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Paper Citation Record · LEDGER

Towards detecting the pathological subharmonic voicing with fully convolutional neural networks

As of 20 August 2026, this Paper Citation Record lists 48 of 48 outbound references and 0 inbound Pith citation observations for arXiv:2501.09159.

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

pith.paper-citation-record.v1
2501.09159 v1

Coverage vector

measured 48 of 48 reference resolution

Typed states for the displayed outbound observations.

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measured 48 of 48 standing notices

One-hop event checks from named stored sources.

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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

48 of 48 outbound references displayed

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External citation measurements

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Outbound references

Observation ea5f76b2-3ec6-4ae5-a43e-69d02dcebbdf · outbound

This paper cites Microphone and electroglottographic data from dyspho- nic patients: Type 1, 2 and 3 signals,.

Towards detecting the pathological subharmonic voicing with fully convolutional neural networks Microphone and electroglottographic data from dyspho- nic patients: Type 1, 2 and 3 signals,

Reference 1

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Observation 1b2fdf37-f055-438a-aa83-3283af4b6fc3 · outbound

This paper cites Diplophonia reappraised,.

Towards detecting the pathological subharmonic voicing with fully convolutional neural networks Diplophonia reappraised,

Reference 2

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Observation 2b710bb3-d57c-42f4-ad57-ac31ccb03d2a · outbound

This paper cites [Spectrographic study of voice disorders: subharmonics],.

Towards detecting the pathological subharmonic voicing with fully convolutional neural networks [Spectrographic study of voice disorders: subharmonics],

Reference 3

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Observation f3bf9537-e349-4f26-a082-4bdaa4fce170 · outbound

This paper cites A study of subharmonics in connected speech material,.

Towards detecting the pathological subharmonic voicing with fully convolutional neural networks A study of subharmonics in connected speech material,

Reference 4

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Observation 050476cd-4afe-4406-9d27-0f86ec5a9807 · outbound

This paper cites Investigation of vocal bifurcations and voice patterns induced by asymmetry of pathological vocal folds,.

Towards detecting the pathological subharmonic voicing with fully convolutional neural networks Investigation of vocal bifurcations and voice patterns induced by asymmetry of pathological vocal folds,

Reference 5

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Observation 43c7f6d0-9d6f-4795-b6a6-e6b789d7678a · outbound

This paper cites On the nature of vocal fry,.

Towards detecting the pathological subharmonic voicing with fully convolutional neural networks On the nature of vocal fry,

Reference 6

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Observation 2448cafc-9635-4349-a3ba-4b4293f6ba78 · outbound

This paper cites Freddie Mercury—acoustic analysis of speaking fundamental frequency, vibrato, and subhar- monics,.

Towards detecting the pathological subharmonic voicing with fully convolutional neural networks Freddie Mercury—acoustic analysis of speaking fundamental frequency, vibrato, and subhar- monics,

Reference 7

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Observation e2d44195-81ac-41be-82c9-a274108a135c · outbound

This paper cites Acoustic characteristics of rough voice: Subharmonics,.

Towards detecting the pathological subharmonic voicing with fully convolutional neural networks Acoustic characteristics of rough voice: Subharmonics,

Reference 8

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Source-reported events for the cited work

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Observation 7b0362a8-dbe8-4676-9ed7-c16d52811658 · outbound

This paper cites Perception of pitch and roughness in vocal signals with subharmonics,.

Towards detecting the pathological subharmonic voicing with fully convolutional neural networks Perception of pitch and roughness in vocal signals with subharmonics,

Reference 9

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Source-reported events for the cited work

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Observation 0b795495-3388-48c7-b0fe-6f99a98bc053 · outbound

This paper cites Perceived pitch of synthesized voice with alternate cycles,.

Towards detecting the pathological subharmonic voicing with fully convolutional neural networks Perceived pitch of synthesized voice with alternate cycles,

Reference 10

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Source-reported events for the cited work

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Observation 675c6f80-f3bd-43bf-99b3-34acc964745b · outbound

This paper cites Perception and imitation of period-doubled phonation: Pitch and voice quality,.

Towards detecting the pathological subharmonic voicing with fully convolutional neural networks Perception and imitation of period-doubled phonation: Pitch and voice quality,

Reference 11

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Observation ae744c06-ef03-4444-a951-02e8c71dd62f · outbound

This paper cites Evaluation of machine-learning pitch estimation algorithms,.

Towards detecting the pathological subharmonic voicing with fully convolutional neural networks Evaluation of machine-learning pitch estimation algorithms,

Reference 12

Resolution
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Observation 98b4ca36-38e6-48d6-8d9e-ff3d8cd8ff48 · outbound

This paper cites Comparison of fundamental frequency estimators with subharmonic voice signals.

Towards detecting the pathological subharmonic voicing with fully convolutional neural networks Comparison of fundamental frequency estimators with subharmonic voice signals

Reference 13

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Observation b558ea7f-a995-42b1-9d91-51e94db103ae · outbound

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Towards detecting the pathological subharmonic voicing with fully convolutional neural networks Unresolved cited work

Reference 14

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Observation 47b5ca8e-df8c-4041-8b73-3a3c02b06d60 · outbound

This paper cites Multi-Dimensional V oice Program (MDVP) model 5105 software instruction manual,.

Towards detecting the pathological subharmonic voicing with fully convolutional neural networks Multi-Dimensional V oice Program (MDVP) model 5105 software instruction manual,

Reference 15

Resolution
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Source-reported events for the cited work

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Observation bad19548-8d0e-4315-aadf-414c01e9bdab · outbound

This paper cites Acoustic model and evaluation of patho- logical voice production,.

Towards detecting the pathological subharmonic voicing with fully convolutional neural networks Acoustic model and evaluation of patho- logical voice production,

Reference 16

Resolution
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Observation e1f02569-eb82-4437-b227-21e435933a21 · outbound

This paper cites A pitch determination algorithm based on subharmonic-to-harmonic ratio,.

Towards detecting the pathological subharmonic voicing with fully convolutional neural networks A pitch determination algorithm based on subharmonic-to-harmonic ratio,

Reference 17

Resolution
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Source-reported events for the cited work

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Observation fe8b4a04-6f0b-480d-915b-93171666df5d · outbound

This paper cites Acoustic tracking of pitch, modal, and subhar- monic vibrations of vocal folds in Parkinson’s Disease and Parkinsonism,.

Towards detecting the pathological subharmonic voicing with fully convolutional neural networks Acoustic tracking of pitch, modal, and subhar- monic vibrations of vocal folds in Parkinson’s Disease and Parkinsonism,

Reference 18

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Observation 526dcd74-aa17-479f-bed9-8c8fe42a8d41 · outbound

This paper cites Fundamental frequency tracking in diplophonic voices,.

Towards detecting the pathological subharmonic voicing with fully convolutional neural networks Fundamental frequency tracking in diplophonic voices,

Reference 19

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Source-reported events for the cited work

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Observation 08190007-6889-410c-818e-847537cc177c · outbound

This paper cites Tracking of mul- tiple fundamental frequencies in diplophonic voices,.

Towards detecting the pathological subharmonic voicing with fully convolutional neural networks Tracking of mul- tiple fundamental frequencies in diplophonic voices,

Reference 20

Resolution
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Source-reported events for the cited work

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Observation 21b4f179-af5f-4289-b14a-10c40f28b6f5 · outbound

This paper cites A two-stage cepstral analysis procedure for the classification of rough voices,.

Towards detecting the pathological subharmonic voicing with fully convolutional neural networks A two-stage cepstral analysis procedure for the classification of rough voices,

Reference 21

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Observation e99fa441-617e-44d0-97ca-8783a0fc870f · outbound

This paper cites Validation of subharmonics quantification using two-stage cepstral analysis,.

Towards detecting the pathological subharmonic voicing with fully convolutional neural networks Validation of subharmonics quantification using two-stage cepstral analysis,

Reference 22

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verified fuzzy
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Source-reported events for the cited work

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Observation 9194d237-3a6c-4fff-b041-2d904c4cd4f0 · outbound

This paper cites Fully-convolutional net- work for pitch estimation of speech signals,.

Towards detecting the pathological subharmonic voicing with fully convolutional neural networks Fully-convolutional net- work for pitch estimation of speech signals,

Reference 23

Resolution
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Observation 8e65706d-496f-4ca2-97d1-39398801ca1f · outbound

This paper cites Crepe: A convolutional representation for pitch estimation,.

Towards detecting the pathological subharmonic voicing with fully convolutional neural networks Crepe: A convolutional representation for pitch estimation,

Reference 24

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Observation 1ffd7146-a769-4307-87d2-de7a6c3a80ea · outbound

This paper cites Fully convo- lutional networks for semantic segmentation,.

Towards detecting the pathological subharmonic voicing with fully convolutional neural networks Fully convo- lutional networks for semantic segmentation,

Reference 25

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Observation 62903429-9abf-4252-927c-9a5e6908d8f9 · outbound

This paper cites Time series classifica- tion from scratch with deep neural networks: A strong baseline,.

Towards detecting the pathological subharmonic voicing with fully convolutional neural networks Time series classifica- tion from scratch with deep neural networks: A strong baseline,

Reference 26

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Observation 76add649-f347-4b83-a7e1-3acc251d2f76 · outbound

This paper cites Deep learning for time series classi- fication: A review,.

Towards detecting the pathological subharmonic voicing with fully convolutional neural networks Deep learning for time series classi- fication: A review,

Reference 27

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Source-reported events for the cited work

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Observation ed106425-6678-4205-8f4e-3ae793140dbc · outbound

This paper cites An analysis of the diplo- phonia phenomenon,.

Towards detecting the pathological subharmonic voicing with fully convolutional neural networks An analysis of the diplo- phonia phenomenon,

Reference 28

Resolution
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Source-reported events for the cited work

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Observation b4405aac-8b9b-472f-800f-f2a22f9e2b1c · outbound

This paper cites Performance evaluation of subharmonic- to-harmonic ratio (SHR) computation,.

Towards detecting the pathological subharmonic voicing with fully convolutional neural networks Performance evaluation of subharmonic- to-harmonic ratio (SHR) computation,

Reference 29

Resolution
verified fuzzy
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Source-reported events for the cited work

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Observation 13373793-7818-4a31-b294-373568b875da · outbound

This paper cites Parameterization of the glottal area, glottal flow, and vocal fold contact area,.

Towards detecting the pathological subharmonic voicing with fully convolutional neural networks Parameterization of the glottal area, glottal flow, and vocal fold contact area,

Reference 30

Resolution
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Source-reported events for the cited work

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Observation 383cc9e2-abab-4e86-a254-158a3eede401 · outbound

This paper cites A four-parameter model of the glottis and vocal fold contact area,.

Towards detecting the pathological subharmonic voicing with fully convolutional neural networks A four-parameter model of the glottis and vocal fold contact area,

Reference 31

Resolution
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Observation 03f7ffd1-e2ec-4cc0-aba0-0afac16e5115 · outbound

This paper cites Physiologically-Based Speech Simulation Us- ing an Enhanced Wave-Reflection Model of the V ocal Tract,.

Towards detecting the pathological subharmonic voicing with fully convolutional neural networks Physiologically-Based Speech Simulation Us- ing an Enhanced Wave-Reflection Model of the V ocal Tract,

Reference 32

Resolution
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Source-reported events for the cited work

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Observation e5626915-0cfd-4887-bf56-49951c8f52f0 · outbound

This paper cites Speech Synthesis with Reflection-Type Line Analog,.

Towards detecting the pathological subharmonic voicing with fully convolutional neural networks Speech Synthesis with Reflection-Type Line Analog,

Reference 33

Resolution
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Source-reported events for the cited work

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Observation b0907301-ffee-4ee5-8bec-9e2759eb0cda · outbound

This paper cites Relation of structural and vibratory kinematics of the vocal folds to two acoustic measures of breathy voice based on computational mod- eling,.

Towards detecting the pathological subharmonic voicing with fully convolutional neural networks Relation of structural and vibratory kinematics of the vocal folds to two acoustic measures of breathy voice based on computational mod- eling,

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:14:25.382282Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 3c98b5c9-4d76-448e-856b-c1ff03e387fd · outbound

This paper cites Relation of perceived breathiness to laryngeal kinematics and acoustic measures based on computational modeling,.

Towards detecting the pathological subharmonic voicing with fully convolutional neural networks Relation of perceived breathiness to laryngeal kinematics and acoustic measures based on computational modeling,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:14:25.362035Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-10T20:14:24.940643Z digest=sha256:baa0a93bbb2aa0120f782602df841ad684af90e81ac49147ba228df284b3e1ff

Observation b7efb19e-003e-4bb5-a1db-67cbea408fae · outbound

This paper cites Acoustic and perceptual effects of left–right laryn- geal asymmetries based on computational modeling,.

Towards detecting the pathological subharmonic voicing with fully convolutional neural networks Acoustic and perceptual effects of left–right laryn- geal asymmetries based on computational modeling,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:14:25.333568Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-10T20:14:24.946078Z digest=sha256:ae9c042edb35fe9359373eaf63a225a346e04d9f8a9d63dde6d2d9312241f2e7

Observation e8de4e69-df96-4ff5-8b33-7c1575ad378d · outbound

This paper cites Synthesis of voiced sounds from a two-mass model of the vocal cords,.

Towards detecting the pathological subharmonic voicing with fully convolutional neural networks Synthesis of voiced sounds from a two-mass model of the vocal cords,

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:14:25.312682Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-10T20:14:24.951208Z digest=sha256:59ecc9eebf51cab1a338faf3dc7a39fb0894478bb2f67a15655b3f584f2e8aaa

Observation 1782ce46-bcbf-425b-912c-7ecde33fbca2 · outbound

This paper cites The physics of small-amplitude oscillation of the vocal folds,.

Towards detecting the pathological subharmonic voicing with fully convolutional neural networks The physics of small-amplitude oscillation of the vocal folds,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:14:25.293436Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-10T20:14:24.956424Z digest=sha256:230be3d03a1dbcbffc0c97819804dd83fb772416459515c59c0f63f8424402d0

Observation 0d953d05-35aa-4862-ba9f-54d4f18a708b · outbound

This paper cites High-speed digital image analysis of vocal cord vibration in diplo- phonia,.

Towards detecting the pathological subharmonic voicing with fully convolutional neural networks High-speed digital image analysis of vocal cord vibration in diplo- phonia,

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:14:25.270336Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-10T20:14:24.961705Z digest=sha256:8a38099e4e6ac2acdfe3966ab0700fcb353d070bf69cdedb8999581802f2c786

Observation 9c100842-bf8d-41dc-a091-048eb124e87d · outbound

This paper cites The mechanisms of subharmonic tone generation in a synthetic larynx model,.

Towards detecting the pathological subharmonic voicing with fully convolutional neural networks The mechanisms of subharmonic tone generation in a synthetic larynx model,

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:14:25.251472Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-10T20:14:24.973405Z digest=sha256:71e2073b9aaac7f840774d2878a04de2522c2a3e7ead44fde93298d0f89d0d56

Observation 4c760d18-5122-4d92-a9c8-ed10bf7045eb · outbound

This paper cites Synthetic multi-line kymographic analysis: A spatiotem- poral data reduction technique for high-speed videoen- doscopy,.

Towards detecting the pathological subharmonic voicing with fully convolutional neural networks Synthetic multi-line kymographic analysis: A spatiotem- poral data reduction technique for high-speed videoen- doscopy,

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:14:25.233124Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-10T20:14:24.978642Z digest=sha256:933bf9b8d4fd0f860e9ec97832eb023f207bb0036e8457bf62aaf04abd7f75b1

Observation 7a7cdd50-a692-4697-a064-9893080b5f18 · outbound

This paper cites Irregular vocal- fold vibration—High-speed observation and modeling,.

Towards detecting the pathological subharmonic voicing with fully convolutional neural networks Irregular vocal- fold vibration—High-speed observation and modeling,

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:14:25.215907Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-10T20:14:24.983664Z digest=sha256:828d38f1c3d7c6cb8e211077445761f3d95161dd0591efd4171187c6baae4518

Observation e0330644-1e46-428e-a5bb-779d01e02c42 · outbound

This paper cites Spatio-temporal analysis of irregular vocal fold oscil- lations: Biphonation due to desynchronization of spatial modes,.

Towards detecting the pathological subharmonic voicing with fully convolutional neural networks Spatio-temporal analysis of irregular vocal fold oscil- lations: Biphonation due to desynchronization of spatial modes,

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:14:25.198727Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-10T20:14:24.988679Z digest=sha256:568168507ab2bba1ab1a7954316e62612b98574ebb156b42f570d8370948efff

Observation 68bad3d3-ddae-498a-bc1a-024d2d180e26 · outbound

This paper cites Regulating glottal airflow in phonation: Application of the maximum power transfer theorem to a low dimensional phonation model,.

Towards detecting the pathological subharmonic voicing with fully convolutional neural networks Regulating glottal airflow in phonation: Application of the maximum power transfer theorem to a low dimensional phonation model,

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:14:25.180756Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-10T20:14:24.994304Z digest=sha256:d05bf34f7ce5eeb79acbaef10304dc1f1632929fb47bf4d418c624942d3027dc

Observation af0f80a4-c05d-4833-9fd1-b300a4c24ec5 · outbound

This paper cites Analysis, synthesis, and perception of voice quality variations among female and male talkers,.

Towards detecting the pathological subharmonic voicing with fully convolutional neural networks Analysis, synthesis, and perception of voice quality variations among female and male talkers,

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:14:25.159989Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-10T20:14:24.999252Z digest=sha256:45ab997330c4f75b8a68a99cf29d216d639e730d74247a4324f5b333a432adc9

Observation 8e806f33-1428-48f6-9891-d454566a9bcb · outbound

This paper cites Glottal airflow and transglottal air pressure measurements for male and female speakers in soft, normal, and loud voice,.

Towards detecting the pathological subharmonic voicing with fully convolutional neural networks Glottal airflow and transglottal air pressure measurements for male and female speakers in soft, normal, and loud voice,

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:14:25.135544Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-10T20:14:25.004848Z digest=sha256:1917b1d7c0b8723c0e1805be0959e2358cebb20bf60dcb96011f6b15fa645cb3

Observation aac34f0e-166e-49ac-b116-8f63ecb8aa00 · outbound

This paper cites Adam: A Method for Stochastic Optimization,.

Towards detecting the pathological subharmonic voicing with fully convolutional neural networks Adam: A Method for Stochastic Optimization,

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:14:25.116079Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-10T20:14:25.010549Z digest=sha256:ec053e72bf788cdfeba2f24cd405fd97bad83b76039e2ad53d844a83695ed75b

Observation 0b9093a2-fa10-4c59-9c2e-2fab119b45e8 · outbound

This paper cites Disordered V oice Database and Program [Model 4337],.

Towards detecting the pathological subharmonic voicing with fully convolutional neural networks Disordered V oice Database and Program [Model 4337],

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:14:25.097724Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-10T20:14:25.016190Z digest=sha256:1386af937f3cffcc5811dd7f297dbc8b158e126dbe565d9894e599b65982863e

Pith citing papers

No inbound Pith citation observations are available.