Paper Citation Record · LEDGER

A Lightweight Hybrid Dual Channel Speech Enhancement System under Low-SNR Conditions

As of 20 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 1 inbound Pith citation observation for arXiv:2505.19597.

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

pith.paper-citation-record.v1
2505.19597 v1

Coverage vector

measured 38 of 38 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:17:44.421202Z

measured 39 of 39 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:17:40.622117Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T14:17:44.511038Z

Reference resolution

38 of 38 outbound references displayed

verified exact1
verified fuzzy29
unresolved8
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b8802c03-b112-4f14-91ee-bacdf54c6f4e · outbound

This paper cites A Lightweight Hybrid Dual Channel Speech Enhancement System under Low-SNR Conditions.

A Lightweight Hybrid Dual Channel Speech Enhancement System under Low-SNR Conditions A Lightweight Hybrid Dual Channel Speech Enhancement System under Low-SNR Conditions

Reference 1

Resolution: verified exact; local_arxiv, observed 2026-08-07T14:17:44.541384Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation a2db8735-584d-4863-a1c0-fca11e3e1383 · outbound

This paper cites an unresolved cited work.

A Lightweight Hybrid Dual Channel Speech Enhancement System under Low-SNR Conditions Unresolved cited work

Reference 2

Resolution: unresolved; raw_fallback, observed 2026-08-07T14:17:49.715084Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 8c360652-82e7-4edc-92f5-399a12a87637 · outbound

This paper cites We introduce the dual-channel version of the model and incorporate several modifications to ensure the comprehensive utilization of diverse information.

A Lightweight Hybrid Dual Channel Speech Enhancement System under Low-SNR Conditions We introduce the dual-channel version of the model and incorporate several modifications to ensure the comprehensive utilization of diverse information

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:17:49.537873Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 32d1c6b6-9ccd-4589-b6eb-f5a2e69f2a7d · outbound

This paper cites Dataset We generate the simulated dataset with the image method [23], with dual-channel RIRs based on a linear array with two mi- crophones placed 4 cm apart.

A Lightweight Hybrid Dual Channel Speech Enhancement System under Low-SNR Conditions Dataset We generate the simulated dataset with the image method [23], with dual-channel RIRs based on a linear array with two mi- crophones placed 4 cm apart

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:17:49.320072Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation f656518f-3b6e-4c28-8408-a7cc9a91044c · outbound

This paper cites an unresolved cited work.

A Lightweight Hybrid Dual Channel Speech Enhancement System under Low-SNR Conditions Unresolved cited work

Reference 5

Resolution: unresolved; raw_fallback, observed 2026-08-07T14:17:49.115955Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 897e9535-dcd0-4c82-ab4a-9fb579b4c4e9 · outbound

This paper cites Aux-IV A acts as a coarse esti- mator, providing auxiliary information, while the GTCRN fur- ther refines the speech quality.

A Lightweight Hybrid Dual Channel Speech Enhancement System under Low-SNR Conditions Aux-IV A acts as a coarse esti- mator, providing auxiliary information, while the GTCRN fur- ther refines the speech quality

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:17:48.772328Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 69a2d03f-277c-4304-9c68-b1629645dcb8 · outbound

This paper cites 12274221) and the AI & AI for Science Project of Nanjing University.

A Lightweight Hybrid Dual Channel Speech Enhancement System under Low-SNR Conditions 12274221) and the AI & AI for Science Project of Nanjing University

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:17:48.605399Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation f596b788-2166-41d1-abcc-4a31589b3b09 · outbound

This paper cites Adl- mvdr: All deep learning mvdr beamformer for target speech sepa- ration,.

A Lightweight Hybrid Dual Channel Speech Enhancement System under Low-SNR Conditions Adl- mvdr: All deep learning mvdr beamformer for target speech sepa- ration,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:17:47.157317Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation a0c2ebbf-794d-4026-bfab-80690bebe929 · outbound

This paper cites Real-time speech enhance- ment using an efficient convolutional recurrent network for dual- microphone mobile phones in close-talk scenarios,.

A Lightweight Hybrid Dual Channel Speech Enhancement System under Low-SNR Conditions Real-time speech enhance- ment using an efficient convolutional recurrent network for dual- microphone mobile phones in close-talk scenarios,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:17:48.400563Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 0cb69b22-7e7e-4363-81c4-28bdab57a559 · outbound

This paper cites A smart binaural hearing aid architecture leveraging a smartphone app with deep- learning speech enhancement,.

A Lightweight Hybrid Dual Channel Speech Enhancement System under Low-SNR Conditions A smart binaural hearing aid architecture leveraging a smartphone app with deep- learning speech enhancement,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:17:48.244809Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation eeb87ecf-9234-46fd-bdf0-7b70af0eab83 · outbound

This paper cites Design of matrix wiener filter for noise reduction and speech enhancement in hearing aids,.

A Lightweight Hybrid Dual Channel Speech Enhancement System under Low-SNR Conditions Design of matrix wiener filter for noise reduction and speech enhancement in hearing aids,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:17:48.093781Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation cca72d77-7d87-41db-958a-b6cc373a6d21 · outbound

This paper cites Unetgan: A robust speech enhancement approach in time domain for ex- tremely low signal-to-noise ratio condition,.

A Lightweight Hybrid Dual Channel Speech Enhancement System under Low-SNR Conditions Unetgan: A robust speech enhancement approach in time domain for ex- tremely low signal-to-noise ratio condition,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:17:47.918216Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 608263f3-3cae-41c1-b5c6-8494537ee6ba · outbound

This paper cites Masking and inpainting: A two-stage speech enhancement ap- proach for low snr and non-stationary noise,.

A Lightweight Hybrid Dual Channel Speech Enhancement System under Low-SNR Conditions Masking and inpainting: A two-stage speech enhancement ap- proach for low snr and non-stationary noise,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:17:47.702545Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 6b3a0ed6-5987-44e8-b5fa-43fb67c2bf84 · outbound

This paper cites Snr- progressive model with harmonic compensation for low-snr speech enhancement,.

A Lightweight Hybrid Dual Channel Speech Enhancement System under Low-SNR Conditions Snr- progressive model with harmonic compensation for low-snr speech enhancement,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:17:47.511680Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 94d42b53-84c4-4ff8-95fc-84c2051afd60 · outbound

This paper cites Harmonic enhancement using learnable comb filter for light-weight full-band speech en- hancement model,.

A Lightweight Hybrid Dual Channel Speech Enhancement System under Low-SNR Conditions Harmonic enhancement using learnable comb filter for light-weight full-band speech en- hancement model,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:17:47.356323Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 9539e488-e3c1-4ed0-b565-d02a5ec16cd6 · outbound

This paper cites Speech extraction un- der extremely low snr conditions,.

A Lightweight Hybrid Dual Channel Speech Enhancement System under Low-SNR Conditions Speech extraction un- der extremely low snr conditions,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:17:46.076071Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation c4573e8d-738a-460b-91ae-8f65ef2149a4 · outbound

This paper cites A hybrid dsp/deep learning approach to real-time full-band speech enhancement,.

A Lightweight Hybrid Dual Channel Speech Enhancement System under Low-SNR Conditions A hybrid dsp/deep learning approach to real-time full-band speech enhancement,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:17:46.987771Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 1acc2e6d-9f99-4c42-9cf7-0b324836825e · outbound

This paper cites Gtcrn: A speech enhancement model requiring ultralow computational resources,.

A Lightweight Hybrid Dual Channel Speech Enhancement System under Low-SNR Conditions Gtcrn: A speech enhancement model requiring ultralow computational resources,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:17:46.853678Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 96f54626-e52b-4857-a81b-20ef95500c5d · outbound

This paper cites DPCRN: Dual-Path Con- volution Recurrent Network for Single Channel Speech Enhance- ment,.

A Lightweight Hybrid Dual Channel Speech Enhancement System under Low-SNR Conditions DPCRN: Dual-Path Con- volution Recurrent Network for Single Channel Speech Enhance- ment,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:17:46.719351Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation a4efecf6-e1a6-4086-8cdc-92fe7b803155 · outbound

This paper cites Shufflenet v2: Practi- cal guidelines for efficient cnn architecture design,.

A Lightweight Hybrid Dual Channel Speech Enhancement System under Low-SNR Conditions Shufflenet v2: Practi- cal guidelines for efficient cnn architecture design,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:17:46.602346Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 71b5bf3d-561c-4d00-9672-47d0b324f96e · outbound

This paper cites Effi- cient sequence learning with group recurrent networks,.

A Lightweight Hybrid Dual Channel Speech Enhancement System under Low-SNR Conditions Effi- cient sequence learning with group recurrent networks,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:17:46.490691Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation aa696cef-9f68-4cd9-aa94-1f47d3ec50a4 · outbound

This paper cites Independent vector analysis: An extension of ica to multivariate components,.

A Lightweight Hybrid Dual Channel Speech Enhancement System under Low-SNR Conditions Independent vector analysis: An extension of ica to multivariate components,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:17:46.364414Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 2b9e7037-a2df-442e-971d-f96306bee9c4 · outbound

This paper cites Blind source sep- aration exploiting higher-order frequency dependencies,.

A Lightweight Hybrid Dual Channel Speech Enhancement System under Low-SNR Conditions Blind source sep- aration exploiting higher-order frequency dependencies,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:17:46.255804Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 74bb449a-b0d9-4c9f-b44e-fe4ed37441b9 · outbound

This paper cites Icassp 2021 deep noise suppres- sion challenge,.

A Lightweight Hybrid Dual Channel Speech Enhancement System under Low-SNR Conditions Icassp 2021 deep noise suppres- sion challenge,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:17:45.151316Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation ab23af90-d7d4-4e58-85db-9be1d2d13632 · outbound

This paper cites Complex ratio mask- ing for monaural speech separation,.

A Lightweight Hybrid Dual Channel Speech Enhancement System under Low-SNR Conditions Complex ratio mask- ing for monaural speech separation,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:17:45.892466Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation f81a1dbe-4163-45f1-8711-5b8f3a76c9b1 · outbound

This paper cites Stable and fast update rules for independent vector anal- ysis based on auxiliary function technique,.

A Lightweight Hybrid Dual Channel Speech Enhancement System under Low-SNR Conditions Stable and fast update rules for independent vector anal- ysis based on auxiliary function technique,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:17:45.714746Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 608ba41f-c3f4-41d0-9ff6-9abe365ccfa3 · outbound

This paper cites An auxiliary-function approach to online independent vector analy- sis for real-time blind source separation,.

A Lightweight Hybrid Dual Channel Speech Enhancement System under Low-SNR Conditions An auxiliary-function approach to online independent vector analy- sis for real-time blind source separation,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:17:45.556195Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation c9be2910-c592-4e1a-94a9-f418cc40aefb · outbound

This paper cites Learning cross-lingual sentence representa- tions via a multi-task dual-encoder model,.

A Lightweight Hybrid Dual Channel Speech Enhancement System under Low-SNR Conditions Learning cross-lingual sentence representa- tions via a multi-task dual-encoder model,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:17:45.405486Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 7e7a2dd5-93a4-4122-a94e-d2ee3c42f2de · outbound

This paper cites an unresolved cited work.

A Lightweight Hybrid Dual Channel Speech Enhancement System under Low-SNR Conditions Unresolved cited work

Reference 29

Resolution: unresolved; raw_fallback, observed 2026-08-07T14:17:48.934118Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation e8486394-c69d-4519-9fa2-210166944e8d · outbound

This paper cites Dual-path rnn: efficient long sequence modeling for time-domain single-channel speech sepa- ration,.

A Lightweight Hybrid Dual Channel Speech Enhancement System under Low-SNR Conditions Dual-path rnn: efficient long sequence modeling for time-domain single-channel speech sepa- ration,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:17:45.277489Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation c44980d9-dcd1-453e-bf6b-70550e3014db · outbound

This paper cites A consolidated view of loss functions for supervised deep learning-based speech enhancement,.

A Lightweight Hybrid Dual Channel Speech Enhancement System under Low-SNR Conditions A consolidated view of loss functions for supervised deep learning-based speech enhancement,

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-07T14:17:44.045053Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4417ca57-261f-4d9d-8b11-20fb4f60dc2d · outbound

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

A Lightweight Hybrid Dual Channel Speech Enhancement System under Low-SNR Conditions Image method for efficiently sim- ulating small-room acoustics,

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-07T14:17:44.124801Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 63f56ae1-7dc8-45b1-9967-fc408a3c2b84 · outbound

This paper cites Description and Discussion on DCASE 2022 Challenge Task 2: Unsupervised Anomalous Sound Detection for Machine Condition Monitoring Applying Domain Generalization Techniques.

A Lightweight Hybrid Dual Channel Speech Enhancement System under Low-SNR Conditions Description and Discussion on DCASE 2022 Challenge Task 2: Unsupervised Anomalous Sound Detection for Machine Condition Monitoring Applying Domain Generalization Techniques

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-07T14:17:44.275508Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1e793b28-6f80-4c1d-b83f-7e907992fe67 · outbound

This paper cites Adam: A method for stochastic opti- mization,.

A Lightweight Hybrid Dual Channel Speech Enhancement System under Low-SNR Conditions Adam: A method for stochastic opti- mization,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:17:45.006406Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation c8daf7f5-5a67-4bb9-b849-90011e417f17 · outbound

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

A Lightweight Hybrid Dual Channel Speech Enhancement System under Low-SNR Conditions Perceptual evaluation of speech quality (pesq)-a new method for speech quality assessment of telephone networks and codecs,

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-07T14:17:44.295452Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a05ede50-fd21-4b5d-aba4-21f65b742f7a · outbound

This paper cites A short- time objective intelligibility measure for time-frequency weighted noisy speech,.

A Lightweight Hybrid Dual Channel Speech Enhancement System under Low-SNR Conditions A short- time objective intelligibility measure for time-frequency weighted noisy speech,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:17:44.841097Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 4a3c725b-dfe4-47f3-a694-d968c1c2de67 · outbound

This paper cites Dnsmos: A non-intrusive perceptual objective speech quality metric to evaluate noise sup- pressors,.

A Lightweight Hybrid Dual Channel Speech Enhancement System under Low-SNR Conditions Dnsmos: A non-intrusive perceptual objective speech quality metric to evaluate noise sup- pressors,

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-07T14:17:44.359578Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 334c62a7-fa92-42f8-ad29-ad5675678f8e · outbound

This paper cites Dnsmos p. 835: A non-intrusive perceptual objective speech quality metric to evaluate noise suppressors,.

A Lightweight Hybrid Dual Channel Speech Enhancement System under Low-SNR Conditions Dnsmos p. 835: A non-intrusive perceptual objective speech quality metric to evaluate noise suppressors,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:17:44.703698Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Pith citing papers

Observation b8802c03-b112-4f14-91ee-bacdf54c6f4e · inbound