Paper Citation Record · LEDGER

Steering Deep Non-Linear Spatially Selective Filters for Weakly Guided Extraction of Moving Speakers in Dynamic Scenarios

As of 22 August 2026, this Paper Citation Record lists 48 of 48 outbound references and 1 inbound Pith citation observation for arXiv:2505.14517.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2505.14517 v1

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measured 48 of 48 reference resolution

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Pith citing papers itemized under the disclosed page cap.

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A source-named dated measurement, never combined with another source.

Source: pith, observed 2026-08-07T15:38:40.057938Z

Reference resolution

48 of 48 outbound references displayed

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External citation measurements

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Outbound references

Observation 494c937b-f379-4e5e-b43a-3026c86e4ada · outbound

This paper cites Steering Deep Non-Linear Spatially Selective Filters for Weakly Guided Extraction of Moving Speakers in Dynamic Scenarios.

Steering Deep Non-Linear Spatially Selective Filters for Weakly Guided Extraction of Moving Speakers in Dynamic Scenarios Steering Deep Non-Linear Spatially Selective Filters for Weakly Guided Extraction of Moving Speakers in Dynamic Scenarios

Reference 1

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Observation 50d75a8d-89c5-4099-a9d7-333c9741f12f · outbound

This paper cites Target speaker extraction Let the multi-channel observation Y be modeled as additive mixture of reverberant target speech X with noise V.

Steering Deep Non-Linear Spatially Selective Filters for Weakly Guided Extraction of Moving Speakers in Dynamic Scenarios Target speaker extraction Let the multi-channel observation Y be modeled as additive mixture of reverberant target speech X with noise V

Reference 2

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This paper cites an unresolved cited work.

Steering Deep Non-Linear Spatially Selective Filters for Weakly Guided Extraction of Moving Speakers in Dynamic Scenarios Unresolved cited work

Reference 3

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Observation c71f09c8-0ccf-4bed-8e4f-622d530aa485 · outbound

This paper cites Dataset For training and evaluation we create a synthetic dataset with reverberant two-speaker mixtures.

Steering Deep Non-Linear Spatially Selective Filters for Weakly Guided Extraction of Moving Speakers in Dynamic Scenarios Dataset For training and evaluation we create a synthetic dataset with reverberant two-speaker mixtures

Reference 4

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Observation 95a695f8-93ae-4303-b476-3a9058151c0c · outbound

This paper cites distortions, perceptual quality and intelligibility via the metrics SI-SDR [38], PESQ.

Steering Deep Non-Linear Spatially Selective Filters for Weakly Guided Extraction of Moving Speakers in Dynamic Scenarios distortions, perceptual quality and intelligibility via the metrics SI-SDR [38], PESQ

Reference 5

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Steering Deep Non-Linear Spatially Selective Filters for Weakly Guided Extraction of Moving Speakers in Dynamic Scenarios Unresolved cited work

Reference 6

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Steering Deep Non-Linear Spatially Selective Filters for Weakly Guided Extraction of Moving Speakers in Dynamic Scenarios Unresolved cited work

Reference 7

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This paper cites Vary and R.

Steering Deep Non-Linear Spatially Selective Filters for Weakly Guided Extraction of Moving Speakers in Dynamic Scenarios Vary and R

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:38:47.861761Z

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Observation 3cb5a373-0900-490f-bab2-535307f6cb3a · outbound

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

Steering Deep Non-Linear Spatially Selective Filters for Weakly Guided Extraction of Moving Speakers in Dynamic Scenarios Some experiments on the recognition of speech, with one and two ears,

Reference 9

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Observation 410a349e-7d0f-4b48-a7fd-b00524240a84 · outbound

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

Steering Deep Non-Linear Spatially Selective Filters for Weakly Guided Extraction of Moving Speakers in Dynamic Scenarios Neural target speech extraction: An overview,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:38:49.780618Z

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Observation 7fe7b378-dcee-4a82-86fa-d2204857b8c2 · outbound

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

Steering Deep Non-Linear Spatially Selective Filters for Weakly Guided Extraction of Moving Speakers in Dynamic Scenarios Multi-channel speech separation us- ing spatially selective deep non-linear filters,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:38:49.424427Z

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Observation 04ed07f3-b180-4e99-8507-17417696e7d3 · outbound

This paper cites Exploiting spatial information with the informed complex-valued spatial au- toencoder for target speaker extraction,.

Steering Deep Non-Linear Spatially Selective Filters for Weakly Guided Extraction of Moving Speakers in Dynamic Scenarios Exploiting spatial information with the informed complex-valued spatial au- toencoder for target speaker extraction,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:38:49.158142Z

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Observation 2d137f24-81d7-4235-b5d4-874ce235936d · outbound

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

Steering Deep Non-Linear Spatially Selective Filters for Weakly Guided Extraction of Moving Speakers in Dynamic Scenarios Spatially se- lective speaker separation using a DNN with a location dependent feature extraction,

Reference 13

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Observation 230693ca-8243-49b8-b373-c04ce757209a · outbound

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

Steering Deep Non-Linear Spatially Selective Filters for Weakly Guided Extraction of Moving Speakers in Dynamic Scenarios All neural low-latency directional speech extraction,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:38:48.423202Z

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Observation 37be34a9-5bcb-4d03-8a45-b9d63b34422f · outbound

This paper cites ReZero: Region-customizable sound extrac- tion,.

Steering Deep Non-Linear Spatially Selective Filters for Weakly Guided Extraction of Moving Speakers in Dynamic Scenarios ReZero: Region-customizable sound extrac- tion,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:38:48.144411Z

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Observation 3829afd2-1848-4b5c-a762-dcfa3d4c2ec2 · outbound

This paper cites LocSelect: Tar- get speaker localization with an auditory selective hearing mech- anism,.

Steering Deep Non-Linear Spatially Selective Filters for Weakly Guided Extraction of Moving Speakers in Dynamic Scenarios LocSelect: Tar- get speaker localization with an auditory selective hearing mech- anism,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:38:45.933999Z

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Observation 0d7e0552-f06b-48c2-b4f0-e7551c3de182 · outbound

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

Steering Deep Non-Linear Spatially Selective Filters for Weakly Guided Extraction of Moving Speakers in Dynamic Scenarios Continuous speech separation: Dataset and analysis,

Reference 17

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Observation abd6a413-bb2b-40a2-9dd5-a7af88ec2fa1 · outbound

This paper cites The Fifth ’CHiME’ Speech Separation and Recognition Challenge: Dataset, Task and Baselines,.

Steering Deep Non-Linear Spatially Selective Filters for Weakly Guided Extraction of Moving Speakers in Dynamic Scenarios The Fifth ’CHiME’ Speech Separation and Recognition Challenge: Dataset, Task and Baselines,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:38:47.611523Z

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Observation 1db5f57e-104f-45f3-9f82-6b2509775551 · outbound

This paper cites 3S-TSE: Ef- ficient three-stage target speaker extraction for real-time and low- resource applications,.

Steering Deep Non-Linear Spatially Selective Filters for Weakly Guided Extraction of Moving Speakers in Dynamic Scenarios 3S-TSE: Ef- ficient three-stage target speaker extraction for real-time and low- resource applications,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:38:47.312859Z

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Observation 9690b948-53f6-40ec-8485-ac99284fb820 · outbound

This paper cites Improved deep speaker localization and tracking: Revised training paradigm and con- trolled latency,.

Steering Deep Non-Linear Spatially Selective Filters for Weakly Guided Extraction of Moving Speakers in Dynamic Scenarios Improved deep speaker localization and tracking: Revised training paradigm and con- trolled latency,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:38:47.045072Z

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Observation 9d9c51e8-c7aa-46f8-abc6-784e3a60c438 · outbound

This paper cites L-SpEx: Localized target speaker extraction,.

Steering Deep Non-Linear Spatially Selective Filters for Weakly Guided Extraction of Moving Speakers in Dynamic Scenarios L-SpEx: Localized target speaker extraction,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:38:46.751428Z

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Observation 781d094a-0855-44c8-b910-bebd37944d91 · outbound

This paper cites Direction-aware speaker beam for multi-channel speaker extraction.

Steering Deep Non-Linear Spatially Selective Filters for Weakly Guided Extraction of Moving Speakers in Dynamic Scenarios Direction-aware speaker beam for multi-channel speaker extraction

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:38:46.503477Z

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Observation b6e9c8c7-96b9-4baa-89ad-6b2f776037be · outbound

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

Steering Deep Non-Linear Spatially Selective Filters for Weakly Guided Extraction of Moving Speakers in Dynamic Scenarios GCC-Speaker: Target speaker localization with optimal speaker-dependent weighting in multi-speaker scenarios,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:38:46.198628Z

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Observation bf387cd0-8192-4981-a01a-61e0c22044ec · outbound

This paper cites Differentiable particle filters through conditional normalizing flow,.

Steering Deep Non-Linear Spatially Selective Filters for Weakly Guided Extraction of Moving Speakers in Dynamic Scenarios Differentiable particle filters through conditional normalizing flow,

Reference 24

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Observation 7b1555f2-d8f0-47ab-b265-e44308dc70b8 · outbound

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

Steering Deep Non-Linear Spatially Selective Filters for Weakly Guided Extraction of Moving Speakers in Dynamic Scenarios Exploiting temporal context in CNN based multisource DoA estimation,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:38:45.647064Z

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Observation e19ad984-b300-4fec-9bbe-179d40c263f4 · outbound

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

Steering Deep Non-Linear Spatially Selective Filters for Weakly Guided Extraction of Moving Speakers in Dynamic Scenarios A wrapped kalman filter for azimuthal speaker tracking,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:38:45.335695Z

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Observation d69d7bd6-87ac-4f65-b83a-4fbe899c707b · outbound

This paper cites Multiple moving speaker tracking by microphone array on mobile robot,.

Steering Deep Non-Linear Spatially Selective Filters for Weakly Guided Extraction of Moving Speakers in Dynamic Scenarios Multiple moving speaker tracking by microphone array on mobile robot,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:38:45.170723Z

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Observation c6ccc3a2-0947-4f7b-a0a2-b61837d516bf · outbound

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

Steering Deep Non-Linear Spatially Selective Filters for Weakly Guided Extraction of Moving Speakers in Dynamic Scenarios Particle filter algorithm for DoA track- ing using co-prime array,

Reference 28

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Observation 898136c1-96c6-42d8-9ea5-c342a3fa1e5d · outbound

This paper cites Particle filtering al- gorithms for tracking an acoustic source in a reverberant environ- ment,.

Steering Deep Non-Linear Spatially Selective Filters for Weakly Guided Extraction of Moving Speakers in Dynamic Scenarios Particle filtering al- gorithms for tracking an acoustic source in a reverberant environ- ment,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:38:44.622606Z

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Observation 09e92487-8ac9-4b12-96c9-766dd799fade · outbound

This paper cites Speaker tracking based on dis- tributed particle filter in distributed microphone networks,.

Steering Deep Non-Linear Spatially Selective Filters for Weakly Guided Extraction of Moving Speakers in Dynamic Scenarios Speaker tracking based on dis- tributed particle filter in distributed microphone networks,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:38:44.403064Z

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Observation a2ba46fd-8a07-43f5-b0fa-04377edf3a99 · outbound

This paper cites KalmanNet: Neural network aided kalman filtering for partially known dynamics,.

Steering Deep Non-Linear Spatially Selective Filters for Weakly Guided Extraction of Moving Speakers in Dynamic Scenarios KalmanNet: Neural network aided kalman filtering for partially known dynamics,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:38:44.182090Z

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Observation c4dca429-07d4-431b-8b75-46dfd5df2b1c · outbound

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

Steering Deep Non-Linear Spatially Selective Filters for Weakly Guided Extraction of Moving Speakers in Dynamic Scenarios Survey of maneuvering target tracking. Part I. Dynamic models,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:38:41.826258Z

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Observation 912a4c56-b5a1-409f-9afc-b811b34d4f24 · outbound

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

Steering Deep Non-Linear Spatially Selective Filters for Weakly Guided Extraction of Moving Speakers in Dynamic Scenarios SRP-DNN: Learning direct-path phase difference for multiple moving sound source localization,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:38:43.608834Z

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Observation 8174055b-4ec7-4fc2-87eb-5b140c8e65e4 · outbound

This paper cites MIMO-DoAnet: Multi-channel input and multiple outputs DoA network with unknown number of sound sources,.

Steering Deep Non-Linear Spatially Selective Filters for Weakly Guided Extraction of Moving Speakers in Dynamic Scenarios MIMO-DoAnet: Multi-channel input and multiple outputs DoA network with unknown number of sound sources,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:38:43.283419Z

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Observation bad3421f-7735-44e2-9716-7c0dc9890873 · outbound

This paper cites A learning-based approach to direction of arrival estimation in noisy and reverberant environments,.

Steering Deep Non-Linear Spatially Selective Filters for Weakly Guided Extraction of Moving Speakers in Dynamic Scenarios A learning-based approach to direction of arrival estimation in noisy and reverberant environments,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:38:42.992867Z

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Observation fbf282c8-4294-45f4-92bf-bd258a58a7a1 · outbound

This paper cites Deep net- works for DoA estimation in low SNR,.

Steering Deep Non-Linear Spatially Selective Filters for Weakly Guided Extraction of Moving Speakers in Dynamic Scenarios Deep net- works for DoA estimation in low SNR,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:38:42.720935Z

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Observation 3dc1bd72-8e9b-4a7f-b394-695aae3b34a8 · outbound

This paper cites Lib- rispeech: An ASR corpus based on public domain audio books,.

Steering Deep Non-Linear Spatially Selective Filters for Weakly Guided Extraction of Moving Speakers in Dynamic Scenarios Lib- rispeech: An ASR corpus based on public domain audio books,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:38:42.385741Z

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Observation 2d3af42a-7aa7-4019-8d49-2ca9da090778 · outbound

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

Steering Deep Non-Linear Spatially Selective Filters for Weakly Guided Extraction of Moving Speakers in Dynamic Scenarios Image method for efficiently simulating small-room acoustics,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:38:42.118688Z

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Observation bcbab81b-995d-4c0c-a777-8c95a9d966d5 · outbound

This paper cites Table 1 displays the results using FT-JNF with different tracking and training strategies for three levels of speaker dynamics, complemented by fig.

Steering Deep Non-Linear Spatially Selective Filters for Weakly Guided Extraction of Moving Speakers in Dynamic Scenarios Table 1 displays the results using FT-JNF with different tracking and training strategies for three levels of speaker dynamics, complemented by fig

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:38:50.390119Z

Source-reported events for the cited work

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Observation 3b9ba10c-8545-4541-a349-57e46c218f8d · outbound

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

Steering Deep Non-Linear Spatially Selective Filters for Weakly Guided Extraction of Moving Speakers in Dynamic Scenarios LibriMix: An Open-Source Dataset for Generalizable Speech Separation

Reference 40

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Observation 5bbd1f29-d292-4505-95c7-234ec4b54547 · outbound

This paper cites Accurate adaptive filtering in square-root Hann windowed short-time fourier transform do- main,.

Steering Deep Non-Linear Spatially Selective Filters for Weakly Guided Extraction of Moving Speakers in Dynamic Scenarios Accurate adaptive filtering in square-root Hann windowed short-time fourier transform do- main,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:38:41.591937Z

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Observation 2738c0dc-21a3-4f37-92eb-3b8e00d23607 · outbound

This paper cites Neural directional filtering: Far-field directivity control with a small microphone array,.

Steering Deep Non-Linear Spatially Selective Filters for Weakly Guided Extraction of Moving Speakers in Dynamic Scenarios Neural directional filtering: Far-field directivity control with a small microphone array,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:38:41.378031Z

Source-reported events for the cited work

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Observation 86527ed7-fb99-4cce-87a4-821f33bd374f · outbound

This paper cites Spatially constrained vs. uncon- strained filtering in neural spatiospectral filters for multichannel speech enhancement,.

Steering Deep Non-Linear Spatially Selective Filters for Weakly Guided Extraction of Moving Speakers in Dynamic Scenarios Spatially constrained vs. uncon- strained filtering in neural spatiospectral filters for multichannel speech enhancement,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:38:41.174366Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 9002196a-f29d-4562-aad2-45b815c9700a · outbound

This paper cites Utilizing head rotation data in DNN- based multi-channel speech enhancement for hearing aids,.

Steering Deep Non-Linear Spatially Selective Filters for Weakly Guided Extraction of Moving Speakers in Dynamic Scenarios Utilizing head rotation data in DNN- based multi-channel speech enhancement for hearing aids,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:38:41.001442Z

Source-reported events for the cited work

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Observation 738d6972-2fc1-4d96-8fad-e507233b9679 · outbound

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

Steering Deep Non-Linear Spatially Selective Filters for Weakly Guided Extraction of Moving Speakers in Dynamic Scenarios gpuRIR: A Python library for room impulse response simulation with GPU accelera- tion,

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:38:40.828616Z

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Observation 842edd10-19ce-4845-b16d-dcbc7bd38f40 · outbound

This paper cites SDR – Half-baked or well done?.

Steering Deep Non-Linear Spatially Selective Filters for Weakly Guided Extraction of Moving Speakers in Dynamic Scenarios SDR – Half-baked or well done?

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:38:40.666335Z

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Observation df95c47f-3d8d-4806-aa0e-a00cb7d5e626 · outbound

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

Steering Deep Non-Linear Spatially Selective Filters for Weakly Guided Extraction of Moving Speakers in Dynamic Scenarios Perceptual eval- uation of speech quality (PESQ)-a new method for speech quality assessment of telephone networks and codecs,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:38:40.498529Z

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Observation 721060df-7427-406a-995f-130298734538 · outbound

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

Steering Deep Non-Linear Spatially Selective Filters for Weakly Guided Extraction of Moving Speakers in Dynamic Scenarios An algorithm for predicting the intelligi- bility of speech masked by modulated noise maskers,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:38:40.298861Z

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Pith citing papers

Observation 494c937b-f379-4e5e-b43a-3026c86e4ada · inbound