Paper Citation Record · LEDGER

Scalable Speech Enhancement with Dynamic Channel Pruning

As of 15 August 2026, this Paper Citation Record lists 30 of 30 outbound references and 1 inbound Pith citation observation for arXiv:2412.17121.

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

pith.paper-citation-record.v1
2412.17121 v1

Coverage vector

measured 30 of 30 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T05:50:33.022884Z

measured 31 of 31 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T05:50:32.881331Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-11T05:50:33.149000Z

Reference resolution

30 of 30 outbound references displayed

verified exact4
verified fuzzy14
unresolved11
parse uncertain0
malformed identifier0
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 67651c93-d372-4d82-81f5-dab34005a60a · outbound

This paper cites an unresolved cited work.

Scalable Speech Enhancement with Dynamic Channel Pruning Unresolved cited work

Reference 1

Resolution: unresolved; raw_fallback, observed 2026-08-11T05:50:33.277583Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 2e53305b-00ec-49d8-a861-5dc4f3965fd2 · outbound

This paper cites Scalable Speech Enhancement with Dynamic Channel Pruning.

Scalable Speech Enhancement with Dynamic Channel Pruning Scalable Speech Enhancement with Dynamic Channel Pruning

Reference 2

Resolution: metadata mismatch; local_arxiv, observed 2026-08-11T05:50:33.152172Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation f9079028-aceb-495c-9d25-99827c463927 · outbound

This paper cites an unresolved cited work.

Scalable Speech Enhancement with Dynamic Channel Pruning Unresolved cited work

Reference 3

Resolution: unresolved; raw_fallback, observed 2026-08-11T05:50:33.270117Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 1f31d2c3-9ef7-4cba-a8fd-f6bec90ce491 · outbound

This paper cites binary special case.

Scalable Speech Enhancement with Dynamic Channel Pruning binary special case

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:50:33.263047Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 29353480-4267-4527-a76b-08bcb33fc136 · outbound

This paper cites Similarly, the test set includes 824 samples from two other speakers mixed with unseen noise at SNR between 17.5 dB and 2.5 dB.

Scalable Speech Enhancement with Dynamic Channel Pruning Similarly, the test set includes 824 samples from two other speakers mixed with unseen noise at SNR between 17.5 dB and 2.5 dB

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:50:33.255484Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 4a5fff94-5043-41cc-8fba-907fa2b1e1ee · outbound

This paper cites 4, we relate the denoising performances and computational efficiency of the Conv-FSENet static baselines with their DynCP counterparts.

Scalable Speech Enhancement with Dynamic Channel Pruning 4, we relate the denoising performances and computational efficiency of the Conv-FSENet static baselines with their DynCP counterparts

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:50:33.247793Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation eba90e44-bb85-4fbc-867a-0ca353b41f71 · outbound

This paper cites Com- pared to the static baseline in Table 2, our dynamic models can save up to 29.6 % of MACs while only incurring a 0.75 % drop in PESQ.

Scalable Speech Enhancement with Dynamic Channel Pruning Com- pared to the static baseline in Table 2, our dynamic models can save up to 29.6 % of MACs while only incurring a 0.75 % drop in PESQ

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:50:33.240258Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation ac8f312b-d7a8-4cbe-9f4e-6e5825a3338b · outbound

This paper cites Real Time Speech Enhancement in the Waveform Domain.

Scalable Speech Enhancement with Dynamic Channel Pruning Real Time Speech Enhancement in the Waveform Domain

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-11T05:50:32.961275Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cbcbfa96-5ef0-4c40-9241-a9c5c0fca454 · outbound

This paper cites TFCN: Temporal-Frequential Convolutional Network for Single-Channel Speech Enhancement.

Scalable Speech Enhancement with Dynamic Channel Pruning TFCN: Temporal-Frequential Convolutional Network for Single-Channel Speech Enhancement

Reference 9

Resolution: verified exact; local_arxiv, observed 2026-08-11T05:50:33.134944Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 5114dfa6-4de3-4f8f-a34e-b0e42a252e47 · outbound

This paper cites Dynamic Neural Networks: A Survey.

Scalable Speech Enhancement with Dynamic Channel Pruning Dynamic Neural Networks: A Survey

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-11T05:50:32.967666Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c75e0247-8665-41d5-b442-9ecf0712cbef · outbound

This paper cites Don't shoot butterfly with rifles: Multi-channel Continuous Speech Separation with Early Exit Transformer.

Scalable Speech Enhancement with Dynamic Channel Pruning Don't shoot butterfly with rifles: Multi-channel Continuous Speech Separation with Early Exit Transformer

Reference 11

Resolution: verified exact; local_arxiv, observed 2026-08-11T05:50:33.117245Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation ce29485e-ec0c-4d47-87e4-2f35bcf08ee6 · outbound

This paper cites Dynamic nsNET2: Efficient Deep Noise Suppression with Early Exiting,.

Scalable Speech Enhancement with Dynamic Channel Pruning Dynamic nsNET2: Efficient Deep Noise Suppression with Early Exiting,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:50:33.232276Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 920ac1db-45a9-4cba-bcf4-d5fc19e15f86 · outbound

This paper cites Latent Iterative Refinement for Modular Source Separation.

Scalable Speech Enhancement with Dynamic Channel Pruning Latent Iterative Refinement for Modular Source Separation

Reference 13

Resolution: verified exact; local_arxiv, observed 2026-08-11T05:50:33.106134Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation d605f2c4-06fd-43e3-8545-5df5015bf297 · outbound

This paper cites Slim-Tasnet: A Slimmable Neural Network for Speech Separation,.

Scalable Speech Enhancement with Dynamic Channel Pruning Slim-Tasnet: A Slimmable Neural Network for Speech Separation,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:50:33.223156Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 43c6f393-c057-4600-be97-7da8a5cbe285 · outbound

This paper cites Runtime Neural Pruning,.

Scalable Speech Enhancement with Dynamic Channel Pruning Runtime Neural Pruning,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:50:33.215603Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 56562fbe-d693-45da-ab36-ca925f392913 · outbound

This paper cites Channel Gating Neural Networks,.

Scalable Speech Enhancement with Dynamic Channel Pruning Channel Gating Neural Networks,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:50:33.207839Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 037fcc45-4047-40e1-980b-f4a9d0b8900c · outbound

This paper cites Dynamic Channel Pruning: Feature Boosting and Suppression.

Scalable Speech Enhancement with Dynamic Channel Pruning Dynamic Channel Pruning: Feature Boosting and Suppression

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-11T05:50:32.987708Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b06d1983-ce27-4122-a7ef-fe393eafd75e · outbound

This paper cites Runtime Network Routing for Efficient Image Classification,.

Scalable Speech Enhancement with Dynamic Channel Pruning Runtime Network Routing for Efficient Image Classification,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:50:33.200482Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 8b42be61-3b93-4502-b66e-f0e910d6c38d · outbound

This paper cites Dynamic Neural Network Channel Execution for Efficient Training.

Scalable Speech Enhancement with Dynamic Channel Pruning Dynamic Neural Network Channel Execution for Efficient Training

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-11T05:50:32.993230Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 762861c6-4ce9-491a-91b6-c994985b9c9f · outbound

This paper cites Learning to Inference with Early Exit in the Progressive Speech Enhancement.

Scalable Speech Enhancement with Dynamic Channel Pruning Learning to Inference with Early Exit in the Progressive Speech Enhancement

Reference 20

Resolution: verified exact; local_arxiv, observed 2026-08-11T05:50:33.081762Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 1a4b6fbe-81eb-4cf1-8be0-92b674329730 · outbound

This paper cites Conv-TasNet: Surpassing Ideal Time-Frequency Magnitude Masking for Speech Separation.

Scalable Speech Enhancement with Dynamic Channel Pruning Conv-TasNet: Surpassing Ideal Time-Frequency Magnitude Masking for Speech Separation

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-11T05:50:32.999084Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 072ae6a3-0ff3-431f-94c3-a0b89076dc3f · outbound

This paper cites Dynamic Slimmable Network for Speech Sepa- ration,.

Scalable Speech Enhancement with Dynamic Channel Pruning Dynamic Slimmable Network for Speech Sepa- ration,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:50:33.192578Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 4fe09e84-d106-495b-83f1-e7cf7a090e50 · outbound

This paper cites TCNN: Temporal Con- volutional Neural Network for Real-time Speech Enhancement in the Time Domain,.

Scalable Speech Enhancement with Dynamic Channel Pruning TCNN: Temporal Con- volutional Neural Network for Real-time Speech Enhancement in the Time Domain,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:50:33.184795Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation cc3ab9c6-14aa-498d-be7c-c3477a1e724d · outbound

This paper cites An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling.

Scalable Speech Enhancement with Dynamic Channel Pruning An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-11T05:50:33.006789Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 47fc8455-13c8-462c-a6e8-2ef1615075ae · outbound

This paper cites 79–86, Springer International Publishing, 2020.

Scalable Speech Enhancement with Dynamic Channel Pruning 79–86, Springer International Publishing, 2020

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:50:33.176717Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 41464957-a3aa-4a57-950d-ead9d57a6126 · outbound

This paper cites Resource-Efficient Speech Quality Prediction through Quantization Aware Training and Binary Activation Maps.

Scalable Speech Enhancement with Dynamic Channel Pruning Resource-Efficient Speech Quality Prediction through Quantization Aware Training and Binary Activation Maps

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-11T05:50:33.012064Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1178a370-2620-4822-8680-13b95dbde972 · outbound

This paper cites The Concrete Distribution: A Continuous Relaxation of Discrete Random Variables.

Scalable Speech Enhancement with Dynamic Channel Pruning The Concrete Distribution: A Continuous Relaxation of Discrete Random Variables

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-11T05:50:33.014849Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e99db393-4a47-4582-930c-6a47075523e6 · outbound

This paper cites Investigating RNN-based speech enhance- ment methods for noise-robust Text-to-Speech,.

Scalable Speech Enhancement with Dynamic Channel Pruning Investigating RNN-based speech enhance- ment methods for noise-robust Text-to-Speech,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:50:33.169189Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation af488b59-48fd-4250-b2aa-a3ae64126b2e · outbound

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

Scalable Speech Enhancement with Dynamic Channel Pruning Per- ceptual evaluation of speech quality (PESQ)-a new method for speech quality assessment of telephone networks and codecs,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:50:33.160729Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 4f5eddc5-958c-4de7-bafe-c119854ac3b1 · outbound

This paper cites SDR - half-baked or well done?.

Scalable Speech Enhancement with Dynamic Channel Pruning SDR - half-baked or well done?

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-11T05:50:33.022884Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 2e53305b-00ec-49d8-a861-5dc4f3965fd2 · inbound