Papers Speech Separation
“Speech Separation” 태그가 달린 논문 384편 · 필터 해제
DuplexChat: Constructing Speaker-Separated Full-Duplex Dialogue Speech at Scale for Spoken Dialogue Language Modeling
Full-duplex spoken dialogue models are trained on conversational speech in which each speaker is represented as a separate stream, but existing large-scale public speech corpora are mostly monaural, making them unsuited …
Speech SeparationTF-MoE: Time-Frequency Mixture-of-Experts for Efficient Speech Separation
Recent advances in speech separation (SS) have led to compact front-end models with small parameter sizes, yet their high computational cost remains a major barrier for deployment on edge devices. To address this, we pro…
Speech SeparationMeCo: One-Step MeanFlow-based Corrector for Multi-Channel Speech Separation
While discriminative models for multi-channel speech separation excel in reference-based metrics, they often exhibit suboptimal human listening quality. To address this, we propose a novel MeanFlow-based one-step generat…
Speech SeparationPredictive-Generative Drift Decomposition for Speech Enhancement and Separation
We propose a plug-and-play framework for speech enhancement and separation that augments predictive methods with a generative speech prior. Our approach, termed Stochastic Interpolant Prior for Speech (SIPS), builds on s…
Speech EnhancementSpeech SeparationA Brain-Inspired Deep Separation Network for Single Channel Raman Spectra Unmixing
Raman spectra obtained in real world applications are often a noisy combination of several spectra of various substances in a tested sample. Unmixing such spectra into individual components corresponding to each of the s…
Speech SeparationSSNAPS: Audio-Visual Separation of Speech and Background Noise with Diffusion Inverse Sampling
This paper addresses the challenge of audio-visual single-microphone speech separation and enhancement in the presence of real-world environmental noise. Our approach is based on generative inverse sampling, where we mod…
Speech SeparationSLM-SS: Speech Language Model for Generative Speech Separation
Speech separation (SS) has advanced significantly with neural network-based methods, showing improved performance on signal-level metrics. However, these methods often struggle to maintain speech intelligibility in the s…
Speech RecognitionSpeech SeparationSpatialEmb: Extract and Encode Spatial Information for 1-Stage Multi-channel Multi-speaker ASR on Arbitrary Microphone Arrays
Spatial information is a critical clue for multi-channel multi-speaker target speech recognition. Most state-of-the-art multi-channel Automatic Speech Recognition (ASR) systems extract spatial features only during the sp…
Speech RecognitionSpeech SeparationLightweight Wasserstein Audio-Visual Model for Unified Speech Enhancement and Separation
Speech Enhancement (SE) and Speech Separation (SS) have traditionally been treated as distinct tasks in speech processing. However, real-world audio often involves both background noise and overlapping speakers, motivati…
Speech EnhancementSpeech ExtractionSpeech SeparationSpeech Separation for Hearing-Impaired Children in the Classroom
Classroom environments are particularly challenging for children with hearing impairments, where background noise, multiple talkers, and reverberation degrade speech perception. These difficulties are greater for childre…
Transfer LearningSpeech SeparationUniSE: A Unified Framework for Decoder-Only Autoregressive LM-Based Speech Enhancement
Neural audio codecs have largely promoted the application of language models (LMs) for speech applications. However, the effectiveness of autoregressive LM-based models in unifying speech enhancement (SE) tasks remains u…
Reinforcement LearningSpeech EnhancementSpeech SeparationLSZone: A Lightweight Spatial Information Modeling Architecture for Real-time In-car Multi-zone Speech Separation
In-car multi-zone speech separation, which captures voices from different speech zones, plays a crucial role in human-vehicle interaction. Although previous SpatialNet has achieved notable results, its high computational…
Information ExtractionSpeech SeparationEfficient Audio-Visual Speech Separation with Discrete Lip Semantics and Multi-Scale Global-Local Attention
Audio-visual speech separation (AVSS) methods leverage visual cues to extract target speech and have demonstrated strong separation quality in noisy acoustic environments. However, these methods usually involve a large n…
Speech SeparationTISDiSS: A Training-Time and Inference-Time Scalable Framework for Discriminative Source Separation
Source separation is a fundamental task in speech, music, and audio processing, and it also provides cleaner and larger data for training generative models. However, improving separation performance in practice often dep…
Speech SeparationDiffusion-Based Unsupervised Audio-Visual Speech Separation in Noisy Environments with Noise Prior
In this paper, we address the problem of single-microphone speech separation in the presence of ambient noise. We propose a generative unsupervised technique that directly models both clean speech and structured noise co…
Speech SeparationError Analysis in a Modular Meeting Transcription System
Meeting transcription is a field of high relevance and remarkable progress in recent years. Still, challenges remain that limit its performance. In this work, we extend a previously proposed framework for analyzing leaka…
Activity DetectionSpeech SeparationCabinSep: IR-Augmented Mask-Based MVDR for Real-Time In-Car Speech Separation with Distributed Heterogeneous Arrays
Separating overlapping speech from multiple speakers is crucial for effective human-vehicle interaction. This paper proposes CabinSep, a lightweight neural mask-based minimum variance distortionless response (MVDR) speec…
Speech RecognitionSpeech SeparationData AugmentationUnifying Diarization, Separation, and ASR with Multi-Speaker Encoder
This paper presents a unified multi-speaker encoder (UME), a novel architecture that jointly learns representations for speaker diarization (SD), speech separation (SS), and multi-speaker automatic speech recognition (AS…
Speaker DiarizationSpeech RecognitionSpeech SeparationA Study of the Scale Invariant Signal to Distortion Ratio in Speech Separation with Noisy References
This paper examines the implications of using the Scale-Invariant Signal-to-Distortion Ratio (SI-SDR) as both evaluation and training objective in supervised speech separation, when the training references contain noise,…
Speech SeparationOptimizing Neural Architectures for Hindi Speech Separation and Enhancement in Noisy Environments
This paper addresses the challenges of Hindi speech separation and enhancement using advanced neural network architectures, with a focus on edge devices. We propose a refined approach leveraging the DEMUCS model to overc…
Speech Separation