Paper Citation Record · LEDGER

Few-Shot and Pseudo-Label Guided Speech Quality Evaluation with Large Language Models

As of 13 August 2026, this Paper Citation Record lists 27 of 27 outbound references and 1 inbound Pith citation observation for arXiv:2604.13528.

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

pith.paper-citation-record.v1
2604.13528 v1

Coverage vector

measured 27 of 27 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-10T12:07:56.969101Z

measured 28 of 28 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-10T12:07:56.969101Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-05-10T12:10:21.825104Z

Reference resolution

27 of 27 outbound references displayed

verified exact1
verified fuzzy24
unresolved1
parse uncertain0
malformed identifier0
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f2378383-e264-472e-883b-31ec387fa8d9 · outbound

This paper cites Few-Shot and Pseudo-Label Guided Speech Quality Evaluation with Large Language Models.

Few-Shot and Pseudo-Label Guided Speech Quality Evaluation with Large Language Models Few-Shot and Pseudo-Label Guided Speech Quality Evaluation with Large Language Models

Reference 1

Resolution: metadata mismatch; local_arxiv, observed 2026-05-10T12:10:21.827452Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation b93204a4-42ee-4abd-81bd-12d9e014daa4 · outbound

This paper cites Zero-shot GatherMOS Given an input waveformx∈R T , we extract several acous- tic descriptors that summarize temporal, spectral, and percep- tual information.

Few-Shot and Pseudo-Label Guided Speech Quality Evaluation with Large Language Models Zero-shot GatherMOS Given an input waveformx∈R T , we extract several acous- tic descriptors that summarize temporal, spectral, and percep- tual information

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T12:13:07.450226Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation ec545162-3080-4a39-8384-7ce234ef6cd4 · outbound

This paper cites Experimental setup The proposed approaches are evaluated on the V oiceBank- DEMAND dataset [15], which is also included in the test evaluation of the V oiceMOS Challenge 2024 [16].

Few-Shot and Pseudo-Label Guided Speech Quality Evaluation with Large Language Models Experimental setup The proposed approaches are evaluated on the V oiceBank- DEMAND dataset [15], which is also included in the test evaluation of the V oiceMOS Challenge 2024 [16]

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T12:13:07.452750Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation f046e69a-b2a9-4263-9684-6b1edf672019 · outbound

This paper cites By leveraging the reasoning capabilities of large language models, GatherMOS integrates these diverse signals to produce more reliable MOS pre- dictions.

Few-Shot and Pseudo-Label Guided Speech Quality Evaluation with Large Language Models By leveraging the reasoning capabilities of large language models, GatherMOS integrates these diverse signals to produce more reliable MOS pre- dictions

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T12:13:07.485513Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 15d11bbd-f636-4dc1-9bd6-ac1a48edd0e5 · outbound

This paper cites an unresolved cited work.

Few-Shot and Pseudo-Label Guided Speech Quality Evaluation with Large Language Models Unresolved cited work

Reference 5

Resolution: unresolved; raw_fallback, observed 2026-05-19T12:13:07.448984Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 5c5a32a8-5bd0-4c6b-94ea-c4996fb3c7c4 · outbound

This paper cites The Hearing-Aid Speech Quality Index (HASQI) Version 2.

Few-Shot and Pseudo-Label Guided Speech Quality Evaluation with Large Language Models The Hearing-Aid Speech Quality Index (HASQI) Version 2

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T12:13:07.454892Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 8b836792-62c9-4c14-a7bf-f5b641455344 · outbound

This paper cites Perceptual ob- jective listening quality assessment (POLQA), the third generation ITU-T standard for end-to-end speech qual- ity measurement part i—temporal alignment.

Few-Shot and Pseudo-Label Guided Speech Quality Evaluation with Large Language Models Perceptual ob- jective listening quality assessment (POLQA), the third generation ITU-T standard for end-to-end speech qual- ity measurement part i—temporal alignment

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T12:13:07.447806Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 72f74347-0c75-4e19-abc5-8c52cc6853b8 · outbound

This paper cites MOSNet: Deep learning-based objective assessment for voice conver- sion.

Few-Shot and Pseudo-Label Guided Speech Quality Evaluation with Large Language Models MOSNet: Deep learning-based objective assessment for voice conver- sion

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T12:13:07.455099Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 48a352aa-c9eb-40a2-a5c2-3bb74c439632 · outbound

This paper cites Deep learning-based non-intrusive multi- objective speech assessment model with cross-domain features.

Few-Shot and Pseudo-Label Guided Speech Quality Evaluation with Large Language Models Deep learning-based non-intrusive multi- objective speech assessment model with cross-domain features

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T12:13:07.461260Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 05cf4dfc-23e8-40bd-bc91-89c9fe66c477 · outbound

This paper cites Self-supervised speech quality estimation and en- hancement using only clean speech.

Few-Shot and Pseudo-Label Guided Speech Quality Evaluation with Large Language Models Self-supervised speech quality estimation and en- hancement using only clean speech

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T12:13:07.483020Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation beccd227-6142-4d15-a715-f276297b1361 · outbound

This paper cites Generalization ability of MOS prediction networks.

Few-Shot and Pseudo-Label Guided Speech Quality Evaluation with Large Language Models Generalization ability of MOS prediction networks

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T12:13:07.447009Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 3c78827f-fae6-4291-8f0c-65de74604cb9 · outbound

This paper cites Enabling auditory large language models for automatic speech quality evaluation.

Few-Shot and Pseudo-Label Guided Speech Quality Evaluation with Large Language Models Enabling auditory large language models for automatic speech quality evaluation

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T12:13:07.460432Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation d4da0c24-7136-45e8-87be-2af135d1488b · outbound

This paper cites Audio large language models can be descriptive speech quality evaluators.

Few-Shot and Pseudo-Label Guided Speech Quality Evaluation with Large Language Models Audio large language models can be descriptive speech quality evaluators

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T12:13:07.462754Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 20ca4490-1770-4895-8b33-b45f89265b49 · outbound

This paper cites Wav2vec 2.0: A framework for self-supervised learn- ing of speech representations.

Few-Shot and Pseudo-Label Guided Speech Quality Evaluation with Large Language Models Wav2vec 2.0: A framework for self-supervised learn- ing of speech representations

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T12:13:07.496647Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation b0a6d23f-fd4b-4f0d-a92c-90c48a1c6714 · outbound

This paper cites Robust speech recogni- tion via large-scale weak supervision.

Few-Shot and Pseudo-Label Guided Speech Quality Evaluation with Large Language Models Robust speech recogni- tion via large-scale weak supervision

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T12:13:07.502035Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 94c5c0ad-0a2c-41b5-b8ae-06d39c32bd4c · outbound

This paper cites Exploring In-Context Learning Capabilities of ChatGPT for Pathological Speech Detection.

Few-Shot and Pseudo-Label Guided Speech Quality Evaluation with Large Language Models Exploring In-Context Learning Capabilities of ChatGPT for Pathological Speech Detection

Reference 16

Resolution: verified exact; arxiv_id, observed 2026-05-10T12:10:21.832107Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation be062fdf-0a2f-4bd1-8192-52dad3ce4bf0 · outbound

This paper cites A study on zero-shot non-intrusive speech assessment using large language models.

Few-Shot and Pseudo-Label Guided Speech Quality Evaluation with Large Language Models A study on zero-shot non-intrusive speech assessment using large language models

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T12:13:07.499024Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 6734d477-7a10-4f65-a3d9-a8d1048519d9 · outbound

This paper cites DNSMOS: A non-intrusive perceptual objective speech quality metric to evaluate noise suppressors.

Few-Shot and Pseudo-Label Guided Speech Quality Evaluation with Large Language Models DNSMOS: A non-intrusive perceptual objective speech quality metric to evaluate noise suppressors

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T12:13:07.487917Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation a3e4a0f8-85bc-458f-80a9-360a2fa7431b · outbound

This paper cites Investigating RNN-based speech enhancement methods for noise-robust text-to-speech.

Few-Shot and Pseudo-Label Guided Speech Quality Evaluation with Large Language Models Investigating RNN-based speech enhancement methods for noise-robust text-to-speech

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T12:13:07.494166Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation f8738367-8df3-42c1-96a2-5438b8804045 · outbound

This paper cites The V oicemos challenge 2024: Beyond speech quality pre- diction.

Few-Shot and Pseudo-Label Guided Speech Quality Evaluation with Large Language Models The V oicemos challenge 2024: Beyond speech quality pre- diction

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T12:13:07.478514Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation d6d7055e-6b88-47cf-9ca7-21e9ab5c4664 · outbound

This paper cites Boosting Self-Supervised Embeddings for Speech Enhancement.

Few-Shot and Pseudo-Label Guided Speech Quality Evaluation with Large Language Models Boosting Self-Supervised Embeddings for Speech Enhancement

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T12:13:07.478236Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation c27fffb1-f7c3-4973-9c8f-b800a0858ca1 · outbound

This paper cites MP-SENet: A Speech Enhancement Model with Parallel Denoising of Magni- tude and Phase Spectra.

Few-Shot and Pseudo-Label Guided Speech Quality Evaluation with Large Language Models MP-SENet: A Speech Enhancement Model with Parallel Denoising of Magni- tude and Phase Spectra

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T12:13:07.480684Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation f6836bb7-3a8c-442e-b394-a44d1bc3b8c0 · outbound

This paper cites CMGAN: Conformer-based Metric GAN for Speech Enhance- ment.

Few-Shot and Pseudo-Label Guided Speech Quality Evaluation with Large Language Models CMGAN: Conformer-based Metric GAN for Speech Enhance- ment

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T12:13:07.473817Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation c7086e7e-c440-460d-bce3-90c9dc60bd4a · outbound

This paper cites Real Time Speech Enhancement in the Waveform Domain.

Few-Shot and Pseudo-Label Guided Speech Quality Evaluation with Large Language Models Real Time Speech Enhancement in the Waveform Domain

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T12:13:07.480840Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation a3a7be59-edfc-4343-b2af-cc5d8e24f3e2 · outbound

This paper cites The proof and measurement of associ- ation between two things.

Few-Shot and Pseudo-Label Guided Speech Quality Evaluation with Large Language Models The proof and measurement of associ- ation between two things

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T12:13:07.485711Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 646e73e8-d170-47e0-9ba9-60d362d2bd18 · outbound

This paper cites The CHiME-7 UDASE task: Unsupervised domain adaptation for conversational speech enhance- ment.

Few-Shot and Pseudo-Label Guided Speech Quality Evaluation with Large Language Models The CHiME-7 UDASE task: Unsupervised domain adaptation for conversational speech enhance- ment

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T12:13:07.471172Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation b2241d74-58dc-4929-aa6e-279bc8057aec · outbound

This paper cites Objective and subjec- tive evaluation of speech enhancement methods in the UDASE task of the 7th CHiME challenge.

Few-Shot and Pseudo-Label Guided Speech Quality Evaluation with Large Language Models Objective and subjec- tive evaluation of speech enhancement methods in the UDASE task of the 7th CHiME challenge

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T12:13:07.490583Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Pith citing papers

Observation f2378383-e264-472e-883b-31ec387fa8d9 · inbound