Autoregressive Guidance of Deep Spatially Selective Filters using Bayesian Tracking for Efficient Extraction of Moving Speakers | Paper Citation Record

Observation ee69361e-afe4-40db-84b2-7ea689b47d5d · outbound

This paper cites Some experiments on the recognition of speech, with one and two ears,.

Autoregressive Guidance of Deep Spatially Selective Filters using Bayesian Tracking for Efficient Extraction of Moving Speakers Some experiments on the recognition of speech, with one and two ears,

Reference 1

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Observation 5e05d736-96d3-459b-b225-888eb763e09a · outbound

This paper cites Neural target speech extraction: An overview,.

Autoregressive Guidance of Deep Spatially Selective Filters using Bayesian Tracking for Efficient Extraction of Moving Speakers Neural target speech extraction: An overview,

Reference 2

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Observation 78731d87-57e1-4c11-9e26-8a22e0758512 · outbound

This paper cites Multi-channel speech separation using spatially selective deep non-linear filters,.

Autoregressive Guidance of Deep Spatially Selective Filters using Bayesian Tracking for Efficient Extraction of Moving Speakers Multi-channel speech separation using spatially selective deep non-linear filters,

Reference 3

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Observation fedab810-e774-4770-bc5a-d81ba15107a8 · outbound

This paper cites Spatially selective speaker separation using a DNN with a location dependent feature extraction,.

Autoregressive Guidance of Deep Spatially Selective Filters using Bayesian Tracking for Efficient Extraction of Moving Speakers Spatially selective speaker separation using a DNN with a location dependent feature extraction,

Reference 4

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This paper cites Insights into deep non-linear filters for im- proved multi-channel speech enhancement,.

Autoregressive Guidance of Deep Spatially Selective Filters using Bayesian Tracking for Efficient Extraction of Moving Speakers Insights into deep non-linear filters for im- proved multi-channel speech enhancement,

Reference 5

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This paper cites End-to-end DOA-guided speech extraction in noisy multi-talker scenarios,.

Autoregressive Guidance of Deep Spatially Selective Filters using Bayesian Tracking for Efficient Extraction of Moving Speakers End-to-end DOA-guided speech extraction in noisy multi-talker scenarios,

Reference 6

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Observation 45c87fd2-5a4f-47ae-a46e-e98d8031c838 · outbound

This paper cites All neural low- latency directional speech extraction,.

Autoregressive Guidance of Deep Spatially Selective Filters using Bayesian Tracking for Efficient Extraction of Moving Speakers All neural low- latency directional speech extraction,

Reference 7

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This paper cites ReZero: Region-customizable sound extraction,.

Autoregressive Guidance of Deep Spatially Selective Filters using Bayesian Tracking for Efficient Extraction of Moving Speakers ReZero: Region-customizable sound extraction,

Reference 8

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Observation dda3c1fc-9a22-427d-aad2-95d883660893 · outbound

This paper cites Multichannel-to-multichannel target sound extraction using direction and timestamp clues,.

Autoregressive Guidance of Deep Spatially Selective Filters using Bayesian Tracking for Efficient Extraction of Moving Speakers Multichannel-to-multichannel target sound extraction using direction and timestamp clues,

Reference 9

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Observation 33dc0c9f-3cf9-4c6c-b6d6-85757e3c0d5d · outbound

This paper cites Location-aware target speaker extraction for hearing aids,.

Autoregressive Guidance of Deep Spatially Selective Filters using Bayesian Tracking for Efficient Extraction of Moving Speakers Location-aware target speaker extraction for hearing aids,

Reference 10

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This paper cites Continuous speech separation: Dataset and analysis,.

Autoregressive Guidance of Deep Spatially Selective Filters using Bayesian Tracking for Efficient Extraction of Moving Speakers Continuous speech separation: Dataset and analysis,

Reference 11

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Observation 7bcda0f7-0e26-4360-b011-b3ad0825631a · outbound

This paper cites The fifth ’CHiME’ speech separation and recognition challenge: Dataset, task and base- lines,.

Autoregressive Guidance of Deep Spatially Selective Filters using Bayesian Tracking for Efficient Extraction of Moving Speakers The fifth ’CHiME’ speech separation and recognition challenge: Dataset, task and base- lines,

Reference 12

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Observation 3e56abaf-a973-449e-9b48-133fb1173ced · outbound

This paper cites Steering deep non-linear spatially selective filters for weakly guided extraction of moving speakers in dynamic scenarios,.

Autoregressive Guidance of Deep Spatially Selective Filters using Bayesian Tracking for Efficient Extraction of Moving Speakers Steering deep non-linear spatially selective filters for weakly guided extraction of moving speakers in dynamic scenarios,

Reference 13

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Observation 935d93cf-aefd-4c2a-ba6e-353e7c333528 · outbound

This paper cites Self-steering deep non-linear spatially selective filters for efficient extraction of moving speakers under weak guidance,.

Autoregressive Guidance of Deep Spatially Selective Filters using Bayesian Tracking for Efficient Extraction of Moving Speakers Self-steering deep non-linear spatially selective filters for efficient extraction of moving speakers under weak guidance,

Reference 14

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Observation 18f07475-e2ae-48db-b279-f491d0a5c387 · outbound

This paper cites Adaptive rotary steering with joint autoregression for robust extraction of closely moving speakers in dynamic scenarios,.

Autoregressive Guidance of Deep Spatially Selective Filters using Bayesian Tracking for Efficient Extraction of Moving Speakers Adaptive rotary steering with joint autoregression for robust extraction of closely moving speakers in dynamic scenarios,

Reference 15

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Observation 9a946ab7-f424-4396-b4f8-74647a2f6076 · outbound

This paper cites Robust sound source tracking using SRP-PHAT and 3D convolutional neural networks,.

Autoregressive Guidance of Deep Spatially Selective Filters using Bayesian Tracking for Efficient Extraction of Moving Speakers Robust sound source tracking using SRP-PHAT and 3D convolutional neural networks,

Reference 16

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Observation 7ffcc3f0-eaa6-446d-b85d-44d07d9e6dd6 · outbound

This paper cites Exploiting temporal context in CNN based multisource DoA estimation,.

Autoregressive Guidance of Deep Spatially Selective Filters using Bayesian Tracking for Efficient Extraction of Moving Speakers Exploiting temporal context in CNN based multisource DoA estimation,

Reference 17

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Observation cb044c9e-8063-4872-b038-87aed62d3c28 · outbound

This paper cites SRP-DNN: Learning direct-path phase difference for multiple moving sound source localization,.

Autoregressive Guidance of Deep Spatially Selective Filters using Bayesian Tracking for Efficient Extraction of Moving Speakers SRP-DNN: Learning direct-path phase difference for multiple moving sound source localization,

Reference 18

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Observation d7f907ae-e77d-48fe-9443-a3e297e383bf · outbound

This paper cites FN-SSL: Full-band and narrow-band fusion for sound source localization,.

Autoregressive Guidance of Deep Spatially Selective Filters using Bayesian Tracking for Efficient Extraction of Moving Speakers FN-SSL: Full-band and narrow-band fusion for sound source localization,

Reference 19

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Observation adaf68ee-d742-4a61-9787-6bbae715e1ff · outbound

This paper cites TF-Mamba: A time-frequency network for sound source localization,.

Autoregressive Guidance of Deep Spatially Selective Filters using Bayesian Tracking for Efficient Extraction of Moving Speakers TF-Mamba: A time-frequency network for sound source localization,

Reference 20

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Observation 56c34e62-b9c9-4bfd-9e13-054bfd6966d0 · outbound

This paper cites A convolutional recurrent neural network for real-time speech enhancement,.

Autoregressive Guidance of Deep Spatially Selective Filters using Bayesian Tracking for Efficient Extraction of Moving Speakers A convolutional recurrent neural network for real-time speech enhancement,

Reference 21

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Observation fece998f-58e1-4b36-9f4e-8e61cdf15c31 · outbound

This paper cites Real time speech enhancement in the waveform domain,.

Autoregressive Guidance of Deep Spatially Selective Filters using Bayesian Tracking for Efficient Extraction of Moving Speakers Real time speech enhancement in the waveform domain,

Reference 22

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Observation 165299e8-d76f-48d6-a69a-24987a9ae63e · outbound

This paper cites Towards efficient models for real-time deep noise suppression,.

Autoregressive Guidance of Deep Spatially Selective Filters using Bayesian Tracking for Efficient Extraction of Moving Speakers Towards efficient models for real-time deep noise suppression,

Reference 23

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Observation d52a1fac-5d43-44a6-8127-d8469af18f22 · outbound

This paper cites Conv-TasNet: Surpassing ideal time–frequency magnitude masking for speech separation,.

Autoregressive Guidance of Deep Spatially Selective Filters using Bayesian Tracking for Efficient Extraction of Moving Speakers Conv-TasNet: Surpassing ideal time–frequency magnitude masking for speech separation,

Reference 24

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Observation 144f0c58-3480-4a32-98a8-70ccf12e99e0 · outbound

This paper cites An investigation of incorporating Mamba for speech enhancement,.

Autoregressive Guidance of Deep Spatially Selective Filters using Bayesian Tracking for Efficient Extraction of Moving Speakers An investigation of incorporating Mamba for speech enhancement,

Reference 25

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This paper cites Iterative autoregression: A novel trick to improve your low-latency speech enhancement model,.

Autoregressive Guidance of Deep Spatially Selective Filters using Bayesian Tracking for Efficient Extraction of Moving Speakers Iterative autoregression: A novel trick to improve your low-latency speech enhancement model,

Reference 26

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This paper cites PARIS: Pseudo-autoregressive siamese training for online speech separation,.

Autoregressive Guidance of Deep Spatially Selective Filters using Bayesian Tracking for Efficient Extraction of Moving Speakers PARIS: Pseudo-autoregressive siamese training for online speech separation,

Reference 27

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Observation 602d12e5-07c4-474d-8e6b-51b5cdac9e22 · outbound

This paper cites ARiSE: Auto-regressive multi- channel speech enhancement,.

Autoregressive Guidance of Deep Spatially Selective Filters using Bayesian Tracking for Efficient Extraction of Moving Speakers ARiSE: Auto-regressive multi- channel speech enhancement,

Reference 28

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This paper cites A wrapped Kalman filter for azimuthal speaker tracking,.

Autoregressive Guidance of Deep Spatially Selective Filters using Bayesian Tracking for Efficient Extraction of Moving Speakers A wrapped Kalman filter for azimuthal speaker tracking,

Reference 29

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This paper cites Particle filtering algorithms for tracking an acoustic source in a reverberant environment,.

Autoregressive Guidance of Deep Spatially Selective Filters using Bayesian Tracking for Efficient Extraction of Moving Speakers Particle filtering algorithms for tracking an acoustic source in a reverberant environment,

Reference 30

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This paper cites Social force model for pedestrian dynamics,.

Autoregressive Guidance of Deep Spatially Selective Filters using Bayesian Tracking for Efficient Extraction of Moving Speakers Social force model for pedestrian dynamics,

Reference 31

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Observation 28b2f17c-0a6b-4eea-8838-9a73f36215de · outbound

This paper cites Benesty, G.

Autoregressive Guidance of Deep Spatially Selective Filters using Bayesian Tracking for Efficient Extraction of Moving Speakers Benesty, G

Reference 32

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This paper cites S ¨arkk¨a,Bayesian Filtering and Smoothing.

Autoregressive Guidance of Deep Spatially Selective Filters using Bayesian Tracking for Efficient Extraction of Moving Speakers S ¨arkk¨a,Bayesian Filtering and Smoothing

Reference 33

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This paper cites A new approach to linear filtering and prediction problems,.

Autoregressive Guidance of Deep Spatially Selective Filters using Bayesian Tracking for Efficient Extraction of Moving Speakers A new approach to linear filtering and prediction problems,

Reference 34

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This paper cites Survey of maneuvering target tracking. Part I. Dynamic models,.

Autoregressive Guidance of Deep Spatially Selective Filters using Bayesian Tracking for Efficient Extraction of Moving Speakers Survey of maneuvering target tracking. Part I. Dynamic models,

Reference 35

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Observation 04f5a10a-33e0-43b0-a1f3-cc929b8134ce · outbound

This paper cites Particle filtering approaches for multiple acoustic source detection and 2-D direction of arrival estimation using a single acoustic vector sensor,.

Autoregressive Guidance of Deep Spatially Selective Filters using Bayesian Tracking for Efficient Extraction of Moving Speakers Particle filtering approaches for multiple acoustic source detection and 2-D direction of arrival estimation using a single acoustic vector sensor,

Reference 36

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Observation 94c5b0b5-7cf2-4858-b8db-8d86cff6b7ff · outbound

This paper cites Particle filter algorithm for DoA tracking using co-prime array,.

Autoregressive Guidance of Deep Spatially Selective Filters using Bayesian Tracking for Efficient Extraction of Moving Speakers Particle filter algorithm for DoA tracking using co-prime array,

Reference 37

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This paper cites Multichannel source separation and tracking with phase dif- ferences by random sample consensus,.

Autoregressive Guidance of Deep Spatially Selective Filters using Bayesian Tracking for Efficient Extraction of Moving Speakers Multichannel source separation and tracking with phase dif- ferences by random sample consensus,

Reference 38

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This paper cites A low complexity weighted least squares narrowband DOA estimator for arbitrary array geometries,.

Autoregressive Guidance of Deep Spatially Selective Filters using Bayesian Tracking for Efficient Extraction of Moving Speakers A low complexity weighted least squares narrowband DOA estimator for arbitrary array geometries,

Reference 39

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Autoregressive Guidance of Deep Spatially Selective Filters using Bayesian Tracking for Efficient Extraction of Moving Speakers Unresolved cited work

Reference 40

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This paper cites Novel approach to nonlinear/non-Gaussian Bayesian state estimation,.

Autoregressive Guidance of Deep Spatially Selective Filters using Bayesian Tracking for Efficient Extraction of Moving Speakers Novel approach to nonlinear/non-Gaussian Bayesian state estimation,

Reference 41

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This paper cites A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking,.

Autoregressive Guidance of Deep Spatially Selective Filters using Bayesian Tracking for Efficient Extraction of Moving Speakers A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking,

Reference 42

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Observation a773220f-0cdb-45ab-b2d1-50b760ecb59e · outbound

This paper cites DOA-estimation based on a complex Watson kernel method,.

Autoregressive Guidance of Deep Spatially Selective Filters using Bayesian Tracking for Efficient Extraction of Moving Speakers DOA-estimation based on a complex Watson kernel method,

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This paper cites Target speaker localization based on the complex Watson mixture model and time-frequency selection neural network,.

Autoregressive Guidance of Deep Spatially Selective Filters using Bayesian Tracking for Efficient Extraction of Moving Speakers Target speaker localization based on the complex Watson mixture model and time-frequency selection neural network,

Reference 44

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Observation 6fc88b72-b8db-44ca-8d8b-1b5bbcbfb02f · outbound

This paper cites On optimal multichannel mean-squared error estimators for speech enhancement,.

Autoregressive Guidance of Deep Spatially Selective Filters using Bayesian Tracking for Efficient Extraction of Moving Speakers On optimal multichannel mean-squared error estimators for speech enhancement,

Reference 45

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Autoregressive Guidance of Deep Spatially Selective Filters using Bayesian Tracking for Efficient Extraction of Moving Speakers Unresolved cited work

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Observation 38977103-5366-4645-8573-c1e485fc2258 · outbound

This paper cites Particle filter with integrated voice activity detection for acoustic source tracking,.

Autoregressive Guidance of Deep Spatially Selective Filters using Bayesian Tracking for Efficient Extraction of Moving Speakers Particle filter with integrated voice activity detection for acoustic source tracking,

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Observation 3fee10fc-fb48-45ed-94d1-0da44dae1ee1 · outbound

This paper cites GCC-Speaker: Target speaker localization with optimal speaker-dependent weighting in multi-speaker scenarios,.

Autoregressive Guidance of Deep Spatially Selective Filters using Bayesian Tracking for Efficient Extraction of Moving Speakers GCC-Speaker: Target speaker localization with optimal speaker-dependent weighting in multi-speaker scenarios,

Reference 48

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Observation b9f7d58c-a8a1-4e6c-9a3d-755e8aa67159 · outbound

This paper cites LocSelect: Target speaker localization with an auditory selective hearing mechanism,.

Autoregressive Guidance of Deep Spatially Selective Filters using Bayesian Tracking for Efficient Extraction of Moving Speakers LocSelect: Target speaker localization with an auditory selective hearing mechanism,

Reference 49

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Observation ee37fec2-36a0-4e0e-83b6-29105fa7860e · outbound

This paper cites Robust frame-level speaker localization in reverberant and noisy envi- ronments by exploiting phase difference losses,.

Autoregressive Guidance of Deep Spatially Selective Filters using Bayesian Tracking for Efficient Extraction of Moving Speakers Robust frame-level speaker localization in reverberant and noisy envi- ronments by exploiting phase difference losses,

Reference 50

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Observation 18471bbb-4a4b-4dd0-b959-25b0813f3c57 · outbound

This paper cites Librispeech: An ASR corpus based on public domain audio books,.

Autoregressive Guidance of Deep Spatially Selective Filters using Bayesian Tracking for Efficient Extraction of Moving Speakers Librispeech: An ASR corpus based on public domain audio books,

Reference 51

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Observation c674ac4e-9480-45ce-87b1-90c720f8e70a · outbound

This paper cites LibriMix: An open-source dataset for generalizable speech separation,.

Autoregressive Guidance of Deep Spatially Selective Filters using Bayesian Tracking for Efficient Extraction of Moving Speakers LibriMix: An open-source dataset for generalizable speech separation,

Reference 52

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Observation 27b19f25-9c7f-4c10-b915-c59fd2a99d56 · outbound

This paper cites gpuRIR: A Python library for room impulse response simulation with GPU acceleration,.

Autoregressive Guidance of Deep Spatially Selective Filters using Bayesian Tracking for Efficient Extraction of Moving Speakers gpuRIR: A Python library for room impulse response simulation with GPU acceleration,

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This paper cites Image method for efficiently simulating small- room acoustics,.

Autoregressive Guidance of Deep Spatially Selective Filters using Bayesian Tracking for Efficient Extraction of Moving Speakers Image method for efficiently simulating small- room acoustics,

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Observation 136c13c8-7027-4a96-901a-eca603b3b334 · outbound

This paper cites Generating sensor signals in isotropic noise fields,.

Autoregressive Guidance of Deep Spatially Selective Filters using Bayesian Tracking for Efficient Extraction of Moving Speakers Generating sensor signals in isotropic noise fields,

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This paper cites Mask-based neural beamforming for moving speakers with self-attention-based tracking,.

Autoregressive Guidance of Deep Spatially Selective Filters using Bayesian Tracking for Efficient Extraction of Moving Speakers Mask-based neural beamforming for moving speakers with self-attention-based tracking,

Reference 56

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This paper cites Array geometry-robust attention-based neural beamformer for moving speakers,.

Autoregressive Guidance of Deep Spatially Selective Filters using Bayesian Tracking for Efficient Extraction of Moving Speakers Array geometry-robust attention-based neural beamformer for moving speakers,

Reference 57

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This paper cites Characterization of moving sound sources direction-of-arrival estimation using different deep learning architectures,.

Autoregressive Guidance of Deep Spatially Selective Filters using Bayesian Tracking for Efficient Extraction of Moving Speakers Characterization of moving sound sources direction-of-arrival estimation using different deep learning architectures,

Reference 58

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This paper cites Goldstein, J.

Autoregressive Guidance of Deep Spatially Selective Filters using Bayesian Tracking for Efficient Extraction of Moving Speakers Goldstein, J

Reference 59

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This paper cites Outdoor walking speeds of apparently healthy adults: A systematic review and meta-analysis,.

Autoregressive Guidance of Deep Spatially Selective Filters using Bayesian Tracking for Efficient Extraction of Moving Speakers Outdoor walking speeds of apparently healthy adults: A systematic review and meta-analysis,

Reference 60

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This paper cites Specification of the social force pedestrian model by evolutionary adjustment to video tracking data,.

Autoregressive Guidance of Deep Spatially Selective Filters using Bayesian Tracking for Efficient Extraction of Moving Speakers Specification of the social force pedestrian model by evolutionary adjustment to video tracking data,

Reference 61

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This paper cites SpatialNet: Extensively learning spatial information for multichannel joint speech separation, denoising and dereverberation,.

Autoregressive Guidance of Deep Spatially Selective Filters using Bayesian Tracking for Efficient Extraction of Moving Speakers SpatialNet: Extensively learning spatial information for multichannel joint speech separation, denoising and dereverberation,

Reference 62

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This paper cites Mamba: Linear-time sequence modeling with selective state spaces,.

Autoregressive Guidance of Deep Spatially Selective Filters using Bayesian Tracking for Efficient Extraction of Moving Speakers Mamba: Linear-time sequence modeling with selective state spaces,

Reference 63

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This paper cites Multichannel long-term streaming neural speech enhancement for static and moving speakers,.

Autoregressive Guidance of Deep Spatially Selective Filters using Bayesian Tracking for Efficient Extraction of Moving Speakers Multichannel long-term streaming neural speech enhancement for static and moving speakers,

Reference 64

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This paper cites Leveraging sound source trajectories for universal sound separation,.

Autoregressive Guidance of Deep Spatially Selective Filters using Bayesian Tracking for Efficient Extraction of Moving Speakers Leveraging sound source trajectories for universal sound separation,

Reference 65

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This paper cites Recurrent deep stacking networks for supervised speech separation,.

Autoregressive Guidance of Deep Spatially Selective Filters using Bayesian Tracking for Efficient Extraction of Moving Speakers Recurrent deep stacking networks for supervised speech separation,

Reference 66

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This paper cites Perceptual evaluation of speech quality (PESQ)-a new method for speech quality assessment of telephone networks and codecs,.

Autoregressive Guidance of Deep Spatially Selective Filters using Bayesian Tracking for Efficient Extraction of Moving Speakers Perceptual evaluation of speech quality (PESQ)-a new method for speech quality assessment of telephone networks and codecs,

Reference 67

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Observation 8270d47f-f88f-4909-8d83-b0db5a9ae679 · outbound

This paper cites An algorithm for predicting the intelligibility of speech masked by modulated noise maskers,.

Autoregressive Guidance of Deep Spatially Selective Filters using Bayesian Tracking for Efficient Extraction of Moving Speakers An algorithm for predicting the intelligibility of speech masked by modulated noise maskers,

Reference 68

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This paper cites Sound event localization and detection of overlapping sources using convolutional recurrent neural networks,.

Autoregressive Guidance of Deep Spatially Selective Filters using Bayesian Tracking for Efficient Extraction of Moving Speakers Sound event localization and detection of overlapping sources using convolutional recurrent neural networks,

Reference 69

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This paper cites 6DoF SELD: Sound event localization and detection using microphones and motion tracking sensors on self-motioning human,.

Autoregressive Guidance of Deep Spatially Selective Filters using Bayesian Tracking for Efficient Extraction of Moving Speakers 6DoF SELD: Sound event localization and detection using microphones and motion tracking sensors on self-motioning human,

Reference 70

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This paper cites The LOCATA challenge: Acoustic source localization and tracking,.

Autoregressive Guidance of Deep Spatially Selective Filters using Bayesian Tracking for Efficient Extraction of Moving Speakers The LOCATA challenge: Acoustic source localization and tracking,

Reference 71

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Autoregressive Guidance of Deep Spatially Selective Filters using Bayesian Tracking for Efficient Extraction of Moving Speakers SDR – Half- baked or well done?

Reference 72

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This paper cites Fairbanks,Voice and Articulation Drillbook.

Autoregressive Guidance of Deep Spatially Selective Filters using Bayesian Tracking for Efficient Extraction of Moving Speakers Fairbanks,Voice and Articulation Drillbook

Reference 73

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This paper cites NISQA: A deep CNN- self-attention model for multidimensional speech quality prediction with crowdsourced datasets,.

Autoregressive Guidance of Deep Spatially Selective Filters using Bayesian Tracking for Efficient Extraction of Moving Speakers NISQA: A deep CNN- self-attention model for multidimensional speech quality prediction with crowdsourced datasets,

Reference 74

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This paper cites NeMo: A toolkit for building AI applica- tions using neural modules,.

Autoregressive Guidance of Deep Spatially Selective Filters using Bayesian Tracking for Efficient Extraction of Moving Speakers NeMo: A toolkit for building AI applica- tions using neural modules,

Reference 75

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This paper cites LibriMix: An Open-Source Dataset for Generalizable Speech Separation.

Autoregressive Guidance of Deep Spatially Selective Filters using Bayesian Tracking for Efficient Extraction of Moving Speakers LibriMix: An Open-Source Dataset for Generalizable Speech Separation

Reference 2020

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