Voice Separation Models
Traditional Blind Source Separation Evaluation (BSS-Eval) metrics were originally designed to evaluate linear audio source separation models based on methods such as time-frequency masking. However, recent generative mod…
Audio Source Separationblind source separationBlind Source Separation in Biomedical Signals Using Variational Methods
This study introduces a novel unsupervised approach for separating overlapping heart and lung sounds using variational autoencoders (VAEs). In clinical settings, these sounds often interfere with each other, making manua…
blind source separationDecoderDiagnosticSpatial Speech Translation: Translating Across Space With Binaural Hearables
Imagine being in a crowded space where people speak a different language and having hearables that transform the auditory space into your native language, while preserving the spatial cues for all speakers. We introduce …
blind source separationTranslationHyperKING: Quantum-Classical Generative Adversarial Networks for Hyperspectral Image Restoration
Quantum machine intelligence starts showing its impact on satellite remote sensing (SRS). Also, recent literature exhibits that quantum generative intelligences encompass superior potential than their classical counterpa…
blind source separationImage RestorationSelf-Supervised Autoencoder Network for Robust Heart Rate Extraction from Noisy Photoplethysmogram: Applying Blind Source Separation to Biosignal Analysis
Biosignals can be viewed as mixtures measuring particular physiological events, and blind source separation (BSS) aims to extract underlying source signals from mixtures. This paper proposes a self-supervised multi-encod…
blind source separationJoint Spectrogram Separation and TDOA Estimation using Optimal Transport
Separating sources is a common challenge in applications such as speech enhancement and telecommunications, where distinguishing between overlapping sounds helps reduce interference and improve signal quality. Additional…
blind source separationSpeech EnhancementA Lightweight Deep Exclusion Unfolding Network for Single Image Reflection Removal
Single Image Reflection Removal (SIRR) is a canonical blind source separation problem and refers to the issue of separating a reflection-contaminated image into a transmission and a reflection image. The core challenge l…
blind source separationReflection RemovalRevisiting convolutive blind source separation for identifying spiking motor neuron activity: From theory to practice
Objective: Identifying the activity of motor neurons (MNs) non-invasively is possible by decomposing signals from muscles, e.g., surface electromyography (EMG) or ultrasound. The theoretical background of MN identificati…
blind source separationElectromyography (EMG)Low-Rank Matrix Factorizations with Volume-based Constraints and Regularizations
Low-rank matrix factorizations are a class of linear models widely used in various fields such as machine learning, signal processing, and data analysis. These models approximate a matrix as the product of two smaller ma…
blind source separationImputationEnhancing Blind Source Separation with Dissociative Principal Component Analysis
Sparse principal component analysis (sPCA) enhances the interpretability of principal components (PCs) by imposing sparsity constraints on loading vectors (LVs). However, when used as a precursor to independent component…
blind source separationImage InpaintingImage ReconstructionHigh-Throughput Blind Co-Channel Interference Cancellation for Edge Devices Using Depthwise Separable Convolutions, Quantization, and Pruning
Co-channel interference cancellation (CCI) is the process used to reduce interference from other signals using the same frequency channel, thereby enhancing the performance of wireless communication systems. An improveme…
blind source separationComputational EfficiencyQuantizationDistributed Blind Source Separation based on FastICA
With the emergence of wireless sensor networks (WSNs), many traditional signal processing tasks are required to be computed in a distributed fashion, without transmissions of the raw data to a centralized processing unit…
blind source separationMotionLeaf: Fine-grained Multi-Leaf Damped Vibration Monitoring for Plant Water Stress using Low-Cost mmWave Sensors
In this paper, we introduce MotionLeaf , a novel mmWave base multi-point vibration frequency measurement system that can estimate plant stress by analyzing the surface vibrations of multiple leaves. MotionLeaf features a…
blind source separationUnsupervised Composable Representations for Audio
Current generative models are able to generate high-quality artefacts but have been shown to struggle with compositional reasoning, which can be defined as the ability to generate complex structures from simpler elements…
Audio Source Separationblind source separationInductive BiasRepresentation LearningPRIME: Blind Multispectral Unmixing Using Virtual Quantum Prism and Convex Geometry
Multispectral unmixing (MU) is critical due to the inevitable mixed pixel phenomenon caused by the limited spatial resolution of typical multispectral images in remote sensing. However, MU mathematically corresponds to t…
blind source separation$S^3$ -- Semantic Signal Separation
Topic models are useful tools for discovering latent semantic structures in large textual corpora. Recent efforts have been oriented at incorporating contextual representations in topic modeling and have been shown to ou…
blind source separationTopic ModelsNeural Blind Source Separation and Diarization for Distant Speech Recognition
This paper presents a neural method for distant speech recognition (DSR) that jointly separates and diarizes speech mixtures without supervision by isolated signals. A standard separation method for multi-talker DSR is a…
blind source separationDistant Speech Recognitionspeaker-diarizationSpeaker Diarization+2Nonparametric Evaluation of Noisy ICA Solutions
Independent Component Analysis (ICA) was introduced in the 1980's as a model for Blind Source Separation (BSS), which refers to the process of recovering the sources underlying a mixture of signals, with little knowledge…
blind source separationDiagnosticOnline Similarity-and-Independence-Aware Beamformer for Low-latency Target Sound Extraction
This study introduces an online target sound extraction (TSE) process using the similarity-and-independence-aware beamformer (SIBF) derived from an iterative batch algorithm. The study aimed to reduce latency while maint…
blind source separationTarget Sound ExtractionA computationally efficient semi-blind source separation based approach for nonlinear echo cancellation based on an element-wise iterative source steering
While the semi-blind source separation-based acoustic echo cancellation (SBSS-AEC) has received much research attention due to its promising performance during double-talk compared to the traditional adaptive algorithms,…
Acoustic echo cancellationblind source separation