Paper Citation Record · LEDGER

Rethinking Language Model-Based Generative Speech Enhancement in the Latent Space of a Neural Audio Codec

As of 21 August 2026, this Paper Citation Record lists 44 of 44 outbound references and 1 inbound Pith citation observation for arXiv:2608.12082.

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

pith.paper-citation-record.v1
2608.12082 v1

Coverage vector

measured 44 of 44 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T00:22:15.154844Z

measured 45 of 45 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T00:22:14.947985Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-16T00:22:15.394980Z

Reference resolution

44 of 44 outbound references displayed

verified exact1
verified fuzzy35
unresolved7
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e2548229-44f6-44ec-9f00-ec511af72113 · outbound

This paper cites an unresolved cited work.

Rethinking Language Model-Based Generative Speech Enhancement in the Latent Space of a Neural Audio Codec Unresolved cited work

Reference 1

Resolution: unresolved; raw_fallback, observed 2026-08-16T00:22:16.062546Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation ac0db359-6fad-4f44-92a9-7f49371b8aed · outbound

This paper cites Rethinking Language Model-Based Generative Speech Enhancement in the Latent Space of a Neural Audio Codec.

Rethinking Language Model-Based Generative Speech Enhancement in the Latent Space of a Neural Audio Codec Rethinking Language Model-Based Generative Speech Enhancement in the Latent Space of a Neural Audio Codec

Reference 2

Resolution: verified exact; local_arxiv, observed 2026-08-16T00:22:15.402867Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 00ca68b4-a7de-40af-a5e4-c1d3bee9c0d7 · outbound

This paper cites Networks In the proposed SE models, the pretrained 16 kHzDAC[25] and WavLM[26] weights are adopted.

Rethinking Language Model-Based Generative Speech Enhancement in the Latent Space of a Neural Audio Codec Networks In the proposed SE models, the pretrained 16 kHzDAC[25] and WavLM[26] weights are adopted

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:22:16.023750Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 8122321e-f33b-4445-bda3-da5b526a152e · outbound

This paper cites C... ”) are consistently outperforming their discrete-domain counterparts (methods named “D.

Rethinking Language Model-Based Generative Speech Enhancement in the Latent Space of a Neural Audio Codec C... ”) are consistently outperforming their discrete-domain counterparts (methods named “D

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:22:15.990634Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation bd9652df-f5ba-4def-a2a0-eea0ab2b4965 · outbound

This paper cites We are the first to de- liver a comprehensive and fair synopsis of the paradigms by employ- ing both non-intrusive and intrusive metrics.

Rethinking Language Model-Based Generative Speech Enhancement in the Latent Space of a Neural Audio Codec We are the first to de- liver a comprehensive and fair synopsis of the paradigms by employ- ing both non-intrusive and intrusive metrics

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:22:15.974349Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 5805f68a-0880-4c8f-b279-0a7ad01e96b5 · outbound

This paper cites an unresolved cited work.

Rethinking Language Model-Based Generative Speech Enhancement in the Latent Space of a Neural Audio Codec Unresolved cited work

Reference 6

Resolution: unresolved; raw_fallback, observed 2026-08-16T00:22:15.956646Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 6def8921-f3cf-4dc9-b242-b8a5b21f5389 · outbound

This paper cites Speech Enhancement Using Continuous Embeddings of Neural Audio Codec,.

Rethinking Language Model-Based Generative Speech Enhancement in the Latent Space of a Neural Audio Codec Speech Enhancement Using Continuous Embeddings of Neural Audio Codec,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:22:15.875410Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation e5beb3b0-5980-42c6-a1cc-0e144eb5e2d6 · outbound

This paper cites AnyEnhance: A Unified Generative Model with Prompt-Guidance and Self-Critic for V oice En- hancement,.

Rethinking Language Model-Based Generative Speech Enhancement in the Latent Space of a Neural Audio Codec AnyEnhance: A Unified Generative Model with Prompt-Guidance and Self-Critic for V oice En- hancement,

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-16T00:22:15.018061Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 47592323-8a9b-4fdd-88bf-eced6bf8cdac · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

Rethinking Language Model-Based Generative Speech Enhancement in the Latent Space of a Neural Audio Codec LLaMA: Open and Efficient Foundation Language Models

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-16T00:22:14.983206Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b7b87fea-d3a7-4e44-acfc-16c87c9d6b14 · outbound

This paper cites GenSE: Generative Speech Enhancement via Language Models using Hierarchical Modeling,.

Rethinking Language Model-Based Generative Speech Enhancement in the Latent Space of a Neural Audio Codec GenSE: Generative Speech Enhancement via Language Models using Hierarchical Modeling,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:22:15.939941Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 9737c5ea-1406-45af-a768-3b463b472f2f · outbound

This paper cites LLaSE-G1: Incentivizing Generalization Capability for Llama-based Speech Enhancement,.

Rethinking Language Model-Based Generative Speech Enhancement in the Latent Space of a Neural Audio Codec LLaSE-G1: Incentivizing Generalization Capability for Llama-based Speech Enhancement,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:22:15.923043Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation bcf74c10-fa97-4f06-a083-916e468ca1d9 · outbound

This paper cites UniSE: A Unified Framework for Decoder-Only Autoregressive LM-Based Speech Enhancement.

Rethinking Language Model-Based Generative Speech Enhancement in the Latent Space of a Neural Audio Codec UniSE: A Unified Framework for Decoder-Only Autoregressive LM-Based Speech Enhancement

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-16T00:22:14.997112Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5edebc01-c165-42a5-92b4-383163e90f1e · outbound

This paper cites Modeling Strategies for Speech En- hancement in the Latent Space of a Neural Audio Codec,.

Rethinking Language Model-Based Generative Speech Enhancement in the Latent Space of a Neural Audio Codec Modeling Strategies for Speech En- hancement in the Latent Space of a Neural Audio Codec,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:22:15.907608Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 624a359c-9951-4bba-bc89-a6f2322753f2 · outbound

This paper cites an unresolved cited work.

Rethinking Language Model-Based Generative Speech Enhancement in the Latent Space of a Neural Audio Codec Unresolved cited work

Reference 14

Resolution: unresolved; raw_fallback, observed 2026-08-16T00:22:16.042114Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation ba856785-120b-4c7d-a054-f33afb372a2e · outbound

This paper cites High-Fidelity Speech Enhance- ment via Discrete Audio Tokens,.

Rethinking Language Model-Based Generative Speech Enhancement in the Latent Space of a Neural Audio Codec High-Fidelity Speech Enhance- ment via Discrete Audio Tokens,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:22:15.891220Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation b2ea674e-b48a-43b1-9c28-9f1e58493520 · outbound

This paper cites Codec Does Matter: Exploring the Seman- tic Shortcoming of Codec for Audio Language Model,.

Rethinking Language Model-Based Generative Speech Enhancement in the Latent Space of a Neural Audio Codec Codec Does Matter: Exploring the Seman- tic Shortcoming of Codec for Audio Language Model,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:22:15.755519Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 906a7c7e-d675-4995-b2b8-84418b437623 · outbound

This paper cites Genhancer: High-Fidelity Speech Enhance- ment via Generative Modeling on Discrete Codec Tokens,.

Rethinking Language Model-Based Generative Speech Enhancement in the Latent Space of a Neural Audio Codec Genhancer: High-Fidelity Speech Enhance- ment via Generative Modeling on Discrete Codec Tokens,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:22:15.858802Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 58bef9d2-5649-4bbb-be02-b1aab53d4020 · outbound

This paper cites DisContSE: Single-Step Diffusion Speech Enhancement Based on Joint Discrete and Continuous Embed- dings,.

Rethinking Language Model-Based Generative Speech Enhancement in the Latent Space of a Neural Audio Codec DisContSE: Single-Step Diffusion Speech Enhancement Based on Joint Discrete and Continuous Embed- dings,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:22:15.842906Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 369a354c-3a12-4605-9891-81db50515939 · outbound

This paper cites Flow Matching for Generative Model- ing,.

Rethinking Language Model-Based Generative Speech Enhancement in the Latent Space of a Neural Audio Codec Flow Matching for Generative Model- ing,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:22:15.826540Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation c34d593d-699d-40d9-9afc-dca70f70e02e · outbound

This paper cites FlowDec: A Flow-Based Full-Band General Audio Codec with High Perceptual Quality,.

Rethinking Language Model-Based Generative Speech Enhancement in the Latent Space of a Neural Audio Codec FlowDec: A Flow-Based Full-Band General Audio Codec with High Perceptual Quality,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:22:15.809078Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 894c424b-7db8-4cfb-8e7a-37b5e90e3464 · outbound

This paper cites High Fidelity Neural Audio Com- pression,.

Rethinking Language Model-Based Generative Speech Enhancement in the Latent Space of a Neural Audio Codec High Fidelity Neural Audio Com- pression,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:22:15.790923Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 487d4ca8-2add-40de-acdf-e631c1b04246 · outbound

This paper cites High-Fidelity Audio Compression with Improved RVQGAN,.

Rethinking Language Model-Based Generative Speech Enhancement in the Latent Space of a Neural Audio Codec High-Fidelity Audio Compression with Improved RVQGAN,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:22:15.772457Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 1f4fc372-c793-4fc4-96fd-5ad5fa39434e · outbound

This paper cites Spark-TTS: An Efficient LLM-Based Text-to-Speech Model with Single-Stream Decoupled Speech Tokens.

Rethinking Language Model-Based Generative Speech Enhancement in the Latent Space of a Neural Audio Codec Spark-TTS: An Efficient LLM-Based Text-to-Speech Model with Single-Stream Decoupled Speech Tokens

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-16T00:22:15.051545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 52049a1a-51e5-4b43-8fcb-c6f8572394bc · outbound

This paper cites Understanding Straight-Through Esti- mator in Training Activation Quantized Neural Nets,.

Rethinking Language Model-Based Generative Speech Enhancement in the Latent Space of a Neural Audio Codec Understanding Straight-Through Esti- mator in Training Activation Quantized Neural Nets,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:22:15.623089Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 204345bb-4593-4176-9ede-4020e25d6b0d · outbound

This paper cites Residual Quantization with Implicit Neural Codebooks,.

Rethinking Language Model-Based Generative Speech Enhancement in the Latent Space of a Neural Audio Codec Residual Quantization with Implicit Neural Codebooks,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:22:15.740047Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 784a394e-2b0d-410c-b458-64bafdaa2673 · outbound

This paper cites WavLM: Large-Scale Self-Supervised Pre-Training for Full Stack Speech Processing,.

Rethinking Language Model-Based Generative Speech Enhancement in the Latent Space of a Neural Audio Codec WavLM: Large-Scale Self-Supervised Pre-Training for Full Stack Speech Processing,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:22:15.724094Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 06ec2a8e-080b-4a30-b149-35253cb7da8d · outbound

This paper cites MaskGIT: Masked Generative Image Transformer,.

Rethinking Language Model-Based Generative Speech Enhancement in the Latent Space of a Neural Audio Codec MaskGIT: Masked Generative Image Transformer,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:22:15.707831Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation c56653f4-cf3e-4034-ad1b-0ee670d3a829 · outbound

This paper cites A Consolidated View of Loss Func- tions for Supervised Deep Learning-Based Speech Enhance- ment,.

Rethinking Language Model-Based Generative Speech Enhancement in the Latent Space of a Neural Audio Codec A Consolidated View of Loss Func- tions for Supervised Deep Learning-Based Speech Enhance- ment,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:22:15.690690Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 482c7594-a71e-48d2-afb2-a02f01812cdd · outbound

This paper cites an unresolved cited work.

Rethinking Language Model-Based Generative Speech Enhancement in the Latent Space of a Neural Audio Codec Unresolved cited work

Reference 29

Resolution: malformed identifier; raw_fallback, observed 2026-08-16T00:22:16.007900Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 1cc15669-2248-48e0-b877-a56ac6c71d78 · outbound

This paper cites EffCRN: An Efficient Convolutional Re- current Network for High-Performance Speech Enhancement,.

Rethinking Language Model-Based Generative Speech Enhancement in the Latent Space of a Neural Audio Codec EffCRN: An Efficient Convolutional Re- current Network for High-Performance Speech Enhancement,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:22:15.674040Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation bc3bb79a-19a5-4efb-a6ec-ee666c2aa898 · outbound

This paper cites Loss Function Inspired by the PESQ Score,.

Rethinking Language Model-Based Generative Speech Enhancement in the Latent Space of a Neural Audio Codec Loss Function Inspired by the PESQ Score,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:22:15.657046Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation c618ff79-e9b9-4841-9ee1-cd6ec182afc9 · outbound

This paper cites PyTorch Implementation of STOI ,.

Rethinking Language Model-Based Generative Speech Enhancement in the Latent Space of a Neural Audio Codec PyTorch Implementation of STOI ,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:22:15.640514Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 0d79e9ab-6245-4aad-b935-d81e2020c01a · outbound

This paper cites Descript Audio Codec (.dac): High-Fidelity Audio Compression with Improved RVQ- GAN,.

Rethinking Language Model-Based Generative Speech Enhancement in the Latent Space of a Neural Audio Codec Descript Audio Codec (.dac): High-Fidelity Audio Compression with Improved RVQ- GAN,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:22:15.607065Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation d5566bd3-5d2c-4994-aba5-54c565fd8ca8 · outbound

This paper cites WavLM-Large,.

Rethinking Language Model-Based Generative Speech Enhancement in the Latent Space of a Neural Audio Codec WavLM-Large,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:22:15.590387Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 431f2714-505a-432e-bac7-9c346f6ee5a3 · outbound

This paper cites Attention Is All You Need,.

Rethinking Language Model-Based Generative Speech Enhancement in the Latent Space of a Neural Audio Codec Attention Is All You Need,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:22:15.573245Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 71241c32-39a6-4991-8cdb-eeec21fdced8 · outbound

This paper cites Interspeech 2025 URGENT Speech En- hancement Challenge,.

Rethinking Language Model-Based Generative Speech Enhancement in the Latent Space of a Neural Audio Codec Interspeech 2025 URGENT Speech En- hancement Challenge,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:22:15.556356Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 7bc8193f-34a9-445e-af79-a1e71569a62b · outbound

This paper cites Common V oice: A Massively- Multilingual Speech Corpus,.

Rethinking Language Model-Based Generative Speech Enhancement in the Latent Space of a Neural Audio Codec Common V oice: A Massively- Multilingual Speech Corpus,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:22:15.540227Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 632c197f-80b8-481c-a11a-985af16d1fae · outbound

This paper cites P .56: Objective Measurement of Active Speech Level, International Telecommunication Union, Telecommu- nication Standardization Sector (ITU-T), Dec.

Rethinking Language Model-Based Generative Speech Enhancement in the Latent Space of a Neural Audio Codec P .56: Objective Measurement of Active Speech Level, International Telecommunication Union, Telecommu- nication Standardization Sector (ITU-T), Dec

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:22:15.524537Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation a33432d6-cf74-4312-9fb4-c4ff87d94223 · outbound

This paper cites Perceptual Evaluation of Speech Quality (PESQ)—A New Method for Speech Quality Assessment of Telephone Networks and Codecs,.

Rethinking Language Model-Based Generative Speech Enhancement in the Latent Space of a Neural Audio Codec Perceptual Evaluation of Speech Quality (PESQ)—A New Method for Speech Quality Assessment of Telephone Networks and Codecs,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:22:15.509281Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation d5bd8283-df88-46df-a8a6-3b2f3f01b669 · outbound

This paper cites An Algorithm for Predicting the Intel- ligibility of Speech Masked by Modulated Noise Maskers,.

Rethinking Language Model-Based Generative Speech Enhancement in the Latent Space of a Neural Audio Codec An Algorithm for Predicting the Intel- ligibility of Speech Masked by Modulated Noise Maskers,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:22:15.490807Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 2902e11d-b382-46a9-9b4c-d7fa28b133a3 · outbound

This paper cites DNSMOS P. 835: A Non- Intrusive Perceptual Objective Speech Quality Metric to Eval- uate Noise Suppressors,.

Rethinking Language Model-Based Generative Speech Enhancement in the Latent Space of a Neural Audio Codec DNSMOS P. 835: A Non- Intrusive Perceptual Objective Speech Quality Metric to Eval- uate Noise Suppressors,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:22:15.473450Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 519ef48a-0930-41bd-93eb-d53ccef1cf7f · outbound

This paper cites NISQA: A Deep CNN-Self-Attention Model for Multidimensional Speech Quality Prediction with Crowdsourced Datasets,.

Rethinking Language Model-Based Generative Speech Enhancement in the Latent Space of a Neural Audio Codec NISQA: A Deep CNN-Self-Attention Model for Multidimensional Speech Quality Prediction with Crowdsourced Datasets,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:22:15.456687Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 15b66ef5-562e-452b-87f9-328c3e9b3f80 · outbound

This paper cites UTMOS: UTokyo-SaruLab System for V oiceMOS Challenge 2022,.

Rethinking Language Model-Based Generative Speech Enhancement in the Latent Space of a Neural Audio Codec UTMOS: UTokyo-SaruLab System for V oiceMOS Challenge 2022,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:22:15.438156Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 7d2d90cd-a032-468f-9817-23d8c452b7c5 · outbound

This paper cites Evaluation Metrics for Generative Speech Enhancement Methods: Issues and Perspectives,.

Rethinking Language Model-Based Generative Speech Enhancement in the Latent Space of a Neural Audio Codec Evaluation Metrics for Generative Speech Enhancement Methods: Issues and Perspectives,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:22:15.420878Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Pith citing papers

Observation ac0db359-6fad-4f44-92a9-7f49371b8aed · inbound