Paper Citation Record · LEDGER

Assessment of L2 Oral Proficiency using Speech Large Language Models

As of 9 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 1 inbound Pith citation observation for arXiv:2505.21148.

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

pith.paper-citation-record.v1
2505.21148 v1

Coverage vector

measured 38 of 38 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:43:11.659473Z

measured 39 of 39 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:43:08.275251Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T13:43:11.881822Z

Reference resolution

38 of 38 outbound references displayed

verified exact1
verified fuzzy28
unresolved9
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 4f564c82-ecd3-4b9e-b49d-5424f77d06e9 · outbound

This paper cites Assessment of L2 Oral Proficiency using Speech Large Language Models.

Assessment of L2 Oral Proficiency using Speech Large Language Models Assessment of L2 Oral Proficiency using Speech Large Language Models

Reference 1

Resolution: verified exact; local_arxiv, observed 2026-08-07T13:43:11.949742Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation db3fd436-dfd1-4d31-88ea-5c1a9111c7a5 · outbound

This paper cites A”to“F”) based on the candidate’s speech responses. Here, a function scoreis used to map each text-based grade into its numeric class (e.g. label“A.

Assessment of L2 Oral Proficiency using Speech Large Language Models A”to“F”) based on the candidate’s speech responses. Here, a function scoreis used to map each text-based grade into its numeric class (e.g. label“A

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:43:18.142777Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 30ba7415-b38f-4eb2-a86e-cd53f4022309 · outbound

This paper cites an unresolved cited work.

Assessment of L2 Oral Proficiency using Speech Large Language Models Unresolved cited work

Reference 3

Resolution: unresolved; raw_fallback, observed 2026-08-07T13:43:17.973911Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation f06beabb-2e53-4953-990d-10e11bea2fb1 · outbound

This paper cites Vari- ous training and decoding schemes are compared on Linguaskill and S&I datasets.

Assessment of L2 Oral Proficiency using Speech Large Language Models Vari- ous training and decoding schemes are compared on Linguaskill and S&I datasets

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:43:17.803088Z

Source-reported events for the cited work

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Observation c5b05755-a48e-4b11-bcbd-93aaf93ac195 · outbound

This paper cites Automatic evaluation and training in English pronuncia- tion,.

Assessment of L2 Oral Proficiency using Speech Large Language Models Automatic evaluation and training in English pronuncia- tion,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:43:17.631824Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation c41db8db-8aa2-4dc1-960c-88c9bb0c5793 · outbound

This paper cites Automatic evaluation of Dutch pronunciation by using speech recognition technology,.

Assessment of L2 Oral Proficiency using Speech Large Language Models Automatic evaluation of Dutch pronunciation by using speech recognition technology,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:43:17.399791Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation c94c84fa-b4cb-4def-b655-7436311d081e · outbound

This paper cites The SRI EduSpeak™ system: Recog- nition and pronunciation scoring for language learning,.

Assessment of L2 Oral Proficiency using Speech Large Language Models The SRI EduSpeak™ system: Recog- nition and pronunciation scoring for language learning,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:43:17.211243Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 7a85fbe4-97b7-4e42-bbe3-1519c08d8cf8 · outbound

This paper cites Speechrater: A construct- driven approach to scoring spontaneous non-native speech,.

Assessment of L2 Oral Proficiency using Speech Large Language Models Speechrater: A construct- driven approach to scoring spontaneous non-native speech,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:43:17.000472Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 4dc075d3-811a-4795-a372-282f589740fc · outbound

This paper cites The use of DBN-HMMs for mispronunciation detection and diagnosis in L2 English to sup- port computer-aided pronunciation training,.

Assessment of L2 Oral Proficiency using Speech Large Language Models The use of DBN-HMMs for mispronunciation detection and diagnosis in L2 English to sup- port computer-aided pronunciation training,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:43:16.808977Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 01112f90-8a76-4a55-921b-0f9c22fa9984 · outbound

This paper cites Improvements to an automated con- tent scoring system for Spoken CALL responses: the ETS sub- mission to the Second Spoken CALL Shared Task.

Assessment of L2 Oral Proficiency using Speech Large Language Models Improvements to an automated con- tent scoring system for Spoken CALL responses: the ETS sub- mission to the Second Spoken CALL Shared Task

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:43:16.625062Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation f6321a22-fb08-4337-ae96-85e21b073e10 · outbound

This paper cites The University of Birm- ingham 2019 Spoken CALL Shared Task Systems: Exploring the importance of word order in text processing,.

Assessment of L2 Oral Proficiency using Speech Large Language Models The University of Birm- ingham 2019 Spoken CALL Shared Task Systems: Exploring the importance of word order in text processing,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:43:16.468673Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation d5e61fe0-009d-4ea0-8d53-93cbca84a0ea · outbound

This paper cites BERT: Pre- training of deep bidirectional transformers for language under- standing,.

Assessment of L2 Oral Proficiency using Speech Large Language Models BERT: Pre- training of deep bidirectional transformers for language under- standing,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:43:16.309065Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 3e0be34d-3fe6-4666-be24-b9b3bee750cd · outbound

This paper cites Universal adversarial attacks on spoken language assessment systems,.

Assessment of L2 Oral Proficiency using Speech Large Language Models Universal adversarial attacks on spoken language assessment systems,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:43:16.094052Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation f18eb159-04ec-400b-81a6-2a5b47901109 · outbound

This paper cites Automated scoring of spontaneous speech from young learners of English using transformers,.

Assessment of L2 Oral Proficiency using Speech Large Language Models Automated scoring of spontaneous speech from young learners of English using transformers,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:43:15.917037Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation e110f760-9eb3-4451-882a-9828fe2047fc · outbound

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

Assessment of L2 Oral Proficiency using Speech Large Language Models wav2vec 2.0: A framework for self-supervised learning of speech representa- tions,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:43:15.706564Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation e1ea675b-df17-4a9e-8818-6d6ede884051 · outbound

This paper cites HuBERT: Self-supervised speech representation learning by masked prediction of hidden units,.

Assessment of L2 Oral Proficiency using Speech Large Language Models HuBERT: Self-supervised speech representation learning by masked prediction of hidden units,

Reference 16

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Source-reported events for the cited work

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Observation 19bf52a7-4888-44c9-8b2a-16ce19250702 · outbound

This paper cites A Study on Fine- Tuning wav2vec2.0 Model for the Task of Mispronunciation De- tection and Diagnosis,.

Assessment of L2 Oral Proficiency using Speech Large Language Models A Study on Fine- Tuning wav2vec2.0 Model for the Task of Mispronunciation De- tection and Diagnosis,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:43:15.477910Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 9c7eda7d-c5f2-445f-9a31-1d77d85374be · outbound

This paper cites Transformer based end-to-end mispronunciation detection and diagnosis,.

Assessment of L2 Oral Proficiency using Speech Large Language Models Transformer based end-to-end mispronunciation detection and diagnosis,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:43:15.294293Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 5f1f8575-6613-4f65-a40e-21bdbd720b55 · outbound

This paper cites Explore wav2vec 2.0 for Mispronunciation Detection,.

Assessment of L2 Oral Proficiency using Speech Large Language Models Explore wav2vec 2.0 for Mispronunciation Detection,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:43:15.075946Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation b77915ca-0cf0-40c0-988c-6c1a20f433bf · outbound

This paper cites Automatic Pronunciation Assessment using Self-Supervised Speech Representation Learn- ing,.

Assessment of L2 Oral Proficiency using Speech Large Language Models Automatic Pronunciation Assessment using Self-Supervised Speech Representation Learn- ing,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:43:14.864060Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 1b7bd062-1843-4f20-8db7-f1c4c749da25 · outbound

This paper cites Proficiency assessment of L2 spo- ken English using wav2vec 2.0,.

Assessment of L2 Oral Proficiency using Speech Large Language Models Proficiency assessment of L2 spo- ken English using wav2vec 2.0,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:43:14.709407Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation c13d8874-57c1-42e1-924d-0509bf1eb878 · outbound

This paper cites Assessment of L2 Oral Proficiency Using Self-Supervised Speech Representation Learning,.

Assessment of L2 Oral Proficiency using Speech Large Language Models Assessment of L2 Oral Proficiency Using Self-Supervised Speech Representation Learning,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:43:14.525929Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 3d8a2c7b-d357-41dd-bd8d-8699355a7cf3 · outbound

This paper cites Automatic assessment of conversational speak- ing tests,.

Assessment of L2 Oral Proficiency using Speech Large Language Models Automatic assessment of conversational speak- ing tests,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:43:14.341490Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 715e95f1-bdce-437e-b570-8572eabb2a57 · outbound

This paper cites SALMONN: Towards Generic Hearing Abilities for Large Language Models,.

Assessment of L2 Oral Proficiency using Speech Large Language Models SALMONN: Towards Generic Hearing Abilities for Large Language Models,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:43:14.103089Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 95378c91-87e8-437f-82eb-771c5d057cf6 · outbound

This paper cites Qwen-Audio: Advancing Universal Audio Understanding via Unified Large-Scale Audio-Language Models.

Assessment of L2 Oral Proficiency using Speech Large Language Models Qwen-Audio: Advancing Universal Audio Understanding via Unified Large-Scale Audio-Language Models

Reference 25

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Source-reported events for the cited work

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Observation 38ff5747-d11a-4012-a08a-76a9b75c4405 · outbound

This paper cites Qwen2-Audio Technical Report.

Assessment of L2 Oral Proficiency using Speech Large Language Models Qwen2-Audio Technical Report

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-07T13:43:10.570169Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0a85cc88-f67a-4e93-bbc4-ae1acf73694d · outbound

This paper cites Exploring the potential of using an ai language model for automated essay scoring,.

Assessment of L2 Oral Proficiency using Speech Large Language Models Exploring the potential of using an ai language model for automated essay scoring,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:43:13.849493Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 1007538d-6449-4d79-a204-e32c1fbe35f2 · outbound

This paper cites Rating short L2 essays on the CEFR scale with GPT-4,.

Assessment of L2 Oral Proficiency using Speech Large Language Models Rating short L2 essays on the CEFR scale with GPT-4,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:43:13.545576Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 04399695-6456-42ee-8e03-6fda48a4f465 · outbound

This paper cites Can GPT-4 do L2 analytic assessment?.

Assessment of L2 Oral Proficiency using Speech Large Language Models Can GPT-4 do L2 analytic assessment?

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:43:13.207181Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation fd9c6a79-b6bf-46f4-ba4d-aa3dfa64a5ae · outbound

This paper cites Pronunciation Assessment with Multi-modal Large Language Models.

Assessment of L2 Oral Proficiency using Speech Large Language Models Pronunciation Assessment with Multi-modal Large Language Models

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-07T13:43:10.980671Z

Source-reported events for the cited work

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Observation 91f679ad-4970-4681-8948-6ea23799f30b · outbound

This paper cites Emergent Abilities of Large Language Models,.

Assessment of L2 Oral Proficiency using Speech Large Language Models Emergent Abilities of Large Language Models,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:43:12.887690Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation bf8472a1-137e-46f6-a17c-4506542e6558 · outbound

This paper cites of Europe.

Assessment of L2 Oral Proficiency using Speech Large Language Models of Europe

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-07T13:43:11.146042Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9b1560fd-a05f-40cc-bc31-87d37dd52991 · outbound

This paper cites Ludlow,Official Quick Guide to Linguaskill.

Assessment of L2 Oral Proficiency using Speech Large Language Models Ludlow,Official Quick Guide to Linguaskill

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:43:12.554501Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 5746ca2c-7d2e-4690-a181-9d26ba798d59 · outbound

This paper cites The Speak & Improve Corpus 2025: an L2 English Speech Corpus for Language Assessment and Feedback,.

Assessment of L2 Oral Proficiency using Speech Large Language Models The Speak & Improve Corpus 2025: an L2 English Speech Corpus for Language Assessment and Feedback,

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-07T13:43:11.321095Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a059604f-028d-4eab-b583-3dedb858791f · outbound

This paper cites Speak & Improve Challenge 2025: Tasks and Baseline Systems.

Assessment of L2 Oral Proficiency using Speech Large Language Models Speak & Improve Challenge 2025: Tasks and Baseline Systems

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-07T13:43:11.403974Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 900887f2-fde2-4c14-9d42-456719329f91 · outbound

This paper cites Universal adversarial attacks on spoken language assessment systems,.

Assessment of L2 Oral Proficiency using Speech Large Language Models Universal adversarial attacks on spoken language assessment systems,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:43:12.347337Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 3d625097-0ade-4b0d-a8a1-dcda6167b620 · outbound

This paper cites Robust speech recognition via large-scale weak supervision,.

Assessment of L2 Oral Proficiency using Speech Large Language Models Robust speech recognition via large-scale weak supervision,

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-07T13:43:11.598707Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f444a020-94e8-49d8-ac2b-e3ffe82ea0c8 · outbound

This paper cites Mitigating Word Bias in Zero-shot Prompt-based Classifiers,.

Assessment of L2 Oral Proficiency using Speech Large Language Models Mitigating Word Bias in Zero-shot Prompt-based Classifiers,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:43:12.176450Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Pith citing papers

Observation 4f564c82-ecd3-4b9e-b49d-5424f77d06e9 · inbound