Exploring Length Generalization For Transformer-based Speech Enhancement | Paper Citation Record

Observation 1352abb5-de50-45f9-9bed-2ae538b5b012 · outbound

This paper cites an unresolved cited work.

Exploring Length Generalization For Transformer-based Speech Enhancement Unresolved cited work

Reference 1

Resolution: unresolved; raw_fallback, observed 2026-08-07T05:59:49.781913Z

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Observation 4b9bd109-714e-4638-b4ca-266d62e32dcb · outbound

This paper cites Suppression of acoustic noise in speech using spectral subtrac- tion,.

Exploring Length Generalization For Transformer-based Speech Enhancement Suppression of acoustic noise in speech using spectral subtrac- tion,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:59:49.766070Z

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Observation 2be40ce0-6747-4a19-8c24-7b85eb7cf64c · outbound

This paper cites Speech Enhancement Using a Minimum Mean-Square Error Short-Time Spectral Amplitude Estimator,.

Exploring Length Generalization For Transformer-based Speech Enhancement Speech Enhancement Using a Minimum Mean-Square Error Short-Time Spectral Amplitude Estimator,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:59:49.750493Z

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Observation 936e8bcf-b573-4c81-ad75-d760d26aade8 · outbound

This paper cites On MMSE-based estimation of amplitude and complex speech spectral coefficients under phase- uncertainty,.

Exploring Length Generalization For Transformer-based Speech Enhancement On MMSE-based estimation of amplitude and complex speech spectral coefficients under phase- uncertainty,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:59:49.734074Z

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Observation 789f86d2-350b-47f8-ab65-5a4b239d231f · outbound

This paper cites A novel fast nonstationary noise tracking approach based on mmse spectral power estimator,.

Exploring Length Generalization For Transformer-based Speech Enhancement A novel fast nonstationary noise tracking approach based on mmse spectral power estimator,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:59:49.717353Z

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Observation 01d6acee-f045-43fa-b5cf-5280b9d91adf · outbound

This paper cites Speech enhancement based on a priori signal to noise estimation,.

Exploring Length Generalization For Transformer-based Speech Enhancement Speech enhancement based on a priori signal to noise estimation,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:59:49.701298Z

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Observation 1105db2c-2f45-4002-979c-10e2eed01f75 · outbound

This paper cites Supervised speech separation based on deep learning: An overview,.

Exploring Length Generalization For Transformer-based Speech Enhancement Supervised speech separation based on deep learning: An overview,

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-07T05:59:48.391195Z

Source-reported events for the cited work

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Observation 20478096-6292-495c-99e5-d1f2bf9ae5b0 · outbound

This paper cites Deep neural network techniques for monaural speech enhancement: state of the art analysis.

Exploring Length Generalization For Transformer-based Speech Enhancement Deep neural network techniques for monaural speech enhancement: state of the art analysis

Reference 8

Resolution: verified exact; local_arxiv, observed 2026-08-07T05:59:48.831365Z

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Observation 38b2131e-dab2-4edb-996e-ee9d6102e0ce · outbound

This paper cites Speech denoising in the waveform domain with self-attention,.

Exploring Length Generalization For Transformer-based Speech Enhancement Speech denoising in the waveform domain with self-attention,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:59:49.674306Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation b2c264a9-a4dd-430b-bf34-f5570f7f55db · outbound

This paper cites Masked multi-head self-attention for causal speech enhancement,.

Exploring Length Generalization For Transformer-based Speech Enhancement Masked multi-head self-attention for causal speech enhancement,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:59:49.658864Z

Source-reported events for the cited work

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Observation bf7b63aa-5301-44aa-a8a9-e35274fea426 · outbound

This paper cites Monaural speech derever- beration using temporal convolutional networks with self attention,.

Exploring Length Generalization For Transformer-based Speech Enhancement Monaural speech derever- beration using temporal convolutional networks with self attention,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:59:49.643736Z

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Observation 0dcd9019-22ca-4f98-bf70-b495f9f9f66e · outbound

This paper cites T-GSA: Transformer with gaussian- weighted self-attention for speech enhancement,.

Exploring Length Generalization For Transformer-based Speech Enhancement T-GSA: Transformer with gaussian- weighted self-attention for speech enhancement,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:59:49.629209Z

Source-reported events for the cited work

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Observation ab2e74fa-9654-4d3b-a16b-467eb692afa9 · outbound

This paper cites Noisy-reverberant speech enhancement using denseunet with time-frequency attention.

Exploring Length Generalization For Transformer-based Speech Enhancement Noisy-reverberant speech enhancement using denseunet with time-frequency attention

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:59:49.613471Z

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Observation 99dfb5fe-953e-4c1d-84c7-db221349bdea · outbound

This paper cites Ripple sparse self-attention for monaural speech enhancement,.

Exploring Length Generalization For Transformer-based Speech Enhancement Ripple sparse self-attention for monaural speech enhancement,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:59:49.596110Z

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Observation 0ec98579-dba7-4ac0-aaaa-4ff3981f283c · outbound

This paper cites Conformer: Convolution-augmented Transformer for Speech Recognition,.

Exploring Length Generalization For Transformer-based Speech Enhancement Conformer: Convolution-augmented Transformer for Speech Recognition,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:59:49.581889Z

Source-reported events for the cited work

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Observation fcc9e7e1-de12-4de1-843a-95c783d7e699 · outbound

This paper cites Exploring length generalization in large language models,.

Exploring Length Generalization For Transformer-based Speech Enhancement Exploring length generalization in large language models,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:59:49.566837Z

Source-reported events for the cited work

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Observation f0aa2558-e842-4e72-a649-04b733878456 · outbound

This paper cites An exploration of length generalization in transformer-based speech enhancement,.

Exploring Length Generalization For Transformer-based Speech Enhancement An exploration of length generalization in transformer-based speech enhancement,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:59:49.552594Z

Source-reported events for the cited work

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Observation bc74a50d-0604-407c-a5ca-983f58852d39 · outbound

This paper cites Attention is all you need,.

Exploring Length Generalization For Transformer-based Speech Enhancement Attention is all you need,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:59:49.537923Z

Source-reported events for the cited work

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Observation 48bc97a4-5a88-40cb-abc8-780cb79dab32 · outbound

This paper cites Exploring the limits of transfer learning with a unified text-to-text transformer.

Exploring Length Generalization For Transformer-based Speech Enhancement Exploring the limits of transfer learning with a unified text-to-text transformer

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-07T05:59:48.448022Z

Source-reported events for the cited work

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Observation 4d4d48fd-7802-4ed9-a44f-4f610911cb89 · outbound

This paper cites The case for translation-invariant self- attention in transformer-based language models,.

Exploring Length Generalization For Transformer-based Speech Enhancement The case for translation-invariant self- attention in transformer-based language models,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:59:49.513259Z

Source-reported events for the cited work

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Observation 9dd2a843-05b6-4787-8a0d-3ff57546000e · outbound

This paper cites Kerple: Kernelized relative positional embedding for length extrapolation,.

Exploring Length Generalization For Transformer-based Speech Enhancement Kerple: Kernelized relative positional embedding for length extrapolation,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:59:49.497754Z

Source-reported events for the cited work

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Observation f01d2629-6051-46e3-aa6b-c4afb43d473f · outbound

This paper cites SEGAN: Speech enhancement generative adversarial network,.

Exploring Length Generalization For Transformer-based Speech Enhancement SEGAN: Speech enhancement generative adversarial network,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:59:49.481891Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 0834a0e3-6ba7-47d4-995a-c589a495fa4b · outbound

This paper cites Raw waveform-based speech enhancement by fully convolutional networks,.

Exploring Length Generalization For Transformer-based Speech Enhancement Raw waveform-based speech enhancement by fully convolutional networks,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:59:49.468109Z

Source-reported events for the cited work

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Observation ce5052f2-6e19-481e-a5d8-252772792b6c · outbound

This paper cites On loss functions for supervised monaural time-domain speech enhancement,.

Exploring Length Generalization For Transformer-based Speech Enhancement On loss functions for supervised monaural time-domain speech enhancement,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:59:49.452887Z

Source-reported events for the cited work

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Observation f6bdb590-f723-45f7-9a4b-74029f58be2e · outbound

This paper cites End-to-end waveform utterance enhancement for direct evaluation metrics optimiza- tion by fully convolutional neural networks,.

Exploring Length Generalization For Transformer-based Speech Enhancement End-to-end waveform utterance enhancement for direct evaluation metrics optimiza- tion by fully convolutional neural networks,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:59:49.439175Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 7fd5d773-8278-424f-966b-a8561d82ee50 · outbound

This paper cites Real time speech enhancement in the waveform domain,.

Exploring Length Generalization For Transformer-based Speech Enhancement Real time speech enhancement in the waveform domain,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:59:49.424727Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation b3448ba2-8bc1-4198-b7d3-6803631a272d · outbound

This paper cites A regression approach to speech enhancement based on deep neural networks,.

Exploring Length Generalization For Transformer-based Speech Enhancement A regression approach to speech enhancement based on deep neural networks,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:59:49.409707Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 3a016a1f-b7a8-42f7-a36e-7073e943903d · outbound

This paper cites Convolutional-recurrent neural networks for speech enhancement,.

Exploring Length Generalization For Transformer-based Speech Enhancement Convolutional-recurrent neural networks for speech enhancement,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:59:49.395547Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation ca9e86bc-d6fd-42d1-890f-35d1cbe2a7cc · outbound

This paper cites Gated residual networks with dilated convolutions for monaural speech enhancement,.

Exploring Length Generalization For Transformer-based Speech Enhancement Gated residual networks with dilated convolutions for monaural speech enhancement,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:59:49.380368Z

Source-reported events for the cited work

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Observation 8e8a20e0-05e8-40c5-873c-fd1a8d623b45 · outbound

This paper cites Speech enhancement using multi-stage self-attentive temporal con- volutional networks,.

Exploring Length Generalization For Transformer-based Speech Enhancement Speech enhancement using multi-stage self-attentive temporal con- volutional networks,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:59:49.365104Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 9763e7f1-3b09-4b78-9103-ae41fcdd6e6c · outbound

This paper cites Exploring tradeoffs in models for low- latency speech enhancement,.

Exploring Length Generalization For Transformer-based Speech Enhancement Exploring tradeoffs in models for low- latency speech enhancement,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:59:49.350053Z

Source-reported events for the cited work

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Observation 711fd9cb-6472-47cd-9fdc-7186b91c9a8f · outbound

This paper cites Learning complex spectral mapping with gated convolutional recurrent networks for monaural speech enhancement,.

Exploring Length Generalization For Transformer-based Speech Enhancement Learning complex spectral mapping with gated convolutional recurrent networks for monaural speech enhancement,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:59:49.336309Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 76b43c59-2f48-4fd9-89f6-11009e96820d · outbound

This paper cites Towards scaling up classification-based speech separation,.

Exploring Length Generalization For Transformer-based Speech Enhancement Towards scaling up classification-based speech separation,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:59:49.322112Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 00535f4f-afdd-490b-a9d6-23ea6cd30c33 · outbound

This paper cites On training targets for super- vised speech separation,.

Exploring Length Generalization For Transformer-based Speech Enhancement On training targets for super- vised speech separation,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:59:49.307548Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation df20fa0e-1a78-4780-a102-da3c8972d4cc · outbound

This paper cites Complex ratio masking for monaural speech separation,.

Exploring Length Generalization For Transformer-based Speech Enhancement Complex ratio masking for monaural speech separation,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:59:49.292024Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 66b863ff-c708-4b40-926f-99ddcadbcb93 · outbound

This paper cites Phase- sensitive and recognition-boosted speech separation using deep recurrent neural networks,.

Exploring Length Generalization For Transformer-based Speech Enhancement Phase- sensitive and recognition-boosted speech separation using deep recurrent neural networks,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:59:49.277464Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 3a52465e-6f4f-46e9-b932-44fd3943622f · outbound

This paper cites Single-channel speech sep- aration with memory-enhanced recurrent neural networks,.

Exploring Length Generalization For Transformer-based Speech Enhancement Single-channel speech sep- aration with memory-enhanced recurrent neural networks,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:59:49.262542Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 6d29d2a8-c4fe-4b28-9197-baf344f0e3bf · outbound

This paper cites Speech enhancement with lstm recurrent neural networks and its application to noise-robust asr,.

Exploring Length Generalization For Transformer-based Speech Enhancement Speech enhancement with lstm recurrent neural networks and its application to noise-robust asr,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:59:49.248658Z

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Observation a3af1ad3-3ae2-4317-a214-e7f01047202b · outbound

This paper cites Long short-term memory for speaker general- ization in supervised speech separation,.

Exploring Length Generalization For Transformer-based Speech Enhancement Long short-term memory for speaker general- ization in supervised speech separation,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:59:49.234425Z

Source-reported events for the cited work

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Observation c78d27fd-428d-4f6e-ae25-64bf37037567 · outbound

This paper cites An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling.

Exploring Length Generalization For Transformer-based Speech Enhancement An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-07T05:59:48.551066Z

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Observation 21236fef-31c3-4702-bbf7-4dbf87998c22 · outbound

This paper cites DeepMMSE: A deep learning approach to mmse-based noise power spectral density estimation,.

Exploring Length Generalization For Transformer-based Speech Enhancement DeepMMSE: A deep learning approach to mmse-based noise power spectral density estimation,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:59:49.219987Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 35872b85-8845-456f-8c3e-286b1dc3de80 · outbound

This paper cites Time-frequency attention for monaural speech enhancement,.

Exploring Length Generalization For Transformer-based Speech Enhancement Time-frequency attention for monaural speech enhancement,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:59:49.205852Z

Source-reported events for the cited work

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Observation 16b25cbd-e916-4952-b91c-47ace79432e7 · outbound

This paper cites Deep attention gated dilated temporal convolutional networks with intra-parallel con- volutional modules for end-to-end monaural speech separation.

Exploring Length Generalization For Transformer-based Speech Enhancement Deep attention gated dilated temporal convolutional networks with intra-parallel con- volutional modules for end-to-end monaural speech separation

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:59:49.190896Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 28d01168-ee86-4841-8610-9d28754e64d1 · outbound

This paper cites Conv-TasNet: Surpassing ideal time– frequency magnitude masking for speech separation,.

Exploring Length Generalization For Transformer-based Speech Enhancement Conv-TasNet: Surpassing ideal time– frequency magnitude masking for speech separation,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:59:49.176623Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation a86f49a0-b2e0-443a-aeb6-d5e7d93d903d · outbound

This paper cites A time-frequency attention module for neural speech enhancement,.

Exploring Length Generalization For Transformer-based Speech Enhancement A time-frequency attention module for neural speech enhancement,

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:59:49.162748Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation eaddd70c-34ed-4ede-9600-4b91237b433b · outbound

This paper cites SE-Conformer: Time-Domain Speech Enhance- ment Using Conformer,.

Exploring Length Generalization For Transformer-based Speech Enhancement SE-Conformer: Time-Domain Speech Enhance- ment Using Conformer,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:59:49.147650Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 8e2227f9-2265-4385-ad46-359e13b60cfb · outbound

This paper cites DPT-FSNet: Dual-path transformer based full-band and sub-band fusion network for speech enhancement,.

Exploring Length Generalization For Transformer-based Speech Enhancement DPT-FSNet: Dual-path transformer based full-band and sub-band fusion network for speech enhancement,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:59:49.132190Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 62aa637f-5e77-4735-bce9-86c4b9fdbd1f · outbound

This paper cites Dual-branch attention-in-attention transformer for single-channel speech enhance- ment,.

Exploring Length Generalization For Transformer-based Speech Enhancement Dual-branch attention-in-attention transformer for single-channel speech enhance- ment,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:59:49.117384Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 33ec9449-2f43-40b1-b542-4d1414b5ae86 · outbound

This paper cites Train short, test long: Attention with linear biases enables input length extrapolation,.

Exploring Length Generalization For Transformer-based Speech Enhancement Train short, test long: Attention with linear biases enables input length extrapolation,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:59:49.100962Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 7a9270f8-2d3e-49fb-a20b-c5bbfd1d4423 · outbound

This paper cites CAPE: Encoding relative positions with continuous augmented positional embeddings,.

Exploring Length Generalization For Transformer-based Speech Enhancement CAPE: Encoding relative positions with continuous augmented positional embeddings,

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:59:49.085671Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 62b3e884-45d8-4240-8614-ac293cda1be7 · outbound

This paper cites Location attention for extrapolation to longer sequences,.

Exploring Length Generalization For Transformer-based Speech Enhancement Location attention for extrapolation to longer sequences,

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:59:49.071706Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation af9c6bf3-3669-485c-ae7c-24fbcbc72cc1 · outbound

This paper cites The EOS decision and length extrapolation,.

Exploring Length Generalization For Transformer-based Speech Enhancement The EOS decision and length extrapolation,

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:59:49.058012Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 0b98f50e-3dd6-4448-bf67-d9c1421d7d7c · outbound

This paper cites From local structures to size generalization in graph neural networks,.

Exploring Length Generalization For Transformer-based Speech Enhancement From local structures to size generalization in graph neural networks,

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:59:49.043709Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation eb46bc38-eec9-4695-ac88-b24797449da3 · outbound

This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

Exploring Length Generalization For Transformer-based Speech Enhancement BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-07T05:59:48.617068Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 27a17401-edd0-4fcc-8984-27caaa767633 · outbound

This paper cites Efficient transformer-based speech enhancement using long frames and STFT magnitudes,.

Exploring Length Generalization For Transformer-based Speech Enhancement Efficient transformer-based speech enhancement using long frames and STFT magnitudes,

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-07T05:59:48.622253Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6444503c-f4ec-487f-8fdb-11d59832fe31 · outbound

This paper cites Attention is all you need in speech separation,.

Exploring Length Generalization For Transformer-based Speech Enhancement Attention is all you need in speech separation,

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:59:49.018491Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 6c28de06-9b9b-46a0-aa5f-393d12d50afa · outbound

This paper cites Self- attentional acoustic models,.

Exploring Length Generalization For Transformer-based Speech Enhancement Self- attentional acoustic models,

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:59:49.002794Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 5eb4a1dd-c64b-455b-9315-711eaf910656 · outbound

This paper cites Da-transformer: Distance-aware trans- former,.

Exploring Length Generalization For Transformer-based Speech Enhancement Da-transformer: Distance-aware trans- former,

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:59:48.987609Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 2e7ee850-8b19-448b-b94e-441e28e19113 · outbound

This paper cites RoFormer: Enhanced Transformer with Rotary Position Embedding.

Exploring Length Generalization For Transformer-based Speech Enhancement RoFormer: Enhanced Transformer with Rotary Position Embedding

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-07T05:59:48.640899Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b495fdb5-a0e9-4532-adc1-2df7caaf9000 · outbound

This paper cites Librispeech: an asr corpus based on public domain audio books,.

Exploring Length Generalization For Transformer-based Speech Enhancement Librispeech: an asr corpus based on public domain audio books,

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:59:48.972872Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation c0199d2a-3682-402b-8b8c-550f550c4a37 · outbound

This paper cites 100 nonspeech environmental sounds,.

Exploring Length Generalization For Transformer-based Speech Enhancement 100 nonspeech environmental sounds,

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:59:48.957861Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation c48ef875-7b28-42e5-9fc1-7ae9920b35d8 · outbound

This paper cites Description of the RSG-10 noise database,.

Exploring Length Generalization For Transformer-based Speech Enhancement Description of the RSG-10 noise database,

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:59:48.943736Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation bbefe631-5464-4a73-9bfe-7b2d016de431 · outbound

This paper cites Smartphone-based real-time classification of noise signals using subband features and random forest classifier,.

Exploring Length Generalization For Transformer-based Speech Enhancement Smartphone-based real-time classification of noise signals using subband features and random forest classifier,

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-07T05:59:48.659343Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 94d9beb5-ad57-4335-a260-6974c20c1696 · outbound

This paper cites Automatic switching between noise classi- fication and speech enhancement for hearing aid devices,.

Exploring Length Generalization For Transformer-based Speech Enhancement Automatic switching between noise classi- fication and speech enhancement for hearing aid devices,

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:59:48.918933Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 2b89078e-0b1a-4a1c-b819-79930463ce41 · outbound

This paper cites A dataset and taxonomy for urban sound research,.

Exploring Length Generalization For Transformer-based Speech Enhancement A dataset and taxonomy for urban sound research,

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:59:48.903766Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation a6e8d33d-3b08-49ba-8183-3eb396632288 · outbound

This paper cites MUSAN: A Music, Speech, and Noise Corpus.

Exploring Length Generalization For Transformer-based Speech Enhancement MUSAN: A Music, Speech, and Noise Corpus

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-07T05:59:48.673473Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2c452c2e-4231-4d64-836f-8cfc89ff8e12 · outbound

This paper cites The QUT- NOISE-TIMIT corpus for the evaluation of voice activity detection algorithms,.

Exploring Length Generalization For Transformer-based Speech Enhancement The QUT- NOISE-TIMIT corpus for the evaluation of voice activity detection algorithms,

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:59:48.887983Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation b1d64cd1-b48a-4a4a-b1f5-1a171e4211de · outbound

This paper cites Interactive Speech and Noise Modeling for Speech Enhancement.

Exploring Length Generalization For Transformer-based Speech Enhancement Interactive Speech and Noise Modeling for Speech Enhancement

Reference 68

Resolution: verified exact; local_arxiv, observed 2026-08-07T05:59:48.745361Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation dffb5959-e5fd-4c4e-aedf-fe0944746867 · outbound

This paper cites 862.2: Wideband extension to recommendation P. 862 for the assessment of wideband telephone networks and speech codecs. ITU-Telecommunication standardization sector, 2007.

Exploring Length Generalization For Transformer-based Speech Enhancement 862.2: Wideband extension to recommendation P. 862 for the assessment of wideband telephone networks and speech codecs. ITU-Telecommunication standardization sector, 2007

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-07T05:59:48.688405Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f360c9a4-4f29-4831-8cc7-912c1d3efac3 · outbound

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

Exploring Length Generalization For Transformer-based Speech Enhancement An algorithm for predicting the intelligibility of speech masked by modulated noise maskers,

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:59:48.862232Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation eb558e16-5b4f-4c13-b19c-3ce0dcedb87b · outbound

This paper cites Evaluation of objective quality measures for speech enhancement,.

Exploring Length Generalization For Transformer-based Speech Enhancement Evaluation of objective quality measures for speech enhancement,

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:59:48.846449Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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