Paper Citation Record · LEDGER

ANCHOR: Autoregressive Non-intrusive Chunk-Ordered Refinement for Joint Multi-Resolution Speech Quality Modeling

As of 19 August 2026, this Paper Citation Record lists 47 of 47 outbound references and 1 inbound Pith citation observation for arXiv:2606.10233.

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

pith.paper-citation-record.v1
2606.10233 v1

Coverage vector

measured 47 of 47 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-27T14:38:44.321577Z

measured 48 of 48 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-27T14:38:44.321577Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-03T03:47:35.782666Z

Reference resolution

47 of 47 outbound references displayed

verified exact0
verified fuzzy0
unresolved45
parse uncertain0
malformed identifier1
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 3f4ed257-2621-487f-b453-5869407e97a7 · outbound

This paper cites This incremental setting mirrors human speech per- ception, where listeners process acoustic signals as they unfold in time rather than waiting for utterance completion [10].

ANCHOR: Autoregressive Non-intrusive Chunk-Ordered Refinement for Joint Multi-Resolution Speech Quality Modeling This incremental setting mirrors human speech per- ception, where listeners process acoustic signals as they unfold in time rather than waiting for utterance completion [10]

Reference 1

Resolution: unresolved; no resolver link, observed 2026-06-27T14:38:44.321577Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ddaaa18d-1c72-4497-a10d-c340d2b56880 · outbound

This paper cites ANCHOR: Autoregressive Non-intrusive Chunk-Ordered Refinement for Joint Multi-Resolution Speech Quality Modeling.

ANCHOR: Autoregressive Non-intrusive Chunk-Ordered Refinement for Joint Multi-Resolution Speech Quality Modeling ANCHOR: Autoregressive Non-intrusive Chunk-Ordered Refinement for Joint Multi-Resolution Speech Quality Modeling

Reference 2

Resolution: metadata mismatch; local_arxiv, observed 2026-07-03T03:47:35.784188Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 46bffe16-0b99-4bb2-89b1-d16289c8226c · outbound

This paper cites Multi-Resolution Autoregressive Modeling ANCHOR extends ARECHO [13] by introducing dual- resolution metric query tokens and a resolution-aware decoding hierarchy.

ANCHOR: Autoregressive Non-intrusive Chunk-Ordered Refinement for Joint Multi-Resolution Speech Quality Modeling Multi-Resolution Autoregressive Modeling ANCHOR extends ARECHO [13] by introducing dual- resolution metric query tokens and a resolution-aware decoding hierarchy

Reference 3

Resolution: unresolved; no resolver link, observed 2026-06-27T14:38:44.321577Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 19500ffb-ead4-4ae0-b1ce-f24b3bc41d74 · outbound

This paper cites Dataset and Prefix Construction Dataset.Experiments utilize theOverall Baseconfiguration from [13], spanning 308.8 hours of clean, corrupted, and synthe- sized speech.

ANCHOR: Autoregressive Non-intrusive Chunk-Ordered Refinement for Joint Multi-Resolution Speech Quality Modeling Dataset and Prefix Construction Dataset.Experiments utilize theOverall Baseconfiguration from [13], spanning 308.8 hours of clean, corrupted, and synthe- sized speech

Reference 4

Resolution: unresolved; no resolver link, observed 2026-06-27T14:38:44.321577Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a8a9048b-db84-463a-8c87-951d0168a0f3 · outbound

This paper cites Chunk-Level: Local vs.

ANCHOR: Autoregressive Non-intrusive Chunk-Ordered Refinement for Joint Multi-Resolution Speech Quality Modeling Chunk-Level: Local vs

Reference 5

Resolution: unresolved; no resolver link, observed 2026-06-27T14:38:44.321577Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 03abdace-38aa-4c10-ad2c-768c05a15c2e · outbound

This paper cites By enforcing a resolution-aware decoding hierarchy, we mitigate supervision conflict between local and global objec- tives.

ANCHOR: Autoregressive Non-intrusive Chunk-Ordered Refinement for Joint Multi-Resolution Speech Quality Modeling By enforcing a resolution-aware decoding hierarchy, we mitigate supervision conflict between local and global objec- tives

Reference 6

Resolution: unresolved; no resolver link, observed 2026-06-27T14:38:44.321577Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1c3c7a0d-6d44-4f46-abaf-113073e2e9be · outbound

This paper cites National Science Foundation grants #2138259, #2138286, #2138307, #2137603, and #2138296.

ANCHOR: Autoregressive Non-intrusive Chunk-Ordered Refinement for Joint Multi-Resolution Speech Quality Modeling National Science Foundation grants #2138259, #2138286, #2138307, #2137603, and #2138296

Reference 7

Resolution: unresolved; no resolver link, observed 2026-06-27T14:38:44.321577Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ac2fa64e-a555-4594-a394-766c8325243b · outbound

This paper cites All experimental design, analysis, and scientific claims are the authors’ own, and the authors take full respon- sibility for the work and its content.

ANCHOR: Autoregressive Non-intrusive Chunk-Ordered Refinement for Joint Multi-Resolution Speech Quality Modeling All experimental design, analysis, and scientific claims are the authors’ own, and the authors take full respon- sibility for the work and its content

Reference 8

Resolution: unresolved; no resolver link, observed 2026-06-27T14:38:44.321577Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3d82ad64-620c-457d-9e7c-3e1c3772e5a2 · outbound

This paper cites Emformer: Efficient memory transformer based acoustic model for low latency streaming speech recognition,.

ANCHOR: Autoregressive Non-intrusive Chunk-Ordered Refinement for Joint Multi-Resolution Speech Quality Modeling Emformer: Efficient memory transformer based acoustic model for low latency streaming speech recognition,

Reference 9

Resolution: unresolved; no resolver link, observed 2026-06-27T14:38:44.321577Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ce37c635-21b1-47e4-aeb4-d7e2e8b89604 · outbound

This paper cites Real time speech enhance- ment in the waveform domain,.

ANCHOR: Autoregressive Non-intrusive Chunk-Ordered Refinement for Joint Multi-Resolution Speech Quality Modeling Real time speech enhance- ment in the waveform domain,

Reference 10

Resolution: unresolved; no resolver link, observed 2026-06-27T14:38:44.321577Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 19685006-5f7b-4870-b874-bd069bfcd5ef · outbound

This paper cites Tacotron: Towards end- to-end speech synthesis,.

ANCHOR: Autoregressive Non-intrusive Chunk-Ordered Refinement for Joint Multi-Resolution Speech Quality Modeling Tacotron: Towards end- to-end speech synthesis,

Reference 11

Resolution: unresolved; no resolver link, observed 2026-06-27T14:38:44.321577Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 12eb3f14-c89c-401c-bcbc-926e92c68c5c · outbound

This paper cites Efficient neural audio synthesis,.

ANCHOR: Autoregressive Non-intrusive Chunk-Ordered Refinement for Joint Multi-Resolution Speech Quality Modeling Efficient neural audio synthesis,

Reference 12

Resolution: unresolved; no resolver link, observed 2026-06-27T14:38:44.321577Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a0573f36-edd1-4567-ac74-3ef3fe42efe1 · outbound

This paper cites Audiolm: A language modeling approach to audio generation,.

ANCHOR: Autoregressive Non-intrusive Chunk-Ordered Refinement for Joint Multi-Resolution Speech Quality Modeling Audiolm: A language modeling approach to audio generation,

Reference 13

Resolution: unresolved; no resolver link, observed 2026-06-27T14:38:44.321577Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3f9fc366-345d-40b4-92a2-64850544b908 · outbound

This paper cites Speak, read and prompt: High-fidelity text-to-speech with minimal super- vision,.

ANCHOR: Autoregressive Non-intrusive Chunk-Ordered Refinement for Joint Multi-Resolution Speech Quality Modeling Speak, read and prompt: High-fidelity text-to-speech with minimal super- vision,

Reference 14

Resolution: unresolved; no resolver link, observed 2026-06-27T14:38:44.321577Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1ab9cc7b-3877-485e-9508-36e75acdbe9f · outbound

This paper cites Neural codec language models are zero-shot text to speech synthesizers,.

ANCHOR: Autoregressive Non-intrusive Chunk-Ordered Refinement for Joint Multi-Resolution Speech Quality Modeling Neural codec language models are zero-shot text to speech synthesizers,

Reference 15

Resolution: unresolved; no resolver link, observed 2026-06-27T14:38:44.321577Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 27b09b1c-59f6-493a-bab1-7c87d66ceaf4 · outbound

This paper cites V oicebox: Text-guided multilingual universal speech gener- ation at scale,.

ANCHOR: Autoregressive Non-intrusive Chunk-Ordered Refinement for Joint Multi-Resolution Speech Quality Modeling V oicebox: Text-guided multilingual universal speech gener- ation at scale,

Reference 16

Resolution: unresolved; no resolver link, observed 2026-06-27T14:38:44.321577Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 072dae3a-71c9-4f04-96ae-f0dd99b2e979 · outbound

This paper cites Spark-tts: An efficient llm-based text-to-speech model with single-stream decoupled speech tokens,.

ANCHOR: Autoregressive Non-intrusive Chunk-Ordered Refinement for Joint Multi-Resolution Speech Quality Modeling Spark-tts: An efficient llm-based text-to-speech model with single-stream decoupled speech tokens,

Reference 17

Resolution: unresolved; no resolver link, observed 2026-06-27T14:38:44.321577Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cfeda360-4f03-4746-b8f0-aa063a07b710 · outbound

This paper cites Functional parallelism in spoken word- recognition,.

ANCHOR: Autoregressive Non-intrusive Chunk-Ordered Refinement for Joint Multi-Resolution Speech Quality Modeling Functional parallelism in spoken word- recognition,

Reference 18

Resolution: unresolved; no resolver link, observed 2026-06-27T14:38:44.321577Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ef0b9019-aa73-4598-95e4-815f970d8fe4 · outbound

This paper cites Per- ceptual evaluation of speech quality (PESQ)-a new method for objective intelligibility assessment of narrow-band speech signals, in the phone network,.

ANCHOR: Autoregressive Non-intrusive Chunk-Ordered Refinement for Joint Multi-Resolution Speech Quality Modeling Per- ceptual evaluation of speech quality (PESQ)-a new method for objective intelligibility assessment of narrow-band speech signals, in the phone network,

Reference 19

Resolution: unresolved; no resolver link, observed 2026-06-27T14:38:44.321577Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 11e5bde2-264e-4254-97dc-eb6b5ec0edcc · outbound

This paper cites ViSQOL: an objective speech quality model,.

ANCHOR: Autoregressive Non-intrusive Chunk-Ordered Refinement for Joint Multi-Resolution Speech Quality Modeling ViSQOL: an objective speech quality model,

Reference 20

Resolution: unresolved; no resolver link, observed 2026-06-27T14:38:44.321577Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0c90aa89-a21e-4099-8809-77c849ceab39 · outbound

This paper cites ARECHO: Autoregressive evaluation via chain-based hypothesis optimization for speech multi-metric estimation,.

ANCHOR: Autoregressive Non-intrusive Chunk-Ordered Refinement for Joint Multi-Resolution Speech Quality Modeling ARECHO: Autoregressive evaluation via chain-based hypothesis optimization for speech multi-metric estimation,

Reference 21

Resolution: unresolved; no resolver link, observed 2026-06-27T14:38:44.321577Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 86638084-15fa-4b38-8ccc-891aa8fd5842 · outbound

This paper cites An al- gorithm for intelligibility prediction of time–frequency weighted noisy speech,.

ANCHOR: Autoregressive Non-intrusive Chunk-Ordered Refinement for Joint Multi-Resolution Speech Quality Modeling An al- gorithm for intelligibility prediction of time–frequency weighted noisy speech,

Reference 22

Resolution: unresolved; no resolver link, observed 2026-06-27T14:38:44.321577Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ade5bd79-7fc3-412b-9bc8-6b1254e1b435 · outbound

This paper cites Utmos: Utokyo-sarulab system for voicemos challenge 2022,.

ANCHOR: Autoregressive Non-intrusive Chunk-Ordered Refinement for Joint Multi-Resolution Speech Quality Modeling Utmos: Utokyo-sarulab system for voicemos challenge 2022,

Reference 23

Resolution: unresolved; no resolver link, observed 2026-06-27T14:38:44.321577Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d317b58f-b642-4aa0-9409-06b4410b3a2b · outbound

This paper cites Dnsmos: A non-intrusive perceptual objec- tive speech quality metric to evaluate noise suppressors,.

ANCHOR: Autoregressive Non-intrusive Chunk-Ordered Refinement for Joint Multi-Resolution Speech Quality Modeling Dnsmos: A non-intrusive perceptual objec- tive speech quality metric to evaluate noise suppressors,

Reference 24

Resolution: unresolved; no resolver link, observed 2026-06-27T14:38:44.321577Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 085890ed-88f8-4d9e-9796-506dc2454a0e · outbound

This paper cites Mosnet: Deep learning-based objective assess- ment for voice conversion,.

ANCHOR: Autoregressive Non-intrusive Chunk-Ordered Refinement for Joint Multi-Resolution Speech Quality Modeling Mosnet: Deep learning-based objective assess- ment for voice conversion,

Reference 25

Resolution: unresolved; no resolver link, observed 2026-06-27T14:38:44.321577Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 94b410da-7bff-46be-b956-75f925ba6421 · outbound

This paper cites NORESQA: A Non-reference Speech Quality As- sessment metric using non-matching references,.

ANCHOR: Autoregressive Non-intrusive Chunk-Ordered Refinement for Joint Multi-Resolution Speech Quality Modeling NORESQA: A Non-reference Speech Quality As- sessment metric using non-matching references,

Reference 26

Resolution: unresolved; no resolver link, observed 2026-06-27T14:38:44.321577Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 55b71f80-4b26-4345-9429-4d5eab2b47ae · outbound

This paper cites Nisqa: A deep cnn-self-attention model for multidimensional speech quality pre- diction,.

ANCHOR: Autoregressive Non-intrusive Chunk-Ordered Refinement for Joint Multi-Resolution Speech Quality Modeling Nisqa: A deep cnn-self-attention model for multidimensional speech quality pre- diction,

Reference 27

Resolution: unresolved; no resolver link, observed 2026-06-27T14:38:44.321577Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e151dd61-03f4-4d00-a379-bda8566153e6 · outbound

This paper cites Nomad: Unsupervised learning of perceptual embeddings for speech enhancement and non-matching reference audio quality assessment,.

ANCHOR: Autoregressive Non-intrusive Chunk-Ordered Refinement for Joint Multi-Resolution Speech Quality Modeling Nomad: Unsupervised learning of perceptual embeddings for speech enhancement and non-matching reference audio quality assessment,

Reference 28

Resolution: unresolved; no resolver link, observed 2026-06-27T14:38:44.321577Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 883b7103-6aa1-4c1d-ae99-0f20b7b44dd7 · outbound

This paper cites Songeval: A benchmark for automatic music aes- thetic evaluation,.

ANCHOR: Autoregressive Non-intrusive Chunk-Ordered Refinement for Joint Multi-Resolution Speech Quality Modeling Songeval: A benchmark for automatic music aes- thetic evaluation,

Reference 29

Resolution: unresolved; no resolver link, observed 2026-06-27T14:38:44.321577Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8f7be793-603c-4d35-a011-ac30aad57b66 · outbound

This paper cites Meta audiobox aesthetics: Uni- fied automatic quality assessment for speech, music, and sound,.

ANCHOR: Autoregressive Non-intrusive Chunk-Ordered Refinement for Joint Multi-Resolution Speech Quality Modeling Meta audiobox aesthetics: Uni- fied automatic quality assessment for speech, music, and sound,

Reference 30

Resolution: unresolved; no resolver link, observed 2026-06-27T14:38:44.321577Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 11f24525-da0a-443c-8a65-ab5996887690 · outbound

This paper cites Urgentmos: Unified multi-metric and preference learning for robust speech quality assessment,.

ANCHOR: Autoregressive Non-intrusive Chunk-Ordered Refinement for Joint Multi-Resolution Speech Quality Modeling Urgentmos: Unified multi-metric and preference learning for robust speech quality assessment,

Reference 31

Resolution: unresolved; no resolver link, observed 2026-06-27T14:38:44.321577Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 352d8889-0c84-4467-9443-d5c6b360e833 · outbound

This paper cites Universa: Unified and versatile evaluation for speech and audio,.

ANCHOR: Autoregressive Non-intrusive Chunk-Ordered Refinement for Joint Multi-Resolution Speech Quality Modeling Universa: Unified and versatile evaluation for speech and audio,

Reference 32

Resolution: unresolved; no resolver link, observed 2026-06-27T14:38:44.321577Z

Source-reported events for the cited work

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Observation 24a8ad27-17ec-494e-8b0f-f5a2a9637241 · outbound

This paper cites To- wards frame-level quality predictions of synthetic speech,.

ANCHOR: Autoregressive Non-intrusive Chunk-Ordered Refinement for Joint Multi-Resolution Speech Quality Modeling To- wards frame-level quality predictions of synthetic speech,

Reference 33

Resolution: unresolved; no resolver link, observed 2026-06-27T14:38:44.321577Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 14e93bcb-1bbd-47b0-a2bd-182345951b4f · outbound

This paper cites Chunk based speech pre-training with high resolution finite scalar quantization,.

ANCHOR: Autoregressive Non-intrusive Chunk-Ordered Refinement for Joint Multi-Resolution Speech Quality Modeling Chunk based speech pre-training with high resolution finite scalar quantization,

Reference 34

Resolution: unresolved; no resolver link, observed 2026-06-27T14:38:44.321577Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 25790b1f-cf2d-4b8d-bf05-1924133ac042 · outbound

This paper cites Layer-wise analysis of a self-supervised speech representation model,.

ANCHOR: Autoregressive Non-intrusive Chunk-Ordered Refinement for Joint Multi-Resolution Speech Quality Modeling Layer-wise analysis of a self-supervised speech representation model,

Reference 35

Resolution: unresolved; no resolver link, observed 2026-06-27T14:38:44.321577Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ceb504ad-fa49-4daa-af10-5b5f6fce4019 · outbound

This paper cites Streaming automatic speech recognition with the transformer model,.

ANCHOR: Autoregressive Non-intrusive Chunk-Ordered Refinement for Joint Multi-Resolution Speech Quality Modeling Streaming automatic speech recognition with the transformer model,

Reference 36

Resolution: unresolved; no resolver link, observed 2026-06-27T14:38:44.321577Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9440d489-36fe-40f5-b83e-d8b242bec7bd · outbound

This paper cites Aishell-1: An open- source mandarin speech corpus and a speech recognition baseline,.

ANCHOR: Autoregressive Non-intrusive Chunk-Ordered Refinement for Joint Multi-Resolution Speech Quality Modeling Aishell-1: An open- source mandarin speech corpus and a speech recognition baseline,

Reference 37

Resolution: unresolved; no resolver link, observed 2026-06-27T14:38:44.321577Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d43c2e48-fd6a-42c8-ac63-9c743bc96dff · outbound

This paper cites The ami meeting corpus,.

ANCHOR: Autoregressive Non-intrusive Chunk-Ordered Refinement for Joint Multi-Resolution Speech Quality Modeling The ami meeting corpus,

Reference 38

Resolution: unresolved; no resolver link, observed 2026-06-27T14:38:44.321577Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 243cd194-353a-45d0-b263-f310e27f4c6d · outbound

This paper cites Common voice: A massively-multilingual speech corpus,.

ANCHOR: Autoregressive Non-intrusive Chunk-Ordered Refinement for Joint Multi-Resolution Speech Quality Modeling Common voice: A massively-multilingual speech corpus,

Reference 39

Resolution: unresolved; no resolver link, observed 2026-06-27T14:38:44.321577Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1e9dc2b8-eef0-44b0-9e47-80afb0ae0107 · outbound

This paper cites Urgent challenge: Uni- versality, robustness, and generalizability for speech enhancement,.

ANCHOR: Autoregressive Non-intrusive Chunk-Ordered Refinement for Joint Multi-Resolution Speech Quality Modeling Urgent challenge: Uni- versality, robustness, and generalizability for speech enhancement,

Reference 40

Resolution: unresolved; no resolver link, observed 2026-06-27T14:38:44.321577Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 52c0e043-cb43-4596-adb0-30ca58dbe38c · outbound

This paper cites The voice bank corpus: De- sign, collection and data analysis of a large regional accent speech database,.

ANCHOR: Autoregressive Non-intrusive Chunk-Ordered Refinement for Joint Multi-Resolution Speech Quality Modeling The voice bank corpus: De- sign, collection and data analysis of a large regional accent speech database,

Reference 41

Resolution: unresolved; no resolver link, observed 2026-06-27T14:38:44.321577Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d8506450-e893-4fe0-9f07-41bb4390ca9c · outbound

This paper cites The diverse environments multi-channel acoustic noise database (demand),.

ANCHOR: Autoregressive Non-intrusive Chunk-Ordered Refinement for Joint Multi-Resolution Speech Quality Modeling The diverse environments multi-channel acoustic noise database (demand),

Reference 42

Resolution: unresolved; no resolver link, observed 2026-06-27T14:38:44.321577Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6ec8bb5e-e8f4-4e6b-af16-b545f4f97947 · outbound

This paper cites The voicemos challenge 2022,.

ANCHOR: Autoregressive Non-intrusive Chunk-Ordered Refinement for Joint Multi-Resolution Speech Quality Modeling The voicemos challenge 2022,

Reference 43

Resolution: unresolved; no resolver link, observed 2026-06-27T14:38:44.321577Z

Source-reported events for the cited work

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Observation afc89261-c390-4adf-b902-82136ed85e04 · outbound

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

ANCHOR: Autoregressive Non-intrusive Chunk-Ordered Refinement for Joint Multi-Resolution Speech Quality Modeling Wavlm: Large-scale self-supervised pre-training for full stack speech processing,

Reference 44

Resolution: unresolved; no resolver link, observed 2026-06-27T14:38:44.321577Z

Source-reported events for the cited work

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Observation 3b95bcd8-5d2b-462e-8ac7-b0664ce123ed · outbound

This paper cites XSEDE: Accelerating scientific discovery,.

ANCHOR: Autoregressive Non-intrusive Chunk-Ordered Refinement for Joint Multi-Resolution Speech Quality Modeling XSEDE: Accelerating scientific discovery,

Reference 45

Resolution: malformed identifier; no resolver link, observed 2026-06-27T14:38:44.321577Z

Source-reported events for the cited work

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Observation d863c121-0604-4db9-9890-bdc5965c8831 · outbound

This paper cites Bridges: a uniquely flexible HPC resource for new communities and data analytics,.

ANCHOR: Autoregressive Non-intrusive Chunk-Ordered Refinement for Joint Multi-Resolution Speech Quality Modeling Bridges: a uniquely flexible HPC resource for new communities and data analytics,

Reference 46

Resolution: unresolved; no resolver link, observed 2026-06-27T14:38:44.321577Z

Source-reported events for the cited work

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Observation 2417cdfd-50f5-478f-8dcf-4793a4650ece · outbound

This paper cites ACCESS: Advancing innovation: NSF’s advanced cyberinfrastruc- ture coordination ecosystem: Services & support,.

ANCHOR: Autoregressive Non-intrusive Chunk-Ordered Refinement for Joint Multi-Resolution Speech Quality Modeling ACCESS: Advancing innovation: NSF’s advanced cyberinfrastruc- ture coordination ecosystem: Services & support,

Reference 47

Resolution: unresolved; no resolver link, observed 2026-06-27T14:38:44.321577Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation ddaaa18d-1c72-4497-a10d-c340d2b56880 · inbound