Paper Citation Record · LEDGER

Supervised Classifiers for Audio Impairments with Noisy Labels

As of 23 August 2026, this Paper Citation Record lists 23 of 23 outbound references and 0 inbound Pith citation observations for arXiv:1907.01742.

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

pith.paper-citation-record.v1
1907.01742 v1

Coverage vector

measured 23 of 23 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-25T10:07:45.531832Z

measured 23 of 23 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

23 of 23 outbound references displayed

verified exact6
verified fuzzy12
unresolved4
parse uncertain1
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e3b944c4-e4ec-4c92-bea0-8af1320f4c42 · outbound

This paper cites The speech signal perceived by the huma n is degraded due to various environmental noises, bad room acoustics and distortions introduced in the communication systems.

Supervised Classifiers for Audio Impairments with Noisy Labels The speech signal perceived by the huma n is degraded due to various environmental noises, bad room acoustics and distortions introduced in the communication systems

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T10:10:39.156286Z

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 2beccfed-a488-4f42-ba0d-443b764d973e · outbound

This paper cites The 4 impairment classes are: i) Background noise, ii) Reverberation, iii) Speech distortion and iv) Low volume.

Supervised Classifiers for Audio Impairments with Noisy Labels The 4 impairment classes are: i) Background noise, ii) Reverberation, iii) Speech distortion and iv) Low volume

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T10:10:39.142911Z

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 2a05d48b-22cc-48c5-be1d-4b7914fa5712 · outbound

This paper cites Hit application for online subjective evaluation Once the audio dataset is synthesized for different impairments, the next step is to label the clips.

Supervised Classifiers for Audio Impairments with Noisy Labels Hit application for online subjective evaluation Once the audio dataset is synthesized for different impairments, the next step is to label the clips

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T10:10:39.139755Z

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 01a099f1-0f49-44a3-935d-f6065dc4c2f0 · outbound

This paper cites Engineered audio features with dense network In the first approach, we extract 18 engineered signal processing features from the audio signal.

Supervised Classifiers for Audio Impairments with Noisy Labels Engineered audio features with dense network In the first approach, we extract 18 engineered signal processing features from the audio signal

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T10:10:39.136305Z

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 a4d92a3a-80fa-4389-a322-29515c3ac3a5 · outbound

This paper cites an unresolved cited work.

Supervised Classifiers for Audio Impairments with Noisy Labels Unresolved cited work

Reference 5

Resolution: unresolved; raw_fallback, observed 2026-05-25T10:10:39.132702Z

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 04743d0f-b8bc-48c9-b36d-30d1d98c9ac2 · outbound

This paper cites an unresolved cited work.

Supervised Classifiers for Audio Impairments with Noisy Labels Unresolved cited work

Reference 6

Resolution: unresolved; raw_fallback, observed 2026-05-25T10:10:39.129616Z

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 6a3bd19d-3b21-4240-858c-be51f330d8c1 · outbound

This paper cites Recommendation P.800: Methods for subjective determination of transmission quality.

Supervised Classifiers for Audio Impairments with Noisy Labels Recommendation P.800: Methods for subjective determination of transmission quality

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T10:10:39.126038Z

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 0b096a2c-28f9-4e44-b6da-b861d89f9d09 · outbound

This paper cites an unresolved cited work.

Supervised Classifiers for Audio Impairments with Noisy Labels Unresolved cited work

Reference 8

Resolution: unresolved; raw_fallback, observed 2026-05-25T10:10:39.122416Z

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 a8bec0cc-19bc-4969-a963-9f6a9a97ed06 · outbound

This paper cites Perceptual objective listening quality assessment (POLQA), the third generation ITU -T standard for end-to-end speech quality measurement part I —Temporal alignment.

Supervised Classifiers for Audio Impairments with Noisy Labels Perceptual objective listening quality assessment (POLQA), the third generation ITU -T standard for end-to-end speech quality measurement part I —Temporal alignment

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T10:10:39.119153Z

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 8a60e3cf-075d-44d4-8f40-6cd642c472b1 · outbound

This paper cites Non -intrusive Speech Quality Assessment Using Neural Networks.

Supervised Classifiers for Audio Impairments with Noisy Labels Non -intrusive Speech Quality Assessment Using Neural Networks

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-05-25T10:10:37.304584Z

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 5f859510-54f1-4cd4-9bf1-fddfe5cb307c · outbound

This paper cites an unresolved cited work.

Supervised Classifiers for Audio Impairments with Noisy Labels Unresolved cited work

Reference 11

Resolution: parse uncertain; raw_fallback, observed 2026-05-25T10:10:39.115541Z

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 59bd661e-99c3-466f-ba65-15180c4401c9 · outbound

This paper cites Learning with noisy labels.

Supervised Classifiers for Audio Impairments with Noisy Labels Learning with noisy labels

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T10:10:39.112515Z

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 29288879-96e1-4e0d-9592-7122247cf8fe · outbound

This paper cites Learning Deep Networks from Noisy Labels with Dropout Regularization.

Supervised Classifiers for Audio Impairments with Noisy Labels Learning Deep Networks from Noisy Labels with Dropout Regularization

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T10:10:39.109423Z

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 e886a413-475e-496b-9e69-5f696f9e98ef · outbound

This paper cites Training Convolutional Networks with Noisy Labels.

Supervised Classifiers for Audio Impairments with Noisy Labels Training Convolutional Networks with Noisy Labels

Reference 14

Resolution: verified exact; local_arxiv, observed 2026-05-25T10:10:37.662525Z

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 3d8977e1-1893-4e4b-a5ff-553404fd189e · outbound

This paper cites Learning Sound Event Classifiers from Web Audio with Noisy Labels.

Supervised Classifiers for Audio Impairments with Noisy Labels Learning Sound Event Classifiers from Web Audio with Noisy Labels

Reference 15

Resolution: verified exact; local_arxiv, observed 2026-05-25T10:10:37.656530Z

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 f50a2ef3-8380-490d-afdb-14028dd50075 · outbound

This paper cites General-purpose audio tagging from noisy labels using convolutional neural networks.

Supervised Classifiers for Audio Impairments with Noisy Labels General-purpose audio tagging from noisy labels using convolutional neural networks

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T10:10:39.152239Z

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 62c1a41e-e43a-4e6c-9372-fae53c1c45f2 · outbound

This paper cites A Closer Look at Weak Label Learning for Audio Events.

Supervised Classifiers for Audio Impairments with Noisy Labels A Closer Look at Weak Label Learning for Audio Events

Reference 17

Resolution: verified exact; local_arxiv, observed 2026-05-25T10:10:37.644471Z

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 fda30153-b326-4502-9ca8-af3f63cc1171 · outbound

This paper cites an unresolved cited work.

Supervised Classifiers for Audio Impairments with Noisy Labels Unresolved cited work

Reference 18

Resolution: unresolved; raw_fallback, observed 2026-05-25T10:10:39.149118Z

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 2d0fc799-05a5-4ffc-b9b3-96fa10514cff · outbound

This paper cites Training deep neural networks on noisy labels with bootstrapping.

Supervised Classifiers for Audio Impairments with Noisy Labels Training deep neural networks on noisy labels with bootstrapping

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T10:10:39.146068Z

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 f6137f87-1ada-4f25-9e97-8aaecbea83e2 · outbound

This paper cites Joint optimization framework for learning with noisy labels.

Supervised Classifiers for Audio Impairments with Noisy Labels Joint optimization framework for learning with noisy labels

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T10:10:39.101662Z

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 fdbba855-3f7a-43bf-b777-7edfa5ad79f0 · outbound

This paper cites Generalized cross entropy loss for training deep neur al networks with noisy labels.

Supervised Classifiers for Audio Impairments with Noisy Labels Generalized cross entropy loss for training deep neur al networks with noisy labels

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T10:10:39.098218Z

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 701c0ff5-d87f-4937-98ec-489f55c6b3db · outbound

This paper cites Deep Learning is Robust to Massive Label Noise.

Supervised Classifiers for Audio Impairments with Noisy Labels Deep Learning is Robust to Massive Label Noise

Reference 22

Resolution: verified exact; local_arxiv, observed 2026-05-25T10:10:37.650854Z

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 5eb553c7-16b4-4174-afcf-6046d526e37e · outbound

This paper cites Low-Complexity, Nonintrusive Speech Quality Assessment.

Supervised Classifiers for Audio Impairments with Noisy Labels Low-Complexity, Nonintrusive Speech Quality Assessment

Reference 23

Resolution: verified exact; arxiv_id, observed 2026-05-25T10:10:37.298600Z

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.

Pith citing papers

No inbound Pith citation observations are available.