Cheng et al., 2023 - Google Patents
Semi-blind source separation using convolutive transfer function for nonlinear acoustic echo cancellationCheng et al., 2023
View PDF- Document ID
- 4085594263162961183
- Author
- Cheng G
- Liao L
- Chen K
- Hu Y
- Zhu C
- Lu J
- Publication year
- Publication venue
- The Journal of the Acoustical Society of America
External Links
Snippet
The recently proposed semi-blind source separation (SBSS) method for nonlinear acoustic echo cancellation (NAEC) outperforms adaptive NAEC in attenuating the nonlinear acoustic echo. However, the multiplicative transfer function (MTF) approximation makes it unsuitableĀ ā¦
- 238000002592 echocardiography 0 title abstract description 26
Classifications
-
- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
- G10L21/00—Processing of the speech or voice signal to produce another audible or non-audible signal, e.g. visual or tactile, in order to modify its quality or its intelligibility
- G10L21/02—Speech enhancement, e.g. noise reduction or echo cancellation
- G10L21/0208—Noise filtering
- G10L21/0216—Noise filtering characterised by the method used for estimating noise
- G10L2021/02161—Number of inputs available containing the signal or the noise to be suppressed
-
- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
- G10L21/00—Processing of the speech or voice signal to produce another audible or non-audible signal, e.g. visual or tactile, in order to modify its quality or its intelligibility
- G10L21/02—Speech enhancement, e.g. noise reduction or echo cancellation
- G10L21/0272—Voice signal separating
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04R—LOUDSPEAKERS, MICROPHONES, GRAMOPHONE PICK-UPS OR LIKE ACOUSTIC ELECTROMECHANICAL TRANSDUCERS; DEAF-AID SETS; PUBLIC ADDRESS SYSTEMS
- H04R3/00—Circuits for transducers, loudspeakers or microphones
- H04R3/005—Circuits for transducers, loudspeakers or microphones for combining the signals of two or more microphones
-
- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
- G10L15/00—Speech recognition
- G10L15/08—Speech classification or search
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04M—TELEPHONIC COMMUNICATION
- H04M3/00—Automatic or semi-automatic exchanges
- H04M3/42—Systems providing special services or facilities to subscribers
-
- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
- G10L19/00—Speech or audio signal analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signal, using source filter models or psychoacoustic analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/14—Fourier, Walsh or analogous domain transformations, e.g. Laplace, Hilbert, Karhunen-Loeve, transforms
- G06F17/147—Discrete orthonormal transforms, e.g. discrete cosine transform, discrete sine transform, and variations therefrom, e.g. modified discrete cosine transform, integer transforms approximating the discrete cosine transform
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Zhang et al. | Deep learning for environmentally robust speech recognition: An overview of recent developments | |
Naylor et al. | Speech dereverberation | |
Erdogan et al. | Deep recurrent networks for separation and recognition of single-channel speech in nonstationary background audio | |
US9881630B2 (en) | Acoustic keystroke transient canceler for speech communication terminals using a semi-blind adaptive filter model | |
Cheng et al. | Semi-blind source separation using convolutive transfer function for nonlinear acoustic echo cancellation | |
Huang et al. | Kronecker product multichannel linear filtering for adaptive weighted prediction error-based speech dereverberation | |
US20110194709A1 (en) | Automatic source separation via joint use of segmental information and spatial diversity | |
US11404055B2 (en) | Simultaneous dereverberation and denoising via low latency deep learning | |
Shankar et al. | Efficient two-microphone speech enhancement using basic recurrent neural network cell for hearing and hearing aids | |
Oo et al. | Phase and reverberation aware DNN for distant-talking speech enhancement | |
Cheng et al. | Deep learning-based stereophonic acoustic echo suppression without decorrelation | |
Lee et al. | Improved mask-based neural beamforming for multichannel speech enhancement by snapshot matching masking | |
Gao et al. | An order-aware scheme for robust direction of arrival estimation in the spherical harmonic domain | |
Lee et al. | DeFTAN-II: Efficient Multichannel Speech Enhancement with Subgroup Processing | |
Kuang et al. | Three-stage hybrid neural beamformer for multi-channel speech enhancement | |
Cobos et al. | Two-microphone separation of speech mixtures based on interclass variance maximization | |
Wang et al. | On Semi-blind Source Separation-based Approaches to Nonlinear Echo Cancellation Based on Bilinear Alternating Optimization | |
Xiang et al. | Multi-channel adaptive dereverberation robust to abrupt change of target speaker position | |
Wang et al. | Low-latency real-time independent vector analysis using convolutive transfer function | |
Inoue et al. | Sepnet: a deep separation matrix prediction network for multichannel audio source separation | |
Emura et al. | Multi-delay sparse approach to residual crosstalk reduction for blind source separation | |
Hsu et al. | Array configuration-agnostic personalized speech enhancement using long-short-term spatial coherence | |
Sarmiento et al. | Initialization method for speech separation algorithms that work in the time-frequency domain | |
JP7270869B2 (en) | Information processing device, output method, and output program | |
Wang et al. | Robust direction-of-arrival estimation for a target speaker based on multi-task U-net based direct-path dominance test |