Paper Citation Record · LEDGER

Evaluating the Effectiveness of Pre-Trained Audio Embeddings for Classification of Parkinson's Disease Speech Data

As of 8 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 0 inbound Pith citation observations for arXiv:2506.02078.

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

pith.paper-citation-record.v1
2506.02078 v1

Coverage vector

measured 35 of 35 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:44:14.476908Z

measured 35 of 35 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+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

35 of 35 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 48d19d10-b350-4f2f-8002-d71ac5ea68d9 · outbound

This paper cites an unresolved cited work.

Evaluating the Effectiveness of Pre-Trained Audio Embeddings for Classification of Parkinson's Disease Speech Data Unresolved cited work

Reference 1

Resolution: unresolved; raw_fallback, observed 2026-08-07T11:44:17.362460Z

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Observation fe1f8312-cefe-489a-8a42-6921846b27f5 · outbound

This paper cites pa -ta-ka.

Evaluating the Effectiveness of Pre-Trained Audio Embeddings for Classification of Parkinson's Disease Speech Data pa -ta-ka

Reference 2

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Observation 4fc8b263-9b28-4388-803d-72f3e0b11754 · outbound

This paper cites Models Performance To answer RQ1, we compared the performances of all three embedding model (OL3, VGG, W2V2) and classifier (SVM, KNN, ERT) combinations on both DDK and LR data.

Evaluating the Effectiveness of Pre-Trained Audio Embeddings for Classification of Parkinson's Disease Speech Data Models Performance To answer RQ1, we compared the performances of all three embedding model (OL3, VGG, W2V2) and classifier (SVM, KNN, ERT) combinations on both DDK and LR data

Reference 3

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Observation 56a5abdc-6a74-4e0f-9d23-ceb9028a6694 · outbound

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Evaluating the Effectiveness of Pre-Trained Audio Embeddings for Classification of Parkinson's Disease Speech Data Unresolved cited work

Reference 4

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Observation 870c331e-b0b3-4350-8e5d-6a9462ee6ffa · outbound

This paper cites The authors of this work would also like to thank Prof.

Evaluating the Effectiveness of Pre-Trained Audio Embeddings for Classification of Parkinson's Disease Speech Data The authors of this work would also like to thank Prof

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:44:17.263898Z

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Observation 1f69ac56-993a-4a72-a704-cacad10269e4 · outbound

This paper cites Computerized analysis of speech and voice for parkinson’s disease: A systematic review,.

Evaluating the Effectiveness of Pre-Trained Audio Embeddings for Classification of Parkinson's Disease Speech Data Computerized analysis of speech and voice for parkinson’s disease: A systematic review,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:44:17.193444Z

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Observation 45d49b80-1f64-4664-a622-002bafe57826 · outbound

This paper cites Innovative Speech - Based Deep Learning Approaches for Parkinson’s Disease Classification: A Systematic Review,.

Evaluating the Effectiveness of Pre-Trained Audio Embeddings for Classification of Parkinson's Disease Speech Data Innovative Speech - Based Deep Learning Approaches for Parkinson’s Disease Classification: A Systematic Review,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:44:17.136797Z

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Observation c26dbbd6-f3e2-41c0-8759-04e2eec67b9e · outbound

This paper cites Multilingual evalua- tion of interpretable biomarkers to represent language and speech patterns in parkinson’s disease,.

Evaluating the Effectiveness of Pre-Trained Audio Embeddings for Classification of Parkinson's Disease Speech Data Multilingual evalua- tion of interpretable biomarkers to represent language and speech patterns in parkinson’s disease,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:44:17.084252Z

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Observation a84c95b8-d2ec-40c6-9c26-2b5ee92c9d89 · outbound

This paper cites Applied machine learning techniques to diagnose voice-affecting conditions and disorders: Systematic literature review,.

Evaluating the Effectiveness of Pre-Trained Audio Embeddings for Classification of Parkinson's Disease Speech Data Applied machine learning techniques to diagnose voice-affecting conditions and disorders: Systematic literature review,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:44:17.042851Z

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Observation c03a283d-3727-4974-9582-21c72245af41 · outbound

This paper cites Clinical diagnostic accuracy of parkin- son’s disease: Where do we stand?.

Evaluating the Effectiveness of Pre-Trained Audio Embeddings for Classification of Parkinson's Disease Speech Data Clinical diagnostic accuracy of parkin- son’s disease: Where do we stand?

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:44:17.007288Z

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Observation ecb5104a-281b-492e-9d9e-422b2d7da9cc · outbound

This paper cites Deep acoustic embeddings for identifying Parkinsonian Speech,.

Evaluating the Effectiveness of Pre-Trained Audio Embeddings for Classification of Parkinson's Disease Speech Data Deep acoustic embeddings for identifying Parkinsonian Speech,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:44:16.971909Z

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Observation c1ae487f-7c7f-4c63-a6e8-a9d7b838bb5e · outbound

This paper cites Multi- class voice disorder classification using OpenL3 -SVM,.

Evaluating the Effectiveness of Pre-Trained Audio Embeddings for Classification of Parkinson's Disease Speech Data Multi- class voice disorder classification using OpenL3 -SVM,

Reference 12

Resolution: verified exact; doi, observed 2026-08-07T11:44:14.572235Z

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Observation 00858117-d567-43c9-a2e4-e91c3eda673a · outbound

This paper cites Poster: Vggish embeddings based au- dio classifiers to improve parkinson’s disease diagnosis,.

Evaluating the Effectiveness of Pre-Trained Audio Embeddings for Classification of Parkinson's Disease Speech Data Poster: Vggish embeddings based au- dio classifiers to improve parkinson’s disease diagnosis,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:44:16.917324Z

Source-reported events for the cited work

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Observation 0c23579e-f0e0-4ccd-97fe-d5bf9f207f25 · outbound

This paper cites Interpretable speech features vs. dnn embeddings: What to use in the automatic assessment of parkinson’s disease in multi-lingual scenarios,.

Evaluating the Effectiveness of Pre-Trained Audio Embeddings for Classification of Parkinson's Disease Speech Data Interpretable speech features vs. dnn embeddings: What to use in the automatic assessment of parkinson’s disease in multi-lingual scenarios,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:44:16.874500Z

Source-reported events for the cited work

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Observation 54cf2eaa-4fc8-4eb8-85c0-a97484897673 · outbound

This paper cites Evaluating the Per- formance of wav2vec Embedding for Parkinson’s Disease Detec- tion,.

Evaluating the Effectiveness of Pre-Trained Audio Embeddings for Classification of Parkinson's Disease Speech Data Evaluating the Per- formance of wav2vec Embedding for Parkinson’s Disease Detec- tion,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:44:16.824587Z

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Observation 4b244cc1-a09c-4b63-8189-61597e790866 · outbound

This paper cites Machine learning approaches to identify parkinson’s disease using voice signal features,.

Evaluating the Effectiveness of Pre-Trained Audio Embeddings for Classification of Parkinson's Disease Speech Data Machine learning approaches to identify parkinson’s disease using voice signal features,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:44:16.791272Z

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Observation ddec7118-ebd6-4a32-aae1-5101019d3995 · outbound

This paper cites Gender -Related Pat - terns of Dysprosody in Parkinson Disease and Correlation Be - tween Speech Variables and Motor Symptoms,.

Evaluating the Effectiveness of Pre-Trained Audio Embeddings for Classification of Parkinson's Disease Speech Data Gender -Related Pat - terns of Dysprosody in Parkinson Disease and Correlation Be - tween Speech Variables and Motor Symptoms,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:44:16.745613Z

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Observation 7e4fc4a8-33d2-4ff1-89b9-0f5ec5407118 · outbound

This paper cites Speech as a biomarker for disease detection,.

Evaluating the Effectiveness of Pre-Trained Audio Embeddings for Classification of Parkinson's Disease Speech Data Speech as a biomarker for disease detection,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:44:16.716552Z

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Observation bbdcd065-fcb1-4ff9-b2be-fa97f81c8698 · outbound

This paper cites Parkinson’s disease and parkinsonism in a longitudinal study: two-fold higher incidence in men,.

Evaluating the Effectiveness of Pre-Trained Audio Embeddings for Classification of Parkinson's Disease Speech Data Parkinson’s disease and parkinsonism in a longitudinal study: two-fold higher incidence in men,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:44:16.671595Z

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Observation ed7eea13-9e41-44d9-bb7f-4cad9a841144 · outbound

This paper cites Gender differences in parkinson’s disease,.

Evaluating the Effectiveness of Pre-Trained Audio Embeddings for Classification of Parkinson's Disease Speech Data Gender differences in parkinson’s disease,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:44:16.631034Z

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Observation af7802ce-af5d-4bbc-8b0e-645e7bbd4ec0 · outbound

This paper cites X-vectors: New quantitative biomarkers for early parkin - son’s disease detection from speech,.

Evaluating the Effectiveness of Pre-Trained Audio Embeddings for Classification of Parkinson's Disease Speech Data X-vectors: New quantitative biomarkers for early parkin - son’s disease detection from speech,

Reference 21

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Observation 22a0afd3-d131-466b-81d1-5edc60711809 · outbound

This paper cites Gender differences in parkinson’s disease: clinical characteristics and cognition,.

Evaluating the Effectiveness of Pre-Trained Audio Embeddings for Classification of Parkinson's Disease Speech Data Gender differences in parkinson’s disease: clinical characteristics and cognition,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:44:16.548405Z

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Observation 6d7235ee-438d-4226-9571-16e245a7a8f4 · outbound

This paper cites Analysis of voice as an assisting tool for detection of parkinson’s disease and its subse - quent clinical interpretation,.

Evaluating the Effectiveness of Pre-Trained Audio Embeddings for Classification of Parkinson's Disease Speech Data Analysis of voice as an assisting tool for detection of parkinson’s disease and its subse - quent clinical interpretation,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:44:16.504195Z

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Observation 7a9559df-883c-4e43-88c3-4318feaa7d66 · outbound

This paper cites NeuroVoz: a Castillian Spanish corpus of parkinsonian speech,.

Evaluating the Effectiveness of Pre-Trained Audio Embeddings for Classification of Parkinson's Disease Speech Data NeuroVoz: a Castillian Spanish corpus of parkinsonian speech,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:44:16.468474Z

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Observation e7736992-f3d2-4f4c-b052-5e3cbd5c89c5 · outbound

This paper cites On open -set classification with l3 -net embed- dings for machine listening applications,.

Evaluating the Effectiveness of Pre-Trained Audio Embeddings for Classification of Parkinson's Disease Speech Data On open -set classification with l3 -net embed- dings for machine listening applications,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:44:16.432850Z

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Observation 52ffc4c2-bd79-4842-aa52-f3b873f39142 · outbound

This paper cites Audio - based deep learing frameworks for detecting covid-19,.

Evaluating the Effectiveness of Pre-Trained Audio Embeddings for Classification of Parkinson's Disease Speech Data Audio - based deep learing frameworks for detecting covid-19,

Reference 26

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Observation 312c9a85-7b88-4d09-8c14-f8afa47a0dbb · outbound

This paper cites Speech emotion recognition based on two-stream deep learning model using korean audio information,.

Evaluating the Effectiveness of Pre-Trained Audio Embeddings for Classification of Parkinson's Disease Speech Data Speech emotion recognition based on two-stream deep learning model using korean audio information,

Reference 27

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Observation 2e7f6a71-7bd1-4204-8e3e-281bbae58e68 · outbound

This paper cites How robust are audio embeddings for polyphonic sound event tagging?.

Evaluating the Effectiveness of Pre-Trained Audio Embeddings for Classification of Parkinson's Disease Speech Data How robust are audio embeddings for polyphonic sound event tagging?

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:44:15.059446Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation a46746ff-cb8e-4792-98b3-a581db262b67 · outbound

This paper cites MLS: A Large-Scale Multilingual Dataset for Speech Research,.

Evaluating the Effectiveness of Pre-Trained Audio Embeddings for Classification of Parkinson's Disease Speech Data MLS: A Large-Scale Multilingual Dataset for Speech Research,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:44:15.028997Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation eb01f318-fbe7-49d0-870d-17ec8a4a8dc7 · outbound

This paper cites Common voice: A massively-multilingual speech corpus,.

Evaluating the Effectiveness of Pre-Trained Audio Embeddings for Classification of Parkinson's Disease Speech Data Common voice: A massively-multilingual speech corpus,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:44:14.974732Z

Source-reported events for the cited work

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Observation 9153b6c1-b391-45c9-a29c-35102c14d91f · outbound

This paper cites Speech recog- nition and keyword spotting for low -resource languages: Babel project research at cued,.

Evaluating the Effectiveness of Pre-Trained Audio Embeddings for Classification of Parkinson's Disease Speech Data Speech recog- nition and keyword spotting for low -resource languages: Babel project research at cued,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:44:14.932385Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 5ba54b0a-a897-4c81-bb42-96cc0dda37f9 · outbound

This paper cites Analyz - ing the potential of pre-trained embeddings for audio classifica - tion tasks,.

Evaluating the Effectiveness of Pre-Trained Audio Embeddings for Classification of Parkinson's Disease Speech Data Analyz - ing the potential of pre-trained embeddings for audio classifica - tion tasks,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:44:14.890603Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 5ca42d36-5ded-404a-80f2-4119115a7f46 · outbound

This paper cites Pro - gression of voice and speech impairment in the course of parkin- son’s disease: A longitudinal study,.

Evaluating the Effectiveness of Pre-Trained Audio Embeddings for Classification of Parkinson's Disease Speech Data Pro - gression of voice and speech impairment in the course of parkin- son’s disease: A longitudinal study,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:44:14.855001Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 1f47ac1b-5110-44dc-ae7a-ff019364c899 · outbound

This paper cites Parkinson disease prediction using intrinsic mode function based features from speech signal,.

Evaluating the Effectiveness of Pre-Trained Audio Embeddings for Classification of Parkinson's Disease Speech Data Parkinson disease prediction using intrinsic mode function based features from speech signal,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:44:14.810323Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation d2eeb5c9-8e05-448d-a665-3eb7c0c9bde0 · outbound

This paper cites Automatic detection of laryngeal pathologies in records of sustained vowels by means of mel-frequency cepstral coefficient parameters and differentiation of patients by sex,.

Evaluating the Effectiveness of Pre-Trained Audio Embeddings for Classification of Parkinson's Disease Speech Data Automatic detection of laryngeal pathologies in records of sustained vowels by means of mel-frequency cepstral coefficient parameters and differentiation of patients by sex,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:44:14.774105Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Pith citing papers

No inbound Pith citation observations are available.