Results 21 to 30 of about 1,864,117 (195)
Speaker Verification Based on Single Channel Speech Separation
IEEE Access, 2023 In multi-speaker scenarios, speech processing tasks like speaker identification and speech recognition are susceptible to noise and overlapped voices.
Rong Jin, Mijit Ablimit, Askar Hamdulla
doaj +1 more source
Analysis and classification of phonation types in speech and singing voice [PDF]
, 2022 Both in speech and singing, humans are capable of generating sounds of different phonation types (e.g., breathy, modal and pressed). Previous studies in the analysis and classification of phonation types have mainly used voice source features derived ...
Kadiri, Sudarsana Reddy +2 more
core +1 more source
Graph Convolution-Based Deep Clustering for Speech Separation
IEEE Access, 2020 Deep clustering is a promising technique for speech separation that is crucial to speech communication, acoustic target detection, acoustic enhancement and speech recognition. In the study of monophonic speech separation, the problem is that the decrease
Shan Qin +4 more
doaj +1 more source
Speech separation for speech recognition [PDF]
Le Journal de Physique IV, 1994 Divers modeles de separation de voix parasites sont implementes a l'entree d'un systeme de reconnaissance de la parole. L'objectif est d'estimer, au travers des taux de reconnaissance, l'efficacite des principes de traitement. Un premier modele utilise l'annulation harmonique des voix parasites dans le domaine temporel.
de Cheveigné, A. +3 more
openaire +1 more source
GA_FastICA Algorithmfor Speech Separation
Journal of Harbin University of Science and Technology, 2022 With the development of speech processing technology, new speech separation algorithms are constantly proposed. The GA_FastICA algorithm is proposed by combining the Geometric Approach (GA) algorithm and Fast Independent Component Analysis (FastICA ...
LAN Chao-feng +4 more
doaj +1 more source
Leveraging Sparse Approximation for Monaural Overlapped Speech Separation From Auditory Perspective
IEEE Access, 2023 Neuroscience suggests that the sparse behavior of a neural population underlies the mechanisms of the auditory system for monaural overlapped speech separation.
Hiroshi Sekiguchi +2 more
doaj +1 more source
Deep NMF for speech separation [PDF]
2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2015 Non-negative matrix factorization (NMF) has been widely used for challenging single-channel audio source separation tasks. However, inference in NMF-based models relies on iterative inference methods, typically formulated as multiplicative updates. We propose “deep NMF”, a novel non-negative deep network architecture which results from unfolding the ...
Jonathan Le Roux +2 more
openaire +2 more sources
Heterogeneous Target Speech Separation
Interspeech 2022, 2022 Submitted to Interspeech ...
Efthymios Tzinis +4 more
openaire +4 more sources
Research on monaural speech segregation based on feature selection
EURASIP Journal on Audio, Speech, and Music Processing, 2023 Speech feature model is the basis of speech and noise separation, speech expression, and different styles of speech conversion. With the development of signal processing methods, the feature types and dimensions increase.
Xiaoping Xie +3 more
doaj +1 more source
, 2021 S.2393-2397This paper describes a hands-on comparison on using state-of-the-art music source separation deep neural networks (DNNs) before and after task-specific fine-tuning for separating speech content from non-speech content in broadcast audio (i.e.,
Martin Strauss +7 more
core +1 more source