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Paper Citation Record · LEDGER

CueNet: Robust Audio-Visual Speaker Extraction through Cross-Modal Cue Mining and Interaction

As of 9 August 2026, this Paper Citation Record lists 57 of 57 outbound references and 0 inbound Pith citation observations for arXiv:2603.01530.

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

pith.paper-citation-record.v1
2603.01530 v2

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measured 57 of 57 reference resolution

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measured 57 of 57 standing notices

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measured 0 of 0 inbound itemization

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57 of 57 outbound references displayed

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Outbound references

Observation 7e745d9b-7458-4b8b-bbe7-c2f906a187bf · outbound

This paper cites Late audio-visual fusion for in-the-wild speaker diarization,.

CueNet: Robust Audio-Visual Speaker Extraction through Cross-Modal Cue Mining and Interaction Late audio-visual fusion for in-the-wild speaker diarization,

Reference 1

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Observation 63a9d8fc-3871-4b88-9369-966523c65264 · outbound

This paper cites Predict-and-update network: Audio-visual speech recognition inspired by human speech perception,.

CueNet: Robust Audio-Visual Speaker Extraction through Cross-Modal Cue Mining and Interaction Predict-and-update network: Audio-visual speech recognition inspired by human speech perception,

Reference 2

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Observation cf4cf079-4ba3-4aa5-88d6-1ce30a822961 · outbound

This paper cites Audio-visual cross- attention network for robotic speaker tracking,.

CueNet: Robust Audio-Visual Speaker Extraction through Cross-Modal Cue Mining and Interaction Audio-visual cross- attention network for robotic speaker tracking,

Reference 3

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Observation 53e1d0f9-1ca6-4203-9034-30adf9fb679f · outbound

This paper cites My lips are concealed: Audio-visual speech enhancement through obstructions,.

CueNet: Robust Audio-Visual Speaker Extraction through Cross-Modal Cue Mining and Interaction My lips are concealed: Audio-visual speech enhancement through obstructions,

Reference 4

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Observation 987c4fe5-f154-4815-bf84-06d766542a17 · outbound

This paper cites Multimodal attention fusion for target speaker extraction,.

CueNet: Robust Audio-Visual Speaker Extraction through Cross-Modal Cue Mining and Interaction Multimodal attention fusion for target speaker extraction,

Reference 5

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Observation bad0a1cd-ae40-4ee0-b7c3-8891513ad009 · outbound

This paper cites Time-domain audio-visual speech separation on low quality videos,.

CueNet: Robust Audio-Visual Speaker Extraction through Cross-Modal Cue Mining and Interaction Time-domain audio-visual speech separation on low quality videos,

Reference 6

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Observation 1bc86261-7476-4377-9659-3a978ba39533 · outbound

This paper cites A two-stage audio-visual speech separation method without visual signals for testing and tuples loss with dynamic margin,.

CueNet: Robust Audio-Visual Speaker Extraction through Cross-Modal Cue Mining and Interaction A two-stage audio-visual speech separation method without visual signals for testing and tuples loss with dynamic margin,

Reference 7

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Observation d505beb3-6b6d-4c24-a05d-f3c6fb0c9083 · outbound

This paper cites Ravss: Robust audio- visual speech separation in multi-speaker scenarios with missing visual cues,.

CueNet: Robust Audio-Visual Speaker Extraction through Cross-Modal Cue Mining and Interaction Ravss: Robust audio- visual speech separation in multi-speaker scenarios with missing visual cues,

Reference 8

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Observation 9fdabcf9-e31b-4906-97fe-bfc6b61e1ab9 · outbound

This paper cites Multi-modal multi-correlation learning for audio-visual speech separation,.

CueNet: Robust Audio-Visual Speaker Extraction through Cross-Modal Cue Mining and Interaction Multi-modal multi-correlation learning for audio-visual speech separation,

Reference 9

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Observation 8568c310-aa1a-4828-827b-73181b449ef7 · outbound

This paper cites Visualvoice: Audio-visual speech separa- tion with cross-modal consistency,.

CueNet: Robust Audio-Visual Speaker Extraction through Cross-Modal Cue Mining and Interaction Visualvoice: Audio-visual speech separa- tion with cross-modal consistency,

Reference 10

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Observation d5ce327e-36a9-4e13-bac5-9532e4eee839 · outbound

This paper cites Explaining face-voice matching decisions: The contribution of mouth movements, stimulus effects and response biases,.

CueNet: Robust Audio-Visual Speaker Extraction through Cross-Modal Cue Mining and Interaction Explaining face-voice matching decisions: The contribution of mouth movements, stimulus effects and response biases,

Reference 11

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Observation 9bc51f8a-9fb8-49dd-b95a-b842d2d15a59 · outbound

This paper cites Rethinking the visual cues in audio-visual speaker extraction,.

CueNet: Robust Audio-Visual Speaker Extraction through Cross-Modal Cue Mining and Interaction Rethinking the visual cues in audio-visual speaker extraction,

Reference 12

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Observation f1cd3764-6ff2-4e55-bd54-65183bec8189 · outbound

This paper cites Muse: Multi-modal target speaker extraction with visual cues,.

CueNet: Robust Audio-Visual Speaker Extraction through Cross-Modal Cue Mining and Interaction Muse: Multi-modal target speaker extraction with visual cues,

Reference 13

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Observation e85590b2-679c-4c45-849d-ca11468bc116 · outbound

This paper cites Hearing lips and seeing voices,.

CueNet: Robust Audio-Visual Speaker Extraction through Cross-Modal Cue Mining and Interaction Hearing lips and seeing voices,

Reference 14

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Observation 82f601e2-676a-44f0-a97b-9ed29faa003a · outbound

This paper cites The effect of speechreading on masked detection thresh- olds for filtered speech,.

CueNet: Robust Audio-Visual Speaker Extraction through Cross-Modal Cue Mining and Interaction The effect of speechreading on masked detection thresh- olds for filtered speech,

Reference 15

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Observation 85a12557-dfd5-4976-a272-f45ea94cdfbd · outbound

This paper cites Neural target speech extraction: An overview,.

CueNet: Robust Audio-Visual Speaker Extraction through Cross-Modal Cue Mining and Interaction Neural target speech extraction: An overview,

Reference 16

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Observation a04400b8-a94e-4b62-9326-6d13188619c0 · outbound

This paper cites Multi-cue guided semi-supervised learning toward target speaker separation in real environments,.

CueNet: Robust Audio-Visual Speaker Extraction through Cross-Modal Cue Mining and Interaction Multi-cue guided semi-supervised learning toward target speaker separation in real environments,

Reference 17

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Observation 0e4e957a-21e2-49a6-b2d8-f4e8c1e28713 · outbound

This paper cites Multi- level speaker representation for target speaker extraction,.

CueNet: Robust Audio-Visual Speaker Extraction through Cross-Modal Cue Mining and Interaction Multi- level speaker representation for target speaker extraction,

Reference 18

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Observation 88058dec-30e4-45d3-add3-c9134998d60e · outbound

This paper cites Usef-tse: Universal speaker embedding free target speaker extraction,.

CueNet: Robust Audio-Visual Speaker Extraction through Cross-Modal Cue Mining and Interaction Usef-tse: Universal speaker embedding free target speaker extraction,

Reference 19

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Observation 4f2b76a7-4c7e-4336-bb74-c2254bf92e91 · outbound

This paper cites Contextual speech extraction: Leveraging textual history as an implicit cue for target speech extraction,.

CueNet: Robust Audio-Visual Speaker Extraction through Cross-Modal Cue Mining and Interaction Contextual speech extraction: Leveraging textual history as an implicit cue for target speech extraction,

Reference 20

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Observation 380459a4-3d15-4e84-88b7-4e652e6ac1cf · outbound

This paper cites Conceptbeam: Concept driven target speech extraction,.

CueNet: Robust Audio-Visual Speaker Extraction through Cross-Modal Cue Mining and Interaction Conceptbeam: Concept driven target speech extraction,

Reference 21

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source=pdf_text observed=2026-08-02T19:39:49.344715Z digest=sha256:571054a2dc591ae4a915b369de19b83896602f9267c7bb5f6e3f541d63a3a580

Observation 09c71ba3-7a9c-46af-b636-f08cbbeefda8 · outbound

This paper cites SenSE: Semantic-Aware High-Fidelity Universal Speech Enhancement.

CueNet: Robust Audio-Visual Speaker Extraction through Cross-Modal Cue Mining and Interaction SenSE: Semantic-Aware High-Fidelity Universal Speech Enhancement

Reference 22

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Observation 1943fd70-11df-4ce3-82f5-4ec69984d198 · outbound

This paper cites Av-crossnet: An audiovisual complex spectral mapping network for speech separation by leveraging narrow-and cross-band modeling,.

CueNet: Robust Audio-Visual Speaker Extraction through Cross-Modal Cue Mining and Interaction Av-crossnet: An audiovisual complex spectral mapping network for speech separation by leveraging narrow-and cross-band modeling,

Reference 23

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Observation 0e469bc5-a982-4c66-8de4-f280c8144b95 · outbound

This paper cites Audio-visual speech separation and dereverberation with a two-stage multimodal network,.

CueNet: Robust Audio-Visual Speaker Extraction through Cross-Modal Cue Mining and Interaction Audio-visual speech separation and dereverberation with a two-stage multimodal network,

Reference 24

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Observation cfef3ce0-3b85-4080-be40-26b12408f5de · outbound

This paper cites Spatialnet: Extensively learning spatial information for multichannel joint speech separation, denoising and dereverberation,.

CueNet: Robust Audio-Visual Speaker Extraction through Cross-Modal Cue Mining and Interaction Spatialnet: Extensively learning spatial information for multichannel joint speech separation, denoising and dereverberation,

Reference 25

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Observation 04a2a2f6-a6b0-4183-8185-b3d3a328c608 · outbound

This paper cites Fasnet: Low- latency adaptive beamforming for multi-microphone audio processing,.

CueNet: Robust Audio-Visual Speaker Extraction through Cross-Modal Cue Mining and Interaction Fasnet: Low- latency adaptive beamforming for multi-microphone audio processing,

Reference 26

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Observation 660cbdaa-f9f3-47ac-99ba-357a0294e03c · outbound

This paper cites Multi-modal multi-channel target speech separation,.

CueNet: Robust Audio-Visual Speaker Extraction through Cross-Modal Cue Mining and Interaction Multi-modal multi-channel target speech separation,

Reference 27

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Observation 0e4f0049-db7f-4fe2-b9c2-759f3fc98d65 · outbound

This paper cites An overview of deep-learning-based audio-visual speech en- hancement and separation,.

CueNet: Robust Audio-Visual Speaker Extraction through Cross-Modal Cue Mining and Interaction An overview of deep-learning-based audio-visual speech en- hancement and separation,

Reference 28

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Observation 6ac8057b-44e4-40b1-a379-571d7678c9d6 · outbound

This paper cites Unified audio visual cues for target speaker extraction,.

CueNet: Robust Audio-Visual Speaker Extraction through Cross-Modal Cue Mining and Interaction Unified audio visual cues for target speaker extraction,

Reference 29

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Observation 7e7e147e-96ba-4759-a544-6ae1f7d213e7 · outbound

This paper cites MoMuSE: Momentum Multi-modal Target Speaker Extraction for Real-time Scenarios with Impaired Visual Cues.

CueNet: Robust Audio-Visual Speaker Extraction through Cross-Modal Cue Mining and Interaction MoMuSE: Momentum Multi-modal Target Speaker Extraction for Real-time Scenarios with Impaired Visual Cues

Reference 30

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Observation a093622f-23ed-4eee-b9d4-df82da779cc2 · outbound

This paper cites MeMo: Attentional Momentum for Real-time Audio-visual Speaker Extraction under Impaired Visual Conditions.

CueNet: Robust Audio-Visual Speaker Extraction through Cross-Modal Cue Mining and Interaction MeMo: Attentional Momentum for Real-time Audio-visual Speaker Extraction under Impaired Visual Conditions

Reference 31

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Observation 9236990d-7209-4cd7-bfe7-6c87dcfc5928 · outbound

This paper cites Tf-gridnet: Making time-frequency domain models great again for monaural speaker separation,.

CueNet: Robust Audio-Visual Speaker Extraction through Cross-Modal Cue Mining and Interaction Tf-gridnet: Making time-frequency domain models great again for monaural speaker separation,

Reference 32

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Observation 7691e0c9-511a-47ff-8a85-d36e2f90fdbc · outbound

This paper cites Separate in the Speech Chain: Cross-Modal Conditional Audio-Visual Target Speech Extraction.

CueNet: Robust Audio-Visual Speaker Extraction through Cross-Modal Cue Mining and Interaction Separate in the Speech Chain: Cross-Modal Conditional Audio-Visual Target Speech Extraction

Reference 33

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Observation 02546d07-92d4-4255-a078-45e13b8b6517 · outbound

This paper cites ClearerVoice-Studio: Bridging Advanced Speech Processing Research and Practical Deployment.

CueNet: Robust Audio-Visual Speaker Extraction through Cross-Modal Cue Mining and Interaction ClearerVoice-Studio: Bridging Advanced Speech Processing Research and Practical Deployment

Reference 34

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Observation 6f81324b-2b19-405e-8ff6-4eefc7fed8ef · outbound

This paper cites Av-sepformer: Cross-attention sepformer for audio-visual target speaker extraction,.

CueNet: Robust Audio-Visual Speaker Extraction through Cross-Modal Cue Mining and Interaction Av-sepformer: Cross-attention sepformer for audio-visual target speaker extraction,

Reference 35

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Observation 42cae12f-b223-4ce4-aed9-ad366c7f16b2 · outbound

This paper cites Deep residual learning for image recognition,.

CueNet: Robust Audio-Visual Speaker Extraction through Cross-Modal Cue Mining and Interaction Deep residual learning for image recognition,

Reference 36

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Observation 147f996f-0f6c-44d0-8946-9b8264e2aba8 · outbound

This paper cites Audio-visual target speaker extraction with selective auditory attention,.

CueNet: Robust Audio-Visual Speaker Extraction through Cross-Modal Cue Mining and Interaction Audio-visual target speaker extraction with selective auditory attention,

Reference 37

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source=pdf_text observed=2026-08-02T19:39:50.758566Z digest=sha256:b5cf8b15dd0eaa1a0b762ffb3ae921686017b575008761000195ea1e84d6fa8b

Observation 9e040b87-7754-4ebd-ab87-558186acd7c4 · outbound

This paper cites Pitch range variations improve cognitive processing of audio messages,.

CueNet: Robust Audio-Visual Speaker Extraction through Cross-Modal Cue Mining and Interaction Pitch range variations improve cognitive processing of audio messages,

Reference 38

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Observation 83d5ffcf-441a-4334-9951-63ea1fc05a65 · outbound

This paper cites Intonation and speaker identification,.

CueNet: Robust Audio-Visual Speaker Extraction through Cross-Modal Cue Mining and Interaction Intonation and speaker identification,

Reference 39

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source=pdf_text observed=2026-08-02T19:39:50.878247Z digest=sha256:a47bede395e9ff84b1040135981d844640227985c962bf9edb84af664d5832ac

Observation a3c7590b-37bd-4fd8-b8f2-99b6028d3f0e · outbound

This paper cites Dual-path rnn: efficient long sequence modeling for time-domain single-channel speech separation,.

CueNet: Robust Audio-Visual Speaker Extraction through Cross-Modal Cue Mining and Interaction Dual-path rnn: efficient long sequence modeling for time-domain single-channel speech separation,

Reference 40

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source=pdf_text observed=2026-08-02T19:39:50.973379Z digest=sha256:12616b767b1d929d4273164aea1c9bf666e1fc76453f72c21bc2fe28be7610e5

Observation 3bde35da-e50b-4f1e-a4a4-b0cea45ceb1b · outbound

This paper cites Time domain audio visual speech separation,.

CueNet: Robust Audio-Visual Speaker Extraction through Cross-Modal Cue Mining and Interaction Time domain audio visual speech separation,

Reference 41

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source=pdf_text observed=2026-08-02T19:39:51.116351Z digest=sha256:89bf954826e7ff71507dbb9c704f5f64f2f412dd92a91ceb409af028b3d212ce

Observation 861f072b-09f5-4af3-b854-a775d81c64cd · outbound

This paper cites Learning audio- visual speech representation by masked multimodal cluster prediction,.

CueNet: Robust Audio-Visual Speaker Extraction through Cross-Modal Cue Mining and Interaction Learning audio- visual speech representation by masked multimodal cluster prediction,

Reference 42

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Observation 2ec3e718-24ea-4b47-a486-cf2ee07409a7 · outbound

This paper cites Rethinking the inception architecture for computer vision,.

CueNet: Robust Audio-Visual Speaker Extraction through Cross-Modal Cue Mining and Interaction Rethinking the inception architecture for computer vision,

Reference 43

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source=pdf_text observed=2026-08-02T19:39:51.421789Z digest=sha256:f24872e3b39f8eb188944a36155e804b50525d520592a5ad39e00cb3207bbb30

Observation 99af4452-84f4-4a29-8fc8-7208625e9b3d · outbound

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

CueNet: Robust Audio-Visual Speaker Extraction through Cross-Modal Cue Mining and Interaction Sdr–half-baked or well done?

Reference 44

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source=pdf_text observed=2026-08-02T19:39:51.538493Z digest=sha256:69feafba9307aeaf5a293499c8541ac36ea9067a12b8af4c6f59c5cf6eccde57

Observation 2e4cbf8c-bce6-4d7c-8181-af5e0fd61cd4 · outbound

This paper cites Audio-Visual Speech Separation in Noisy Environments with a Lightweight Iterative Model,.

CueNet: Robust Audio-Visual Speaker Extraction through Cross-Modal Cue Mining and Interaction Audio-Visual Speech Separation in Noisy Environments with a Lightweight Iterative Model,

Reference 45

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source=pdf_text observed=2026-08-02T19:39:51.693426Z digest=sha256:2f5b8c20922807374986d71abd8b203aef799690ff5de00a22d88dae409dd253

Observation 3c3d8a28-7000-4038-adf8-e588e3a7538f · outbound

This paper cites An audio-visual speech separation model inspired by cortico-thalamo-cortical circuits,.

CueNet: Robust Audio-Visual Speaker Extraction through Cross-Modal Cue Mining and Interaction An audio-visual speech separation model inspired by cortico-thalamo-cortical circuits,

Reference 46

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source=pdf_text observed=2026-08-02T19:39:51.835676Z digest=sha256:62ece97f5efa0cb8d15f8c1b8cde0f10efa21b48d252077d3da32097b5d07788

Observation 514335a0-d76a-4404-8576-ecdf84ed0ece · outbound

This paper cites Iianet: an intra-and inter-modality attention network for audio-visual speech separation,.

CueNet: Robust Audio-Visual Speaker Extraction through Cross-Modal Cue Mining and Interaction Iianet: an intra-and inter-modality attention network for audio-visual speech separation,

Reference 47

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source=pdf_text observed=2026-08-02T19:39:51.902230Z digest=sha256:529d34483ea19c945d5b7b74c780e5f3a9a03817832b911a3b8ec28a112a19a4

Observation b78ba67f-4f44-4135-abdf-d3d62d824dd6 · outbound

This paper cites Deep audio-visual speech recognition,.

CueNet: Robust Audio-Visual Speaker Extraction through Cross-Modal Cue Mining and Interaction Deep audio-visual speech recognition,

Reference 48

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source=pdf_text observed=2026-08-02T19:39:51.948455Z digest=sha256:73234e4cd440ee660be6f031d9ebdea70816f8ee38dd0f6fbc9a9e196ecc893f

Observation a667534c-8589-45d5-9bf7-6a3ec0025dae · outbound

This paper cites VoxCeleb2: Deep Speaker Recognition.

CueNet: Robust Audio-Visual Speaker Extraction through Cross-Modal Cue Mining and Interaction VoxCeleb2: Deep Speaker Recognition

Reference 49

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Observation de8584db-4a6a-46fa-ba23-6aa2417334f6 · outbound

This paper cites Looking into your speech: Learning cross-modal affinity for audio-visual speech separation,.

CueNet: Robust Audio-Visual Speaker Extraction through Cross-Modal Cue Mining and Interaction Looking into your speech: Learning cross-modal affinity for audio-visual speech separation,

Reference 50

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source=pdf_text observed=2026-08-02T19:39:52.175405Z digest=sha256:f7a48a0bfd0f5066b398a693f2a74841593502010f92fa8e39060979707ed674

Observation a7256a29-e690-49c8-b956-a3dd7f0a2d5b · outbound

This paper cites Watch or listen: Robust audio- visual speech recognition with visual corruption modeling and reliability scoring,.

CueNet: Robust Audio-Visual Speaker Extraction through Cross-Modal Cue Mining and Interaction Watch or listen: Robust audio- visual speech recognition with visual corruption modeling and reliability scoring,

Reference 51

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Observation b334d924-65e3-47f9-b207-5d84923d7c9f · outbound

This paper cites Restoring speaking lips from occlusion for audio-visual speech recognition,.

CueNet: Robust Audio-Visual Speaker Extraction through Cross-Modal Cue Mining and Interaction Restoring speaking lips from occlusion for audio-visual speech recognition,

Reference 52

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Observation dd4a8bae-a187-420a-a7a4-4568218dfee1 · outbound

This paper cites Delving into high-quality synthetic face occlusion segmentation datasets,.

CueNet: Robust Audio-Visual Speaker Extraction through Cross-Modal Cue Mining and Interaction Delving into high-quality synthetic face occlusion segmentation datasets,

Reference 53

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Observation e34e8283-d8b2-4aab-9303-c6a80775876a · outbound

This paper cites Data2vec: A general framework for self-supervised learning in speech, vision and language,.

CueNet: Robust Audio-Visual Speaker Extraction through Cross-Modal Cue Mining and Interaction Data2vec: A general framework for self-supervised learning in speech, vision and language,

Reference 54

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source=pdf_text observed=2026-08-02T19:39:52.616289Z digest=sha256:855e28034ce60f851b4d8f18a192262b5c2d779e2ac64aadfa83186f21a679bb

Observation 82b83497-9b72-49fa-b5a1-0ebe40e3426a · outbound

This paper cites Adam: A Method for Stochastic Optimization.

CueNet: Robust Audio-Visual Speaker Extraction through Cross-Modal Cue Mining and Interaction Adam: A Method for Stochastic Optimization

Reference 55

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source=pdf_text observed=2026-08-02T19:39:52.723885Z digest=sha256:ad7e80383c22e3bc98ff1b577414230f2b6ec59ae344b5b053c43b6ecaf23280

Observation cd1737d7-935f-4925-954b-b90a960cda81 · outbound

This paper cites Long short-term memory,.

CueNet: Robust Audio-Visual Speaker Extraction through Cross-Modal Cue Mining and Interaction Long short-term memory,

Reference 56

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source=pdf_text observed=2026-08-02T19:39:52.814970Z digest=sha256:9ce93dbfeb381452f721dfbc910177b8d388b518c3a2b8bad4b3faf3fd3707ef

Observation 0edb5e94-dfa7-49ff-8040-5d7d0f070bfc · outbound

This paper cites How many phonemes does the english language have,.

CueNet: Robust Audio-Visual Speaker Extraction through Cross-Modal Cue Mining and Interaction How many phonemes does the english language have,

Reference 57

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source=pdf_text observed=2026-08-02T19:39:52.897328Z digest=sha256:710bd2ccf56496751f2b58592284625a5a808c69eebb9548c3192b12d023d270

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