Paper Citation Record · LEDGER

Sub-Spectrogram Segmentation for Environmental Sound Classification via Convolutional Recurrent Neural Network and Score Level Fusion

As of 16 August 2026, this Paper Citation Record lists 24 of 24 outbound references and 0 inbound Pith citation observations for arXiv:1908.05863.

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

pith.paper-citation-record.v1
1908.05863 v1

Coverage vector

measured 24 of 24 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T13:06:01.854513Z

measured 24 of 24 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+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

24 of 24 outbound references displayed

verified exact1
verified fuzzy18
unresolved5
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e77d94cc-c452-420a-99f5-ba40b441f399 · outbound

This paper cites Acoustic scene classiﬁcation: Classifying environments from the sounds they produce,.

Sub-Spectrogram Segmentation for Environmental Sound Classification via Convolutional Recurrent Neural Network and Score Level Fusion Acoustic scene classiﬁcation: Classifying environments from the sounds they produce,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:06:02.251029Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 527ae2ca-5cb7-400c-a0ec-ed6bbf687003 · outbound

This paper cites Structure and function of auditory cortex: music and speech,.

Sub-Spectrogram Segmentation for Environmental Sound Classification via Convolutional Recurrent Neural Network and Score Level Fusion Structure and function of auditory cortex: music and speech,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:06:02.235923Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation cbf9f569-6a5d-4870-8075-d7eb612a39ac · outbound

This paper cites Environmental sound recognition: A survey,.

Sub-Spectrogram Segmentation for Environmental Sound Classification via Convolutional Recurrent Neural Network and Score Level Fusion Environmental sound recognition: A survey,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:06:02.220918Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation a7d7d03d-9332-463d-b480-885315db216a · outbound

This paper cites Environmental sound recog- nition with time–frequency audio features,.

Sub-Spectrogram Segmentation for Environmental Sound Classification via Convolutional Recurrent Neural Network and Score Level Fusion Environmental sound recog- nition with time–frequency audio features,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:06:02.205637Z

Source-reported events for the cited work

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Observation 88e7b142-5b5b-4aba-850d-66fe38ff1089 · outbound

This paper cites Comparison of techniques for environmental sound recognition,.

Sub-Spectrogram Segmentation for Environmental Sound Classification via Convolutional Recurrent Neural Network and Score Level Fusion Comparison of techniques for environmental sound recognition,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:06:02.190963Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation a8f85a81-6964-4df2-a54e-2c83c981cdbc · outbound

This paper cites Short-time energy, magnitude, zero crossing rate and autocorrelation measurement for discriminating voiced and unvoiced segments of speech signals,.

Sub-Spectrogram Segmentation for Environmental Sound Classification via Convolutional Recurrent Neural Network and Score Level Fusion Short-time energy, magnitude, zero crossing rate and autocorrelation measurement for discriminating voiced and unvoiced segments of speech signals,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:06:02.175086Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation ace900a7-b3c9-45f1-9659-638529ecbfe5 · outbound

This paper cites Sound event recognition in unstructured environments us- ing spectrogram image processing,.

Sub-Spectrogram Segmentation for Environmental Sound Classification via Convolutional Recurrent Neural Network and Score Level Fusion Sound event recognition in unstructured environments us- ing spectrogram image processing,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:06:02.158227Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 4093229d-ecf0-403b-84a7-ca5e6262afa0 · outbound

This paper cites an unresolved cited work.

Sub-Spectrogram Segmentation for Environmental Sound Classification via Convolutional Recurrent Neural Network and Score Level Fusion Unresolved cited work

Reference 8

Resolution: unresolved; raw_fallback, observed 2026-08-14T13:06:02.142988Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation c7f28b1b-23a5-4058-90ce-94ab92345de7 · outbound

This paper cites Environmental sound classiﬁcation with convolutional neural networks,.

Sub-Spectrogram Segmentation for Environmental Sound Classification via Convolutional Recurrent Neural Network and Score Level Fusion Environmental sound classiﬁcation with convolutional neural networks,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:06:02.127216Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 10b73743-edce-424c-a8dd-0af6f8f1455f · outbound

This paper cites A fuzzy k-nearest neighbor algorithm,.

Sub-Spectrogram Segmentation for Environmental Sound Classification via Convolutional Recurrent Neural Network and Score Level Fusion A fuzzy k-nearest neighbor algorithm,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:06:02.111673Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 2aa7749a-dd32-43ee-81d7-2bbfccff9104 · outbound

This paper cites Scholkopf and A.

Sub-Spectrogram Segmentation for Environmental Sound Classification via Convolutional Recurrent Neural Network and Score Level Fusion Scholkopf and A

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:06:02.095346Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 6d4cd928-f636-414c-8e05-bd033714f33f · outbound

This paper cites Random forests,.

Sub-Spectrogram Segmentation for Environmental Sound Classification via Convolutional Recurrent Neural Network and Score Level Fusion Random forests,

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-14T13:06:01.797629Z

Source-reported events for the cited work

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Observation 32260ceb-258f-47b7-813f-d0b34a3da770 · outbound

This paper cites Audio based event detection for multimedia surveillance,.

Sub-Spectrogram Segmentation for Environmental Sound Classification via Convolutional Recurrent Neural Network and Score Level Fusion Audio based event detection for multimedia surveillance,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:06:02.071375Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation d1456f2c-a2e5-44e7-8d5b-303eadbf3d7c · outbound

This paper cites Feature learning with matrix factorization applied to acoustic scene classiﬁcation,.

Sub-Spectrogram Segmentation for Environmental Sound Classification via Convolutional Recurrent Neural Network and Score Level Fusion Feature learning with matrix factorization applied to acoustic scene classiﬁcation,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:06:02.056527Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation f4709a9d-21e4-404a-81ce-3dbe20c29bc2 · outbound

This paper cites Learning from between-class examples for deep sound recognition,.

Sub-Spectrogram Segmentation for Environmental Sound Classification via Convolutional Recurrent Neural Network and Score Level Fusion Learning from between-class examples for deep sound recognition,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:06:02.040976Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 809ccf9d-162d-49df-a6e3-429115520d42 · outbound

This paper cites Robust sound event classiﬁcation using deep neural networks,.

Sub-Spectrogram Segmentation for Environmental Sound Classification via Convolutional Recurrent Neural Network and Score Level Fusion Robust sound event classiﬁcation using deep neural networks,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:06:02.024402Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 969c9a4c-386e-4434-9b59-315cc00d3471 · outbound

This paper cites Classifying environmental sounds using image recognition networks,.

Sub-Spectrogram Segmentation for Environmental Sound Classification via Convolutional Recurrent Neural Network and Score Level Fusion Classifying environmental sounds using image recognition networks,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:06:02.007375Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 38918e62-534e-4ec4-81ea-3248b84f62c5 · outbound

This paper cites Dilated convolution neural network with leakyrelu for environmental sound classiﬁcation,.

Sub-Spectrogram Segmentation for Environmental Sound Classification via Convolutional Recurrent Neural Network and Score Level Fusion Dilated convolution neural network with leakyrelu for environmental sound classiﬁcation,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:06:01.991992Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 3ca5bd18-fe60-4ec0-9b78-a966e56ca514 · outbound

This paper cites SubSpectralNet - Using Sub-Spectrogram based Convolutional Neural Networks for Acoustic Scene Classification.

Sub-Spectrogram Segmentation for Environmental Sound Classification via Convolutional Recurrent Neural Network and Score Level Fusion SubSpectralNet - Using Sub-Spectrogram based Convolutional Neural Networks for Acoustic Scene Classification

Reference 19

Resolution: verified exact; local_arxiv, observed 2026-08-14T13:06:01.943960Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation af8d57fa-a811-4f10-bd7e-e2cc5036acf1 · outbound

This paper cites Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling.

Sub-Spectrogram Segmentation for Environmental Sound Classification via Convolutional Recurrent Neural Network and Score Level Fusion Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-14T13:06:01.836119Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d93264ad-e7f0-4dae-bc10-821bf852ba21 · outbound

This paper cites Deep convolutional neural network with mixup for environmental sound classiﬁcation,.

Sub-Spectrogram Segmentation for Environmental Sound Classification via Convolutional Recurrent Neural Network and Score Level Fusion Deep convolutional neural network with mixup for environmental sound classiﬁcation,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:06:01.976183Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation b0354718-1161-4f6b-8a17-c72d857949c0 · outbound

This paper cites Voice Recognition Algorithms using Mel Frequency Cepstral Coefficient (MFCC) and Dynamic Time Warping (DTW) Techniques.

Sub-Spectrogram Segmentation for Environmental Sound Classification via Convolutional Recurrent Neural Network and Score Level Fusion Voice Recognition Algorithms using Mel Frequency Cepstral Coefficient (MFCC) and Dynamic Time Warping (DTW) Techniques

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-14T13:06:01.845527Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f5659884-23f9-49a3-b921-44f8d7ee2f6d · outbound

This paper cites Esc: Dataset for environmental sound classiﬁcation,.

Sub-Spectrogram Segmentation for Environmental Sound Classification via Convolutional Recurrent Neural Network and Score Level Fusion Esc: Dataset for environmental sound classiﬁcation,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:06:01.960642Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 5a96ddac-bb18-43ae-a7b2-e4c9b20da78e · outbound

This paper cites mixup: Beyond Empirical Risk Minimization.

Sub-Spectrogram Segmentation for Environmental Sound Classification via Convolutional Recurrent Neural Network and Score Level Fusion mixup: Beyond Empirical Risk Minimization

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-14T13:06:01.854513Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.