Paper Citation Record · LEDGER

Improving Speech Enhancement with Multi-Metric Supervision from Learned Quality Assessment

As of 8 August 2026, this Paper Citation Record lists 54 of 54 outbound references and 1 inbound Pith citation observation for arXiv:2506.12260.

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

pith.paper-citation-record.v1
2506.12260 v2

Coverage vector

measured 54 of 54 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T00:59:56.303718Z

measured 55 of 55 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 2026-08-06T21:34:07.924156Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T21:34:11.220887Z

Reference resolution

54 of 54 outbound references displayed

verified exact4
verified fuzzy40
unresolved10
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b28c77b7-c622-455f-8923-0c0497d98042 · outbound

This paper cites an unresolved cited work.

Improving Speech Enhancement with Multi-Metric Supervision from Learned Quality Assessment Unresolved cited work

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-07T00:59:51.318929Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cf9aca71-7c68-471f-8309-c9ab7386e0d9 · outbound

This paper cites SDR–half- baked or well done?.

Improving Speech Enhancement with Multi-Metric Supervision from Learned Quality Assessment SDR–half- baked or well done?

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:00:02.810913Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 21a0fe25-e3cb-480e-8759-75a7212852d2 · outbound

This paper cites How bad are artifacts?: Analyzing the impact of speech enhancement errors on asr,.

Improving Speech Enhancement with Multi-Metric Supervision from Learned Quality Assessment How bad are artifacts?: Analyzing the impact of speech enhancement errors on asr,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:00:02.732807Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 462bd6d8-9579-48ab-8a2b-b97a2c17bb4b · outbound

This paper cites Bridging the gap between monaural speech enhancement and recognition with distortion-independent acous- tic modeling,.

Improving Speech Enhancement with Multi-Metric Supervision from Learned Quality Assessment Bridging the gap between monaural speech enhancement and recognition with distortion-independent acous- tic modeling,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:00:02.663269Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 18d0c539-84f8-47f7-a0f3-de04eb4b5ebe · outbound

This paper cites Advancing non-intrusive suppression on enhancement distortion for noise robust asr,.

Improving Speech Enhancement with Multi-Metric Supervision from Learned Quality Assessment Advancing non-intrusive suppression on enhancement distortion for noise robust asr,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:00:02.606075Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 2c90d128-7dfd-4885-bdaa-c7e8af5ba188 · outbound

This paper cites Fat-hubert: Front-end adaptive training of hidden-unit bert for distortion-invariant robust speech recognition,.

Improving Speech Enhancement with Multi-Metric Supervision from Learned Quality Assessment Fat-hubert: Front-end adaptive training of hidden-unit bert for distortion-invariant robust speech recognition,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:00:02.555239Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation aa56e567-42db-46b9-8ad8-67614693cccb · outbound

This paper cites Closing the gap between time-domain multi-channel speech enhancement on real and simulation conditions,.

Improving Speech Enhancement with Multi-Metric Supervision from Learned Quality Assessment Closing the gap between time-domain multi-channel speech enhancement on real and simulation conditions,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:00:02.496086Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 799acbfa-1e7f-4781-8821-d5544ec02d31 · outbound

This paper cites Less is More: Data Curation Matters in Scaling Speech Enhancement.

Improving Speech Enhancement with Multi-Metric Supervision from Learned Quality Assessment Less is More: Data Curation Matters in Scaling Speech Enhancement

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T00:59:52.138592Z

Source-reported events for the cited work

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Observation 96a43799-7db9-4a3f-874e-205fe6af9ebb · outbound

This paper cites Lightweight Front-end Enhancement for Robust ASR via Frame Resampling and Sub-Band Pruning,.

Improving Speech Enhancement with Multi-Metric Supervision from Learned Quality Assessment Lightweight Front-end Enhancement for Robust ASR via Frame Resampling and Sub-Band Pruning,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:00:02.437242Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 71ce7602-6300-4836-a3d3-a682f31ac579 · outbound

This paper cites A review on subjective and objective evaluation of synthetic speech,.

Improving Speech Enhancement with Multi-Metric Supervision from Learned Quality Assessment A review on subjective and objective evaluation of synthetic speech,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:00:02.156596Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 9b077439-c7e1-4fdf-9589-6e8474f368cc · outbound

This paper cites Objective measures of perceptual audio quality reviewed: An evaluation of their application domain dependence,.

Improving Speech Enhancement with Multi-Metric Supervision from Learned Quality Assessment Objective measures of perceptual audio quality reviewed: An evaluation of their application domain dependence,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:00:01.982525Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 3e5aa4c9-92f2-4de0-b13b-3d3faf4c71ad · outbound

This paper cites Versa: A versatile evaluation toolkit for speech, audio, and music,.

Improving Speech Enhancement with Multi-Metric Supervision from Learned Quality Assessment Versa: A versatile evaluation toolkit for speech, audio, and music,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:00:01.716700Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 5d88ab18-9866-414a-93e4-188c6102559e · outbound

This paper cites Lessons Learned from the URGENT 2024 Speech Enhancement Challenge.

Improving Speech Enhancement with Multi-Metric Supervision from Learned Quality Assessment Lessons Learned from the URGENT 2024 Speech Enhancement Challenge

Reference 13

Resolution: verified exact; local_arxiv, observed 2026-08-07T00:59:56.812979Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 9fda4650-5519-426c-ad6a-23f20fcf6493 · outbound

This paper cites Meta Audiobox Aesthetics: Unified Automatic Quality Assessment for Speech, Music, and Sound.

Improving Speech Enhancement with Multi-Metric Supervision from Learned Quality Assessment Meta Audiobox Aesthetics: Unified Automatic Quality Assessment for Speech, Music, and Sound

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-07T00:59:52.863711Z

Source-reported events for the cited work

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Observation 80f9f217-b210-4834-896a-ec540a5dcbd5 · outbound

This paper cites DNSMOS P.835: A non-intrusive perceptual objective speech quality metric to evaluate noise suppressors,.

Improving Speech Enhancement with Multi-Metric Supervision from Learned Quality Assessment DNSMOS P.835: A non-intrusive perceptual objective speech quality metric to evaluate noise suppressors,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:00:01.527396Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 27c49265-0fba-42b5-bd78-2e6f52b627d0 · outbound

This paper cites UTMOS: UTokyo-SaruLab system for V oiceMOS chal- lenge 2022,.

Improving Speech Enhancement with Multi-Metric Supervision from Learned Quality Assessment UTMOS: UTokyo-SaruLab system for V oiceMOS chal- lenge 2022,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:00:01.324060Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 97c161ad-e9fe-4bc3-9e0e-38510567681c · outbound

This paper cites The t05 system for the voicemos challenge 2024: Transfer learning from deep image classifier to naturalness mos prediction of high-quality synthetic speech,.

Improving Speech Enhancement with Multi-Metric Supervision from Learned Quality Assessment The t05 system for the voicemos challenge 2024: Transfer learning from deep image classifier to naturalness mos prediction of high-quality synthetic speech,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:00:01.010390Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 526ae2a3-fbfd-4f51-bcc8-6f7dc5585c70 · outbound

This paper cites The voicemos challenge 2022,.

Improving Speech Enhancement with Multi-Metric Supervision from Learned Quality Assessment The voicemos challenge 2022,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:00:00.617091Z

Source-reported events for the cited work

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Observation 73aad329-0b7a-4d60-9102-eb326a1451c0 · outbound

This paper cites The voicemos challenge 2023: Zero-shot subjective speech quality prediction for multiple domains,.

Improving Speech Enhancement with Multi-Metric Supervision from Learned Quality Assessment The voicemos challenge 2023: Zero-shot subjective speech quality prediction for multiple domains,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:00:00.399408Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation b1911d94-4095-45af-a45c-c3fd70cc2894 · outbound

This paper cites The voicemos challenge 2024: Beyond speech quality prediction,.

Improving Speech Enhancement with Multi-Metric Supervision from Learned Quality Assessment The voicemos challenge 2024: Beyond speech quality prediction,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:00:00.262689Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 828a28ec-a6a1-4453-be17-03e14ef6c3ef · outbound

This paper cites URGENT-PK: Perceptually-Aligned Ranking Model Designed for Speech Enhancement Competition.

Improving Speech Enhancement with Multi-Metric Supervision from Learned Quality Assessment URGENT-PK: Perceptually-Aligned Ranking Model Designed for Speech Enhancement Competition

Reference 21

Resolution: verified exact; local_arxiv, observed 2026-08-07T00:59:56.682451Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 1610e23b-d9f4-4649-8891-e3c20ab1fbde · outbound

This paper cites ICASSP 2024 speech signal improvement challenge,.

Improving Speech Enhancement with Multi-Metric Supervision from Learned Quality Assessment ICASSP 2024 speech signal improvement challenge,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:00:00.101072Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 64a7a598-988f-45c9-8b04-891bd755a587 · outbound

This paper cites Uni-VERSA: Versatile Speech Assessment with a Unified Network.

Improving Speech Enhancement with Multi-Metric Supervision from Learned Quality Assessment Uni-VERSA: Versatile Speech Assessment with a Unified Network

Reference 23

Resolution: verified exact; local_arxiv, observed 2026-08-07T00:59:56.557082Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation c6de50a5-1516-4526-a048-fd359071ccdd · outbound

This paper cites Perceptual evaluation of speech quality (PESQ)—a new method for speech quality assessment of telephone networks and codecs,.

Improving Speech Enhancement with Multi-Metric Supervision from Learned Quality Assessment Perceptual evaluation of speech quality (PESQ)—a new method for speech quality assessment of telephone networks and codecs,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:59:59.954336Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 717af5b2-ce14-497d-a98e-e3e55a746213 · outbound

This paper cites Perceptual objective listening quality assess- ment (POLQA), the third generation ITU-T standard for end-to-end speech quality measurement part I–—temporal alignment,.

Improving Speech Enhancement with Multi-Metric Supervision from Learned Quality Assessment Perceptual objective listening quality assess- ment (POLQA), the third generation ITU-T standard for end-to-end speech quality measurement part I–—temporal alignment,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:59:59.760642Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 286b5014-978a-4f2d-a3a5-d389b67e1ec7 · outbound

This paper cites URGENT challenge: Universality, robustness, and generalizability for speech en- hancement,.

Improving Speech Enhancement with Multi-Metric Supervision from Learned Quality Assessment URGENT challenge: Universality, robustness, and generalizability for speech en- hancement,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:59:59.624900Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation b3bbf6c2-0e84-4dc6-8791-bbab95095f28 · outbound

This paper cites Inter- speech 2025 URGENT speech enhancement challenge,.

Improving Speech Enhancement with Multi-Metric Supervision from Learned Quality Assessment Inter- speech 2025 URGENT speech enhancement challenge,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:59:59.472832Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 13f11994-095c-42dd-ac5b-d32284d9a7c2 · outbound

This paper cites Performance measurement in blind audio source separation,.

Improving Speech Enhancement with Multi-Metric Supervision from Learned Quality Assessment Performance measurement in blind audio source separation,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:59:59.343918Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 78437f9c-7a8c-442d-8745-7c857bbeb1ab · outbound

This paper cites Distillation and pruning for scalable self- supervised representation-based speech quality assessment,.

Improving Speech Enhancement with Multi-Metric Supervision from Learned Quality Assessment Distillation and pruning for scalable self- supervised representation-based speech quality assessment,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:59:59.213900Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation daf7cdf0-5a0b-4cd1-a709-c00337bfc8d7 · outbound

This paper cites NISQA: A deep CNN- self-attention model for multidimensional speech quality prediction with crowdsourced datasets,.

Improving Speech Enhancement with Multi-Metric Supervision from Learned Quality Assessment NISQA: A deep CNN- self-attention model for multidimensional speech quality prediction with crowdsourced datasets,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:59:59.041433Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 963dbb25-bd7e-4808-9049-20944ecea082 · outbound

This paper cites SCOREQ: Speech quality assessment with contrastive regression,.

Improving Speech Enhancement with Multi-Metric Supervision from Learned Quality Assessment SCOREQ: Speech quality assessment with contrastive regression,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:59:58.879269Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 0faae484-a6a3-4fa9-b9cf-a0852255993b · outbound

This paper cites Owsm v3. 1: Better and faster open whisper-style speech models based on e-branchformer,.

Improving Speech Enhancement with Multi-Metric Supervision from Learned Quality Assessment Owsm v3. 1: Better and faster open whisper-style speech models based on e-branchformer,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:59:58.708717Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 39fe393c-1152-4e33-bc00-37f251892288 · outbound

This paper cites An algorithm for predicting the intelligibility of speech masked by modulated noise maskers,.

Improving Speech Enhancement with Multi-Metric Supervision from Learned Quality Assessment An algorithm for predicting the intelligibility of speech masked by modulated noise maskers,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:59:58.586149Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 7be65e64-7583-49de-98a1-d3ab0c68ef69 · outbound

This paper cites SpeechBERTScore: Reference-aware automatic evaluation of speech generation leveraging NLP evaluation metrics,.

Improving Speech Enhancement with Multi-Metric Supervision from Learned Quality Assessment SpeechBERTScore: Reference-aware automatic evaluation of speech generation leveraging NLP evaluation metrics,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:59:58.488141Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 5acf0661-06e7-448f-80d5-79851f3403fe · outbound

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

Improving Speech Enhancement with Multi-Metric Supervision from Learned Quality Assessment Hubert: Self-supervised speech representation learning by masked prediction of hidden units,

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-07T00:59:55.245748Z

Source-reported events for the cited work

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Observation 4abb97a3-c6e6-43af-b5f2-a7c70b786a03 · outbound

This paper cites Evaluation metrics for generative speech enhancement methods: Issues and perspectives,.

Improving Speech Enhancement with Multi-Metric Supervision from Learned Quality Assessment Evaluation metrics for generative speech enhancement methods: Issues and perspectives,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:59:58.367515Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation ba36eb9c-7f0d-4ea1-bdc6-2d178ed17c46 · outbound

This paper cites Espnet-spk: full pipeline speaker embedding toolkit with reproducible recipes, self- supervised front-ends, and off-the-shelf models,.

Improving Speech Enhancement with Multi-Metric Supervision from Learned Quality Assessment Espnet-spk: full pipeline speaker embedding toolkit with reproducible recipes, self- supervised front-ends, and off-the-shelf models,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:59:58.188012Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 825bc888-e9c2-43d5-bc37-41bf4fb89d03 · outbound

This paper cites Mel-cepstral distance measure for objective speech qual- ity assessment,.

Improving Speech Enhancement with Multi-Metric Supervision from Learned Quality Assessment Mel-cepstral distance measure for objective speech qual- ity assessment,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:59:58.069927Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation f53e7362-7fc5-4143-8137-8d17d957a590 · outbound

This paper cites Lessons learned from the URGENT 2024 speech enhancement chal- lenge,.

Improving Speech Enhancement with Multi-Metric Supervision from Learned Quality Assessment Lessons learned from the URGENT 2024 speech enhancement chal- lenge,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:59:57.928233Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation f8d7e008-305d-4c47-a548-798d160bd59d · outbound

This paper cites Distance measures for speech processing,.

Improving Speech Enhancement with Multi-Metric Supervision from Learned Quality Assessment Distance measures for speech processing,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:59:57.771171Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 7b40b310-2311-414f-955d-0e1c5e80c18d · outbound

This paper cites SHEET: A Multi-purpose Open-source Speech Human Evaluation Estimation Toolkit.

Improving Speech Enhancement with Multi-Metric Supervision from Learned Quality Assessment SHEET: A Multi-purpose Open-source Speech Human Evaluation Estimation Toolkit

Reference 41

Resolution: verified exact; local_arxiv, observed 2026-08-07T00:59:56.456405Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 3013255a-d3d3-4827-bc4f-2c9f25c1cac1 · outbound

This paper cites The chime-7 udase task: Unsupervised domain adaptation for conversational speech enhancement,.

Improving Speech Enhancement with Multi-Metric Supervision from Learned Quality Assessment The chime-7 udase task: Unsupervised domain adaptation for conversational speech enhancement,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:59:57.667117Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation fba4b467-5ee4-4b4f-8a1b-3e52edcded0e · outbound

This paper cites Generalization ability of mos prediction networks,.

Improving Speech Enhancement with Multi-Metric Supervision from Learned Quality Assessment Generalization ability of mos prediction networks,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:59:57.516889Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation dcf98de6-a306-46dd-a800-20bd7f478278 · outbound

This paper cites The blizzard challenge 2019,.

Improving Speech Enhancement with Multi-Metric Supervision from Learned Quality Assessment The blizzard challenge 2019,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:59:57.400223Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 6cc6fd5e-383a-4eef-a2d3-8f238e7618a1 · outbound

This paper cites Mos-bench: Benchmarking generalization abilities of subjective speech quality assessment models,.

Improving Speech Enhancement with Multi-Metric Supervision from Learned Quality Assessment Mos-bench: Benchmarking generalization abilities of subjective speech quality assessment models,

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-07T00:59:55.841645Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 57d83909-e1ff-4e8e-9e5e-0ce9d9f0bbdd · outbound

This paper cites The INTERSPEECH 2020 deep noise suppression challenge: Datasets, subjective testing framework, and challenge results,.

Improving Speech Enhancement with Multi-Metric Supervision from Learned Quality Assessment The INTERSPEECH 2020 deep noise suppression challenge: Datasets, subjective testing framework, and challenge results,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:59:57.250392Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 26c706da-74de-42f9-9042-ce318aa2c9fb · outbound

This paper cites An analysis of environment, microphone and data simulation mismatches in robust speech recognition,.

Improving Speech Enhancement with Multi-Metric Supervision from Learned Quality Assessment An analysis of environment, microphone and data simulation mismatches in robust speech recognition,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:59:57.155828Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 7dd16f2b-a7b8-4757-87ff-b1e5e21a8ad7 · outbound

This paper cites ESPnet: End-to-End Speech Processing Toolkit.

Improving Speech Enhancement with Multi-Metric Supervision from Learned Quality Assessment ESPnet: End-to-End Speech Processing Toolkit

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-07T00:59:56.058833Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b99c0718-0b12-4817-8cb4-94b26172514d · outbound

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

Improving Speech Enhancement with Multi-Metric Supervision from Learned Quality Assessment Wavlm: Large-scale self-supervised pre- training for full stack speech processing,

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-07T00:59:56.102596Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 336466e3-0897-4f1e-822f-4945ea164596 · outbound

This paper cites SUPERB: Speech Processing Universal PERformance Benchmark,.

Improving Speech Enhancement with Multi-Metric Supervision from Learned Quality Assessment SUPERB: Speech Processing Universal PERformance Benchmark,

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-07T00:59:56.156431Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5a8b846c-7665-4d28-965c-27e0a789b056 · outbound

This paper cites Music source separation with band-split rnn,.

Improving Speech Enhancement with Multi-Metric Supervision from Learned Quality Assessment Music source separation with band-split rnn,

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:59:57.051037Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 6fdeea55-fb72-4c5b-b4ea-702eb9a77ec6 · outbound

This paper cites Towards deep learning models resistant to adversarial attacks,.

Improving Speech Enhancement with Multi-Metric Supervision from Learned Quality Assessment Towards deep learning models resistant to adversarial attacks,

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-07T00:59:56.261770Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7e6c78d8-7051-49ec-9026-26acd3bf90bd · outbound

This paper cites Adversarial attacks on automatic speech recognition (asr): A survey,.

Improving Speech Enhancement with Multi-Metric Supervision from Learned Quality Assessment Adversarial attacks on automatic speech recognition (asr): A survey,

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:59:56.935708Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 0ec3ff65-a3be-4a88-863f-a0c4a7c59ef8 · outbound

This paper cites MOS-Bench: Benchmarking Generalization Abilities of Subjective Speech Quality Assessment Models.

Improving Speech Enhancement with Multi-Metric Supervision from Learned Quality Assessment MOS-Bench: Benchmarking Generalization Abilities of Subjective Speech Quality Assessment Models

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-07T00:59:55.909879Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 3fbac6c8-1f69-4e11-b181-9c5c61e0a827 · inbound

Less is More: Data Curation Matters in Scaling Speech Enhancement cites this paper.

Less is More: Data Curation Matters in Scaling Speech Enhancement Improving Speech Enhancement with Multi-Metric Supervision from Learned Quality Assessment

Reference 7

Resolution: verified exact; local_arxiv, observed 2026-08-06T21:34:11.310798Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.