Paper Citation Record · LEDGER

Acoustic-to-Articulatory Inversion of Clean Speech Using an MRI-Trained Model

As of 9 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 1 inbound Pith citation observation for arXiv:2603.11845.

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

pith.paper-citation-record.v1
2603.11845 v2

Coverage vector

measured 40 of 40 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-02T18:22:54.128084Z

measured 41 of 41 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-02T18:22:50.261816Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

40 of 40 outbound references displayed

verified exact0
verified fuzzy0
unresolved40
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malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation fc12be3f-a65e-43b7-8e8b-0dc8de3caf88 · outbound

This paper cites Since the 1970s, several families of solutions have been pro- posed to address this complex inverse problem.

Acoustic-to-Articulatory Inversion of Clean Speech Using an MRI-Trained Model Since the 1970s, several families of solutions have been pro- posed to address this complex inverse problem

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-02T18:22:50.182190Z

Source-reported events for the cited work

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Observation eba6292b-2a54-49d3-8cbf-768cb752784e · outbound

This paper cites How- ever, speech recorded in an MRI machine, even if it is denoised before use, is still far from speech produced in a quiet envi- ronment.

Acoustic-to-Articulatory Inversion of Clean Speech Using an MRI-Trained Model How- ever, speech recorded in an MRI machine, even if it is denoised before use, is still far from speech produced in a quiet envi- ronment

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-02T18:22:50.221078Z

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Observation 9961f304-fd06-4ccb-89f0-73ac0e9b5403 · outbound

This paper cites The first corpus was recorded at the Centre Hospitalier R ´egional Universitaire (CHRU) de Nancy and contains approximately 2.5 hours of data.

Acoustic-to-Articulatory Inversion of Clean Speech Using an MRI-Trained Model The first corpus was recorded at the Centre Hospitalier R ´egional Universitaire (CHRU) de Nancy and contains approximately 2.5 hours of data

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-02T18:22:50.322507Z

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Observation de8faf10-6d68-46c1-9fe5-878ba5eb26dd · outbound

This paper cites Apr`es une heure.

Acoustic-to-Articulatory Inversion of Clean Speech Using an MRI-Trained Model Apr`es une heure

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-02T18:22:50.613321Z

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Observation 1d84a803-1472-4048-97f4-154f21b87e0f · outbound

This paper cites The M2M configuration remains the best, with an average RMSE of 1.51 mm and a median of 1.33 mm.

Acoustic-to-Articulatory Inversion of Clean Speech Using an MRI-Trained Model The M2M configuration remains the best, with an average RMSE of 1.51 mm and a median of 1.33 mm

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-02T18:22:51.187324Z

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Observation 09219410-0288-40c1-b339-4744823daed0 · outbound

This paper cites This configuration corresponds to that of our previous work on in- version, using denoised speech for both training and testing.

Acoustic-to-Articulatory Inversion of Clean Speech Using an MRI-Trained Model This configuration corresponds to that of our previous work on in- version, using denoised speech for both training and testing

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-02T18:22:51.290549Z

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Observation 4e81944a-307e-4151-9c51-aef66e35ae66 · outbound

This paper cites an unresolved cited work.

Acoustic-to-Articulatory Inversion of Clean Speech Using an MRI-Trained Model Unresolved cited work

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-02T18:22:50.728792Z

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Observation 8195e381-2b80-4e3c-b4ce-476aabff5d03 · outbound

This paper cites an unresolved cited work.

Acoustic-to-Articulatory Inversion of Clean Speech Using an MRI-Trained Model Unresolved cited work

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-02T18:22:50.869127Z

Source-reported events for the cited work

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Observation 14ceba48-00df-47a4-b12f-0ffec3f47186 · outbound

This paper cites an unresolved cited work.

Acoustic-to-Articulatory Inversion of Clean Speech Using an MRI-Trained Model Unresolved cited work

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-02T18:22:51.035075Z

Source-reported events for the cited work

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Observation 2fd82ddc-4aac-430b-adaa-dff96a4b9319 · outbound

This paper cites Speaker dependent acoustic-to-articulatory inversion using real-time MRI of the vocal tract,.

Acoustic-to-Articulatory Inversion of Clean Speech Using an MRI-Trained Model Speaker dependent acoustic-to-articulatory inversion using real-time MRI of the vocal tract,

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-02T18:22:52.833204Z

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Observation cb1d9df5-cc72-4f05-a893-c13cd3dfddbc · outbound

This paper cites Preprocessing for acoustic-to-articulatory inversion using real-time mri movies of japanese speech,.

Acoustic-to-Articulatory Inversion of Clean Speech Using an MRI-Trained Model Preprocessing for acoustic-to-articulatory inversion using real-time mri movies of japanese speech,

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-02T18:22:52.923065Z

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Observation a9a14a67-2d29-42bf-bbdb-68b0a94301a3 · outbound

This paper cites an unresolved cited work.

Acoustic-to-Articulatory Inversion of Clean Speech Using an MRI-Trained Model Unresolved cited work

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-02T18:22:51.422579Z

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Observation 2fa62f4b-e1b5-4ad3-89f3-768295d37a4c · outbound

This paper cites A multi-channel/multi-speaker articulatory database for continuous speech recognition research,.

Acoustic-to-Articulatory Inversion of Clean Speech Using an MRI-Trained Model A multi-channel/multi-speaker articulatory database for continuous speech recognition research,

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-02T18:22:51.593298Z

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Observation 9dcebb0b-eb07-4d56-95e6-dc674c5bbab4 · outbound

This paper cites X-ray mi- crobeam speech production database,.

Acoustic-to-Articulatory Inversion of Clean Speech Using an MRI-Trained Model X-ray mi- crobeam speech production database,

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-02T18:22:51.752564Z

Source-reported events for the cited work

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Observation 34d060a0-66db-4338-a63c-9fe3c21ac810 · outbound

This paper cites Acoustic-to-articulatory inversion mapping with gaussian mixture model.

Acoustic-to-Articulatory Inversion of Clean Speech Using an MRI-Trained Model Acoustic-to-articulatory inversion mapping with gaussian mixture model

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-02T18:22:51.873810Z

Source-reported events for the cited work

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Observation bcafdc29-6de6-4f9c-86db-6e4c87065cb5 · outbound

This paper cites Estimation of articulatory movements from speech acoustics using an hmm-based speech production model,.

Acoustic-to-Articulatory Inversion of Clean Speech Using an MRI-Trained Model Estimation of articulatory movements from speech acoustics using an hmm-based speech production model,

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-02T18:22:51.999557Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8c34b210-4097-4b44-8bd2-03db93de8791 · outbound

This paper cites A deep recurrent approach for acoustic-to-articulatory inversion,.

Acoustic-to-Articulatory Inversion of Clean Speech Using an MRI-Trained Model A deep recurrent approach for acoustic-to-articulatory inversion,

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-02T18:22:52.125276Z

Source-reported events for the cited work

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Observation 46e8d844-8c2c-4f9a-99a4-c7ec40902264 · outbound

This paper cites Independent and Automatic Evaluation of Speaker-Independent Acoustic-to- Articulatory Reconstruction,.

Acoustic-to-Articulatory Inversion of Clean Speech Using an MRI-Trained Model Independent and Automatic Evaluation of Speaker-Independent Acoustic-to- Articulatory Reconstruction,

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-02T18:22:52.252484Z

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Unavailable: canonical work link unavailable.

Observation 52b8089f-ed1d-4ca4-9845-a69b2fea6839 · outbound

This paper cites Speaker-independent acoustic-to-articulatory speech inversion,.

Acoustic-to-Articulatory Inversion of Clean Speech Using an MRI-Trained Model Speaker-independent acoustic-to-articulatory speech inversion,

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-02T18:22:52.368057Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c4c6e208-3620-4063-b28e-c1ea6e3cbd34 · outbound

This paper cites The secret source: In- corporating source features to improve acoustic-to-articulatory speech inversion,.

Acoustic-to-Articulatory Inversion of Clean Speech Using an MRI-Trained Model The secret source: In- corporating source features to improve acoustic-to-articulatory speech inversion,

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-02T18:22:52.547849Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2636f26b-94ac-4eaf-a5a1-2bd89f24cff4 · outbound

This paper cites Analysis of speech production real-time mri,.

Acoustic-to-Articulatory Inversion of Clean Speech Using an MRI-Trained Model Analysis of speech production real-time mri,

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-02T18:22:52.696552Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9edc5bab-6874-4e21-90de-eda76b05e526 · outbound

This paper cites Multimodal dataset of real-time 2D and static 3D MRI of healthy French speakers,.

Acoustic-to-Articulatory Inversion of Clean Speech Using an MRI-Trained Model Multimodal dataset of real-time 2D and static 3D MRI of healthy French speakers,

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-02T18:22:53.803281Z

Source-reported events for the cited work

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Observation 0b9c5122-69cd-4293-acc4-f977cb9a3724 · outbound

This paper cites Acoustic-to-Articulatory Inversion of Clean Speech Using an MRI-Trained Model.

Acoustic-to-Articulatory Inversion of Clean Speech Using an MRI-Trained Model Acoustic-to-Articulatory Inversion of Clean Speech Using an MRI-Trained Model

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-02T18:22:50.261816Z

Source-reported events for the cited work

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Observation 1f201044-3f5b-4f86-a50e-ba12db3b53b6 · outbound

This paper cites Speech2rtmri: Speech-guided diffusion model for real-time mri video of the vocal tract during speech,.

Acoustic-to-Articulatory Inversion of Clean Speech Using an MRI-Trained Model Speech2rtmri: Speech-guided diffusion model for real-time mri video of the vocal tract during speech,

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-02T18:22:53.037002Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0d7a1521-4bc4-47c0-b485-03e43fd208e1 · outbound

This paper cites Automatic segmentation of vocal tract articulators in real-time magnetic resonance imaging,.

Acoustic-to-Articulatory Inversion of Clean Speech Using an MRI-Trained Model Automatic segmentation of vocal tract articulators in real-time magnetic resonance imaging,

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-02T18:22:53.097956Z

Source-reported events for the cited work

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Observation c8193d2c-e022-4131-87c7-ef4233b906de · outbound

This paper cites Both phonetic segmentations were carefully reviewed to ensure they were strictly identical across the two corpora.

Acoustic-to-Articulatory Inversion of Clean Speech Using an MRI-Trained Model Both phonetic segmentations were carefully reviewed to ensure they were strictly identical across the two corpora

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-02T18:22:50.400122Z

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Observation 080d4b77-b26a-4149-affe-5d5c1ec6fcd2 · outbound

This paper cites Complete Reconstruc- tion of the Tongue Contour Through Acoustic to Articulatory Inversion Using Real-Time MRI Data,.

Acoustic-to-Articulatory Inversion of Clean Speech Using an MRI-Trained Model Complete Reconstruc- tion of the Tongue Contour Through Acoustic to Articulatory Inversion Using Real-Time MRI Data,

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-02T18:22:53.188555Z

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Observation 19b23fed-29eb-4920-9eb4-a35f05f35b08 · outbound

This paper cites Reconstruction of the Complete V ocal Tract Contour Through Acoustic to Articulatory Inversion Using Real-Time MRI Data,.

Acoustic-to-Articulatory Inversion of Clean Speech Using an MRI-Trained Model Reconstruction of the Complete V ocal Tract Contour Through Acoustic to Articulatory Inversion Using Real-Time MRI Data,

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-02T18:22:53.266565Z

Source-reported events for the cited work

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Observation f5235915-146e-41e5-bee1-6cf8b4ab7c4a · outbound

This paper cites Hubert: Self-supervised speech represen- tation learning by masked prediction of hidden units,.

Acoustic-to-Articulatory Inversion of Clean Speech Using an MRI-Trained Model Hubert: Self-supervised speech represen- tation learning by masked prediction of hidden units,

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-02T18:22:53.351970Z

Source-reported events for the cited work

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Observation 8c288bc4-f418-4db9-98ae-66bccbd6e5dc · outbound

This paper cites Self-supervised models of speech infer universal articulatory kinematics,.

Acoustic-to-Articulatory Inversion of Clean Speech Using an MRI-Trained Model Self-supervised models of speech infer universal articulatory kinematics,

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-02T18:22:53.404063Z

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Observation 21619794-ab7c-4775-8615-7668ffa11882 · outbound

This paper cites wav2vec 2.0: A framework for self-supervised learning of speech repre- sentations,.

Acoustic-to-Articulatory Inversion of Clean Speech Using an MRI-Trained Model wav2vec 2.0: A framework for self-supervised learning of speech repre- sentations,

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-02T18:22:53.480097Z

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Observation 164ead96-2a0b-4171-a544-a3736e247353 · outbound

This paper cites Wavlm: Large-scale self- supervised pre-training for full stack speech processing,.

Acoustic-to-Articulatory Inversion of Clean Speech Using an MRI-Trained Model Wavlm: Large-scale self- supervised pre-training for full stack speech processing,

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-02T18:22:53.559803Z

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Observation 4b067e34-c436-4951-9aa8-74e8c82698f5 · outbound

This paper cites Improv- ing speech inversion through self-supervised embeddings and en- hanced tract variables,.

Acoustic-to-Articulatory Inversion of Clean Speech Using an MRI-Trained Model Improv- ing speech inversion through self-supervised embeddings and en- hanced tract variables,

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-02T18:22:53.637789Z

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Observation c17e9a26-d61c-41d8-b06f-acc2587c7b15 · outbound

This paper cites A Fine-tuned Wav2vec 2.0/HuBERT Benchmark For Speech Emotion Recognition, Speaker Verification and Spoken Language Understanding.

Acoustic-to-Articulatory Inversion of Clean Speech Using an MRI-Trained Model A Fine-tuned Wav2vec 2.0/HuBERT Benchmark For Speech Emotion Recognition, Speaker Verification and Spoken Language Understanding

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-02T18:22:53.721498Z

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Observation 8b8bb7af-fec1-4307-b590-23c37f2ab248 · outbound

This paper cites The influence of acoustics on speech production: A noise-induced stress phenomenon known as the lombard reflex,.

Acoustic-to-Articulatory Inversion of Clean Speech Using an MRI-Trained Model The influence of acoustics on speech production: A noise-induced stress phenomenon known as the lombard reflex,

Reference 35

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Observation 0b5d8c48-c1ba-4d13-b03c-97b76abd2d41 · outbound

This paper cites A general flexible frame- work for the handling of prior information in audio source sepa- ration,.

Acoustic-to-Articulatory Inversion of Clean Speech Using an MRI-Trained Model A general flexible frame- work for the handling of prior information in audio source sepa- ration,

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-02T18:22:53.915118Z

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Observation bc07674c-7188-47ea-8599-ea419a1f2262 · outbound

This paper cites De l’importance de l’homog ´en´eisation des conventions de transcription pour l’alignement automatique de corpus oraux de parole spontan ´ee,.

Acoustic-to-Articulatory Inversion of Clean Speech Using an MRI-Trained Model De l’importance de l’homog ´en´eisation des conventions de transcription pour l’alignement automatique de corpus oraux de parole spontan ´ee,

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-02T18:22:53.961906Z

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Observation 5c484670-bf95-42c7-9cc7-16c2651170d8 · outbound

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

Acoustic-to-Articulatory Inversion of Clean Speech Using an MRI-Trained Model Montreal forced aligner: Trainable text-speech align- ment using kaldi

Reference 38

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Observation 979567ff-b331-4745-898e-615fa66cdd6c · outbound

This paper cites Pattern matching: The gestalt approach,.

Acoustic-to-Articulatory Inversion of Clean Speech Using an MRI-Trained Model Pattern matching: The gestalt approach,

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-02T18:22:54.069292Z

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Observation dbdbbc1e-149d-4ad3-a2fc-5debf42606a5 · outbound

This paper cites M ¨uller,Fundamentals of music processing: Audio, analysis, algorithms, applications.

Acoustic-to-Articulatory Inversion of Clean Speech Using an MRI-Trained Model M ¨uller,Fundamentals of music processing: Audio, analysis, algorithms, applications

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-02T18:22:54.128084Z

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Pith citing papers

Observation 0b9c5122-69cd-4293-acc4-f977cb9a3724 · inbound