Pith. sign in

Paper Citation Record · LEDGER

Revisiting Rule-Based Stuttering Detection: A Comprehensive Analysis of Interpretable Models for Clinical Applications

As of 8 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 0 inbound Pith citation observations for arXiv:2508.16681.

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

pith.paper-citation-record.v1
2508.16681 v1

Coverage vector

measured 38 of 38 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T17:52:40.580503Z

measured 38 of 38 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

38 of 38 outbound references displayed

  • verified exact5
  • verified fuzzy23
  • unresolved7
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch2

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 3889c060-78ce-4740-9c50-d939f8e0e646 · outbound

This paper cites The uclass archive of stuttered speech.

Revisiting Rule-Based Stuttering Detection: A Comprehensive Analysis of Interpretable Models for Clinical Applications The uclass archive of stuttered speech

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T17:52:45.836609Z

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.

source=pdf_text observed=2026-08-05T17:52:37.388267Z digest=sha256:ffb7ba15e0ff16eba6046048bdb2f74ff6d6f5ac17bccda3b763a7c013f0a5bb

Observation 4b2fc372-dee7-4b24-a84d-4975803075ed · outbound

This paper cites A systematic review of anxiety levels in people who stutter.

Revisiting Rule-Based Stuttering Detection: A Comprehensive Analysis of Interpretable Models for Clinical Applications A systematic review of anxiety levels in people who stutter

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T17:52:45.700675Z

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.

source=pdf_text observed=2026-08-05T17:52:37.440328Z digest=sha256:6a4def2b3f96aa63ae057b16d6407d2c156c988b24235df40c68b97f57ec2d46

Observation 116cb2ba-e03e-4329-9734-cd39ced3bf56 · outbound

This paper cites The relationship between mental health disorders and treatment outcomes among adults who stutter.

Revisiting Rule-Based Stuttering Detection: A Comprehensive Analysis of Interpretable Models for Clinical Applications The relationship between mental health disorders and treatment outcomes among adults who stutter

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T17:52:45.569960Z

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.

source=pdf_text observed=2026-08-05T17:52:37.548990Z digest=sha256:bd3f4774661f0892f044205767d59eb7f2a4f41b5a125e1b5c1ce1e695e7bba6

Observation d70f5b6d-7755-46ce-ab5a-05a3b7ce8e33 · outbound

This paper cites Localization of stuttering based on causal brain lesions.

Revisiting Rule-Based Stuttering Detection: A Comprehensive Analysis of Interpretable Models for Clinical Applications Localization of stuttering based on causal brain lesions

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T17:52:45.442203Z

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.

source=pdf_text observed=2026-08-05T17:52:37.613548Z digest=sha256:4209594646f3e8aa3c1557d3c02783d82d9edc7eb0d2d0e930864bf93a5d5e4f

Observation 21e4c56a-667f-4798-a20f-125ccd307f4d · outbound

This paper cites Acquired stuttering in parkinson’s disease.

Revisiting Rule-Based Stuttering Detection: A Comprehensive Analysis of Interpretable Models for Clinical Applications Acquired stuttering in parkinson’s disease

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T17:52:45.287207Z

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.

source=pdf_text observed=2026-08-05T17:52:37.719828Z digest=sha256:1a53b9909021d67c2a26b350e792500de2600b04c4040c6e36dc161af38f9104

Observation 68f1813a-8bc1-4d3f-9dd8-eb0900f299a5 · outbound

This paper cites Neurogenic stuttering: Etiology, symptomatology, and treatment.

Revisiting Rule-Based Stuttering Detection: A Comprehensive Analysis of Interpretable Models for Clinical Applications Neurogenic stuttering: Etiology, symptomatology, and treatment

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T17:52:45.168941Z

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.

source=pdf_text observed=2026-08-05T17:52:37.785201Z digest=sha256:e7ba0f16300feaa1f305a5f8ff65d8c37c8fc229f12ba99446aded7eb1a3d65b

Observation 3826db9d-a321-4101-b909-8b15cf954ef6 · outbound

This paper cites Neurogenic stuttering: a review of the literature.

Revisiting Rule-Based Stuttering Detection: A Comprehensive Analysis of Interpretable Models for Clinical Applications Neurogenic stuttering: a review of the literature

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T17:52:45.004754Z

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.

source=pdf_text observed=2026-08-05T17:52:37.892998Z digest=sha256:940c9c7e97ae2b1a9910d097c48a468516c29e8eb2b422ed61753ada6ea4a620

Observation 8fba09cf-79d6-4949-9767-8f5ce367c56f · outbound

This paper cites A crucial role for the cortico-striato-cortical loop in the pathogenesis of stroke-related neurogenic stuttering.

Revisiting Rule-Based Stuttering Detection: A Comprehensive Analysis of Interpretable Models for Clinical Applications A crucial role for the cortico-striato-cortical loop in the pathogenesis of stroke-related neurogenic stuttering

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T17:52:44.812693Z

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.

source=pdf_text observed=2026-08-05T17:52:37.958350Z digest=sha256:3479a3af51f81f678275758bbb306ba93d5dd4aac9c61e883f606b7a66efa126

Observation 1bf4f4f6-be35-49b2-b47f-d40ca1a1a777 · outbound

This paper cites A comprehensive review of stuttering therapy apps: Landscape analysis and quality assessment.

Revisiting Rule-Based Stuttering Detection: A Comprehensive Analysis of Interpretable Models for Clinical Applications A comprehensive review of stuttering therapy apps: Landscape analysis and quality assessment

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T17:52:44.668126Z

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.

source=pdf_text observed=2026-08-05T17:52:38.052760Z digest=sha256:2448717c4ed2ad7149e650759cf13a89b37075908901fa02e7885777d115ca9f

Observation 402cc9fc-6b69-4ef7-9b8a-9b125c8315e7 · outbound

This paper cites SEP-28k: A Dataset for Stuttering Event Detection From Podcasts With People Who Stutter.

Revisiting Rule-Based Stuttering Detection: A Comprehensive Analysis of Interpretable Models for Clinical Applications SEP-28k: A Dataset for Stuttering Event Detection From Podcasts With People Who Stutter

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-05T17:52:38.127476Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T17:52:38.127476Z digest=sha256:f6d826390278ce7434f01153eecd31446a8e52940a93c602c7f01203b371dc89

Observation 1947383d-dfd9-4e02-8515-b909861091a1 · outbound

This paper cites Machine learning for stuttering identi- fication: Review, challenges & future directions.

Revisiting Rule-Based Stuttering Detection: A Comprehensive Analysis of Interpretable Models for Clinical Applications Machine learning for stuttering identi- fication: Review, challenges & future directions

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T17:52:44.516313Z

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.

source=pdf_text observed=2026-08-05T17:52:38.196616Z digest=sha256:f483c68508591a42fd02a12081d7c1b534e9be5d2914d6372cbd008bd0d9db28

Observation 390b77d0-c5f3-4ad7-acd1-7e92a7bb94e3 · outbound

This paper cites Fluency bank: a new resource for fluency research and practice.

Revisiting Rule-Based Stuttering Detection: A Comprehensive Analysis of Interpretable Models for Clinical Applications Fluency bank: a new resource for fluency research and practice

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T17:52:44.358871Z

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.

source=pdf_text observed=2026-08-05T17:52:38.256470Z digest=sha256:696252a7ec29ac7a787c372f698ad46942808b3819a2bcf333d2a20dab182d42

Observation 91dbf146-682a-4b10-890d-30401f8139e7 · outbound

This paper cites Classification of stuttering–the compare challenge and beyond.

Revisiting Rule-Based Stuttering Detection: A Comprehensive Analysis of Interpretable Models for Clinical Applications Classification of stuttering–the compare challenge and beyond

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T17:52:44.197042Z

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.

source=pdf_text observed=2026-08-05T17:52:38.347885Z digest=sha256:ea220bd94c65984fd658cd493324e14c04a5a9d940f99c4bd9fd462145e598e4

Observation f996f442-6931-48b2-90f5-6a35aeddcf26 · outbound

This paper cites Ssdm: Scalable speech dysfluency modeling.

Revisiting Rule-Based Stuttering Detection: A Comprehensive Analysis of Interpretable Models for Clinical Applications Ssdm: Scalable speech dysfluency modeling

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T17:52:44.051589Z

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.

source=pdf_text observed=2026-08-05T17:52:38.439623Z digest=sha256:426c1df5a11185b3da976274ef1571360df64cac1d7ae1cb38970d1834285bad

Observation efa9ab3e-fc93-468d-9ff8-51ff24db52fe · outbound

This paper cites SSDM 2.0: Time-Accurate Speech Rich Transcription with Non-Fluencies.

Revisiting Rule-Based Stuttering Detection: A Comprehensive Analysis of Interpretable Models for Clinical Applications SSDM 2.0: Time-Accurate Speech Rich Transcription with Non-Fluencies

Reference 15

Resolution
verified exact
local_arxiv, observed 2026-08-05T17:52:42.332945Z

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.

source=pdf_text observed=2026-08-05T17:52:38.516956Z digest=sha256:30d01cd482513e111746e660386156879a6dd6ed15f59c9af71e6e603c193f13

Observation 671784cc-2582-4df5-8bf6-12807aa4fd3d · outbound

This paper cites Yolo-stutter: End-to-end region-wise speech dysfluency detection.

Revisiting Rule-Based Stuttering Detection: A Comprehensive Analysis of Interpretable Models for Clinical Applications Yolo-stutter: End-to-end region-wise speech dysfluency detection

Reference 16

Resolution
verified exact
doi, observed 2026-08-05T17:52:40.756030Z

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.

source=pdf_text observed=2026-08-05T17:52:38.608703Z digest=sha256:48652f1fdc4329165a34e3929fe940142302bebd92b9c809b460508b0250654f

Observation 36990f5e-6eb1-447c-96e8-19d333f595b6 · outbound

This paper cites Stutter-solver: End-to-end multi-lingual dysfluency detection.

Revisiting Rule-Based Stuttering Detection: A Comprehensive Analysis of Interpretable Models for Clinical Applications Stutter-solver: End-to-end multi-lingual dysfluency detection

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-05T17:52:38.662574Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T17:52:38.662574Z digest=sha256:7d6e2538ead522e66b74bbe0a8bdaeed3a67a97502e6912e0f358ca853fb47de

Observation 0f96a66d-badf-4264-a15b-c78bc95bbd37 · outbound

This paper cites Automatic recognition of repetitions and prolongations in stuttered speech.

Revisiting Rule-Based Stuttering Detection: A Comprehensive Analysis of Interpretable Models for Clinical Applications Automatic recognition of repetitions and prolongations in stuttered speech

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T17:52:43.904028Z

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.

source=pdf_text observed=2026-08-05T17:52:38.755824Z digest=sha256:224e6921049fb7892e8f2febb0babc545bd61f6171a6c555608758c2b96c7eea

Observation 50561126-a32e-4674-8ff2-7b9ded27996d · outbound

This paper cites An automatic prolongation detection approach in continuous speech with robustness against speaking rate variations.

Revisiting Rule-Based Stuttering Detection: A Comprehensive Analysis of Interpretable Models for Clinical Applications An automatic prolongation detection approach in continuous speech with robustness against speaking rate variations

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T17:52:43.794090Z

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.

source=pdf_text observed=2026-08-05T17:52:38.869633Z digest=sha256:115f9167f5cead5efe1c4cf35ad0452c02bb9b7c745b872eaa0ebb521a58dc11

Observation f0fe55de-049c-49d0-baca-cd10470221ee · outbound

This paper cites Seamless dysfluent speech text alignment for disordered speech analysis.

Revisiting Rule-Based Stuttering Detection: A Comprehensive Analysis of Interpretable Models for Clinical Applications Seamless dysfluent speech text alignment for disordered speech analysis

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-05T17:52:38.958527Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T17:52:38.958527Z digest=sha256:65924d8190518242a39c81b63ae6841aabbc0869d9e54f00fa59adeeb1c0f4c4

Observation ce6bbf85-357e-401c-8469-e5d6819b7d53 · outbound

This paper cites LCS-CTC: Leveraging Soft Alignments to Enhance Phonetic Transcription Robustness.

Revisiting Rule-Based Stuttering Detection: A Comprehensive Analysis of Interpretable Models for Clinical Applications LCS-CTC: Leveraging Soft Alignments to Enhance Phonetic Transcription Robustness

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-05T17:52:39.050666Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T17:52:39.050666Z digest=sha256:d024f7b2db3d1536b7bec3bc85340bdef47efda2f5d14b38195d41741394b0f3

Observation c6f5c504-28ce-47a9-92bb-c1dd28b8fafa · outbound

This paper cites Universal phone recognition with a multilingual allophone system.

Revisiting Rule-Based Stuttering Detection: A Comprehensive Analysis of Interpretable Models for Clinical Applications Universal phone recognition with a multilingual allophone system

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T17:52:43.678016Z

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.

source=pdf_text observed=2026-08-05T17:52:39.164196Z digest=sha256:98baf6e0b4f2b66f238ce7b810f7afcbaea99744aa58835eea553ad284e73218

Observation 7cf55aae-6c38-470e-9fef-33816ea0d1e7 · outbound

This paper cites Pattern search in dysfluent speech.

Revisiting Rule-Based Stuttering Detection: A Comprehensive Analysis of Interpretable Models for Clinical Applications Pattern search in dysfluent speech

Reference 23

Resolution
malformed identifier
doi_truncated, observed 2026-08-05T17:52:42.123734Z

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.

source=pdf_text observed=2026-08-05T17:52:39.252453Z digest=sha256:91d9d374223e580e369e6af792cf74cda057f8fc4e934f4252af6a443f992349

Observation 804ef992-3dfe-4727-af17-8f61e9df4cac · outbound

This paper cites Lever- aging allophony in self-supervised speech models for atypical pronunciation assessment.

Revisiting Rule-Based Stuttering Detection: A Comprehensive Analysis of Interpretable Models for Clinical Applications Lever- aging allophony in self-supervised speech models for atypical pronunciation assessment

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T17:52:43.541855Z

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.

source=pdf_text observed=2026-08-05T17:52:39.343925Z digest=sha256:13b213304cf97f52efb46e6633a23a0421975496c958311c9118a1b5ecdc5986

Observation 67cfa16b-9dcd-43b8-9b6f-61be3ebd9b41 · outbound

This paper cites Data-driven mispronunciation pattern discovery for robust speech recognition.

Revisiting Rule-Based Stuttering Detection: A Comprehensive Analysis of Interpretable Models for Clinical Applications Data-driven mispronunciation pattern discovery for robust speech recognition

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T17:52:43.379499Z

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.

source=pdf_text observed=2026-08-05T17:52:39.400841Z digest=sha256:d62927918601b7b059ff3ac1d8e40a358567a3867db97b5cde28ab21bf6614a2

Observation 12485ed2-3ff0-4921-9ee7-5238be705934 · outbound

This paper cites Towards hierarchical spoken language disfluency modeling.

Revisiting Rule-Based Stuttering Detection: A Comprehensive Analysis of Interpretable Models for Clinical Applications Towards hierarchical spoken language disfluency modeling

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T17:52:43.227029Z

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.

source=pdf_text observed=2026-08-05T17:52:39.579008Z digest=sha256:7b35dc9921217affd452bd0f2e0846ee981bc9c17cb41bf2cb788be0ca1d346a

Observation 06efeade-0a37-4545-bf2b-4804abca02cd · outbound

This paper cites Unconstrained dysfluency modeling for dysfluent speech transcription and detection.

Revisiting Rule-Based Stuttering Detection: A Comprehensive Analysis of Interpretable Models for Clinical Applications Unconstrained dysfluency modeling for dysfluent speech transcription and detection

Reference 27

Resolution
metadata mismatch
raw_fallback, observed 2026-08-05T17:52:41.778547Z

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.

source=pdf_text observed=2026-08-05T17:52:39.688444Z digest=sha256:ca8c3914c3226ba695aa880739f8a4cdbc3454c575b60eb0280f52ee9b4a621f

Observation 98e18363-5da2-4dd1-889a-8750012ecece · outbound

This paper cites Dysfluent wfst: A framework for zero-shot speech dysfluency transcription and detection, 2025.

Revisiting Rule-Based Stuttering Detection: A Comprehensive Analysis of Interpretable Models for Clinical Applications Dysfluent wfst: A framework for zero-shot speech dysfluency transcription and detection, 2025

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T17:52:43.049242Z

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.

source=pdf_text observed=2026-08-05T17:52:39.805362Z digest=sha256:a1bc18293cf18a99167ec83de0efbe105cc44154ad9e4f6359abf8d259f805f6

Observation 1a659dd7-63d9-4dfc-a569-85751efdee40 · outbound

This paper cites Time and Tokens: Benchmarking End-to-End Speech Dysfluency Detection.

Revisiting Rule-Based Stuttering Detection: A Comprehensive Analysis of Interpretable Models for Clinical Applications Time and Tokens: Benchmarking End-to-End Speech Dysfluency Detection

Reference 29

Resolution
verified exact
local_arxiv, observed 2026-08-05T17:52:41.545972Z

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.

source=pdf_text observed=2026-08-05T17:52:39.881002Z digest=sha256:1ee412bc2a3d0e79f8d91594ca85be21ad7b8ce38ef42cbe773abee37060214a

Observation fc10087a-48fe-4559-bb68-fdbc3c39abf9 · outbound

This paper cites Cstr vctk corpus: English multi-speaker corpus for cstr voice cloning toolkit (version 0.92), 2019.

Revisiting Rule-Based Stuttering Detection: A Comprehensive Analysis of Interpretable Models for Clinical Applications Cstr vctk corpus: English multi-speaker corpus for cstr voice cloning toolkit (version 0.92), 2019

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T17:52:42.904185Z

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.

source=pdf_text observed=2026-08-05T17:52:39.971644Z digest=sha256:1661959c471d20d2149c5759a80c42a69d139bbf47fd64dc79a7e6241bdc19dd

Observation 362fbf4c-516b-4583-bd94-c188986e5857 · outbound

This paper cites Analysis and Evaluation of Synthetic Data Generation in Speech Dysfluency Detection.

Revisiting Rule-Based Stuttering Detection: A Comprehensive Analysis of Interpretable Models for Clinical Applications Analysis and Evaluation of Synthetic Data Generation in Speech Dysfluency Detection

Reference 31

Resolution
verified exact
local_arxiv, observed 2026-08-05T17:52:41.329492Z

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.

source=pdf_text observed=2026-08-05T17:52:40.054555Z digest=sha256:dd66be7b2bab5a8c318e69f8ff862609205b0dae87b5074780f2db373a1bd3c1

Observation 726b3ab3-5654-4880-a229-46d9a45d0605 · outbound

This paper cites Montreal forced aligner: Trainable text-speech alignment using kaldi.

Revisiting Rule-Based Stuttering Detection: A Comprehensive Analysis of Interpretable Models for Clinical Applications Montreal forced aligner: Trainable text-speech alignment using kaldi

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-05T17:52:40.148715Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T17:52:40.148715Z digest=sha256:1631780d37aa9634e8332fd821f6c99a2dd17e66a0e054d903ff4485f82184d3

Observation b9f22c59-455e-4496-bcf1-85a0c05ab08b · outbound

This paper cites K-function: Joint pronunciation transcription and feedback for evaluating kids language function.

Revisiting Rule-Based Stuttering Detection: A Comprehensive Analysis of Interpretable Models for Clinical Applications K-function: Joint pronunciation transcription and feedback for evaluating kids language function

Reference 33

Resolution
verified exact
raw_fallback, observed 2026-08-05T17:52:41.156966Z

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.

source=pdf_text observed=2026-08-05T17:52:40.234683Z digest=sha256:421ddfef09686590f0612e2635fc749472ef4ec7bb303252c5f1b3e825645e9a

Observation 5a3ec0ba-001d-4b01-b2cb-c27addeea116 · outbound

This paper cites Signature verification using a Siamese time delay neural network.

Revisiting Rule-Based Stuttering Detection: A Comprehensive Analysis of Interpretable Models for Clinical Applications Signature verification using a Siamese time delay neural network

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T17:52:42.738410Z

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.

source=pdf_text observed=2026-08-05T17:52:40.344634Z digest=sha256:30dbf827371c10543719bfd1855ec256f1e1504ba592a82a85f9298dce7d1cab

Observation 7c3a3941-8806-4874-b950-4a4b731bb9e7 · outbound

This paper cites an unresolved cited work.

Revisiting Rule-Based Stuttering Detection: A Comprehensive Analysis of Interpretable Models for Clinical Applications Unresolved cited work

Reference 35

Resolution
unresolved
raw_fallback, observed 2026-08-05T17:52:42.601441Z

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.

source=pdf_text observed=2026-08-05T17:52:40.437559Z digest=sha256:34a8e659f25c1b64b3f124cb4358c54643e6721291a8c0d2ce1fbac2acf229c5

Observation 37270d8d-b602-4404-a217-e2a155382c67 · outbound

This paper cites Conditional variational autoencoder with adver- sarial learning for end-to-end text-to-speech.

Revisiting Rule-Based Stuttering Detection: A Comprehensive Analysis of Interpretable Models for Clinical Applications Conditional variational autoencoder with adver- sarial learning for end-to-end text-to-speech

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T17:52:42.479698Z

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.

source=pdf_text observed=2026-08-05T17:52:40.580503Z digest=sha256:8dd1af0548d90212c2491d19ca94fbf738c0e8007d077030383b0b7625f9ebbc

Observation 1ec01694-459c-4c84-9f05-74afc57087d2 · outbound

This paper cites an unresolved cited work.

Revisiting Rule-Based Stuttering Detection: A Comprehensive Analysis of Interpretable Models for Clinical Applications Unresolved cited work

Reference 2022

Resolution
metadata mismatch
raw_fallback, observed 2026-08-05T17:52:40.956808Z

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.

source=pdf_text observed=2026-08-05T17:52:40.498660Z digest=sha256:97a1a4ea0683617cfb1031f39f95f5c57322a1af7bf12ff3b938fd3742643fa4

Observation 965e1386-f473-4e7a-b9cc-736e09551f51 · outbound

This paper cites URL http://dx.doi.org/10.1109/ ICASSP49660.2025.10888676.

Revisiting Rule-Based Stuttering Detection: A Comprehensive Analysis of Interpretable Models for Clinical Applications URL http://dx.doi.org/10.1109/ ICASSP49660.2025.10888676

Reference 2025

Resolution
unresolved
no resolver link, observed 2026-08-05T17:52:39.484971Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T17:52:39.484971Z digest=sha256:5731a980f4d28f71792d3dc016d717eeb19d678c03ccdecc2952ebd3f4395a01

Pith citing papers

No inbound Pith citation observations are available.