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Paper Citation Record · LEDGER

DeepFilterNet: Perceptually Motivated Real-Time Speech Enhancement

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2305.08227.

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

pith.paper-citation-record.v1
2305.08227 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T16:26:51.272692Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-16T03:50:33.661324Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 02f93389-3f82-4c2e-bc23-9fcb5497ebd2 · inbound

Let SSMs be ConvNets: State-space Modeling with Optimal Tensor Contractions cites this paper.

Let SSMs be ConvNets: State-space Modeling with Optimal Tensor Contractions DeepFilterNet: Perceptually Motivated Real-Time Speech Enhancement

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-10T16:26:51.272692Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T16:26:51.272692Z digest=sha256:ad0d14d5e03aad069bff06c618959daa5b77d088e11c5c767cd1bfd18b759262

Observation 65aa04ff-a1e6-40ad-a4fb-0dae91f38506 · inbound

A Framework for Robust Speaker Verification in Highly Noisy Environments Leveraging Both Noisy and Enhanced Audio cites this paper.

A Framework for Robust Speaker Verification in Highly Noisy Environments Leveraging Both Noisy and Enhanced Audio DeepFilterNet: Perceptually Motivated Real-Time Speech Enhancement

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-05T16:08:49.488573Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T16:08:49.488573Z digest=sha256:1b218ad48572cd1b9fe2ce03b91bc4b8ff29fd7e4c7a5c447691d3e9eaaaaf04

Observation 93f595f9-2e83-43bb-b334-24ffcd62f62e · inbound

Lightweight DNN for Full-Band Speech Denoising on Mobile Devices: Exploiting Long and Short Temporal Patterns cites this paper.

Lightweight DNN for Full-Band Speech Denoising on Mobile Devices: Exploiting Long and Short Temporal Patterns DeepFilterNet: Perceptually Motivated Real-Time Speech Enhancement

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-05T05:40:19.470357Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T05:40:19.470357Z digest=sha256:f847cc00952bbe67898e930f8957e5487e1b65300fe035036eff14152c5a1325

Observation c1794bd0-c655-4a28-996f-d5b1dc1d71d2 · inbound

DPDFNet: Boosting DeepFilterNet2 via Dual-Path RNN cites this paper.

DPDFNet: Boosting DeepFilterNet2 via Dual-Path RNN DeepFilterNet: Perceptually Motivated Real-Time Speech Enhancement

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-03T15:34:29.364511Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T15:34:29.364511Z digest=sha256:06577da55fef68e19ddb4c39706212fe708f1897a2398b0f579dd08468eca2be

Observation d0f43619-6ea8-444b-9148-d947e78911e1 · inbound

From Diet to Free Lunch: Estimating Auxiliary Signal Properties using Dynamic Pruning Masks in Speech Enhancement Networks cites this paper.

From Diet to Free Lunch: Estimating Auxiliary Signal Properties using Dynamic Pruning Masks in Speech Enhancement Networks DeepFilterNet: Perceptually Motivated Real-Time Speech Enhancement

Reference 12

Resolution
verified exact
arxiv_id, observed 2026-05-16T03:50:33.665240Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-16T03:50:17.300414Z digest=sha256:02cf57b8e00171e75c2c6d479dedfc7243b2314961fd9aec4d8e11e1ddd6ac5c