Paper Citation Record · LEDGER

End-to-end Acoustic-linguistic Emotion and Intent Recognition Enhanced by Semi-supervised Learning

As of 10 August 2026, this Paper Citation Record lists 32 of 32 outbound references and 0 inbound Pith citation observations for arXiv:2507.07806.

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

pith.paper-citation-record.v1
2507.07806 v1

Coverage vector

measured 32 of 32 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T18:36:05.834924Z

measured 32 of 32 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

32 of 32 outbound references displayed

verified exact0
verified fuzzy25
unresolved7
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 459f071c-36b8-4627-8f81-ff84710d4b6b · outbound

This paper cites Schuller and A.

End-to-end Acoustic-linguistic Emotion and Intent Recognition Enhanced by Semi-supervised Learning Schuller and A

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:36:06.348892Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 7b576c6a-0312-406a-90c4-428e421371c8 · outbound

This paper cites Domain Adaptation in Intent Classification Systems: A Review.

End-to-end Acoustic-linguistic Emotion and Intent Recognition Enhanced by Semi-supervised Learning Domain Adaptation in Intent Classification Systems: A Review

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-06T18:36:05.688417Z

Source-reported events for the cited work

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Observation 1304a568-28fe-4e84-b709-f6e163bb688d · outbound

This paper cites End-to-end continuous speech emotion recognition in real-life customer service call center conversations,.

End-to-end Acoustic-linguistic Emotion and Intent Recognition Enhanced by Semi-supervised Learning End-to-end continuous speech emotion recognition in real-life customer service call center conversations,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:36:06.333983Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation c9124f1a-64ab-4dda-af29-0bd2c3f1818d · outbound

This paper cites A VEC 2019 workshop and challenge: State-of-mind, detecting depression with AI, and cross-cultural affect recognition,.

End-to-end Acoustic-linguistic Emotion and Intent Recognition Enhanced by Semi-supervised Learning A VEC 2019 workshop and challenge: State-of-mind, detecting depression with AI, and cross-cultural affect recognition,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:36:06.318440Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation e4db70e6-b527-45bb-b68b-6a7728adaaf2 · outbound

This paper cites Cross- lingual/cross-channel intent detection in contact-center conversations,.

End-to-end Acoustic-linguistic Emotion and Intent Recognition Enhanced by Semi-supervised Learning Cross- lingual/cross-channel intent detection in contact-center conversations,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:36:06.303401Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation ea5e5ffd-bd87-4bd0-872e-8753b9bafeef · outbound

This paper cites Survey of deep representation learning for speech emotion recognition,.

End-to-end Acoustic-linguistic Emotion and Intent Recognition Enhanced by Semi-supervised Learning Survey of deep representation learning for speech emotion recognition,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:36:06.287562Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 4b2c86e6-21fc-41f4-9ff2-602cf4cb4d66 · outbound

This paper cites Fast yet effective speech emotion recognition with self-distillation,.

End-to-end Acoustic-linguistic Emotion and Intent Recognition Enhanced by Semi-supervised Learning Fast yet effective speech emotion recognition with self-distillation,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:36:06.273253Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 9d6ed6ae-6c47-49a8-8077-1c6423d2c152 · outbound

This paper cites An effective multimodal representation and fusion method for multimodal intent recognition,.

End-to-end Acoustic-linguistic Emotion and Intent Recognition Enhanced by Semi-supervised Learning An effective multimodal representation and fusion method for multimodal intent recognition,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:36:06.258293Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 564fc5e0-2370-4478-9948-b866156d255e · outbound

This paper cites wav2vec 2.0: A framework for self-supervised learning of speech representations,.

End-to-end Acoustic-linguistic Emotion and Intent Recognition Enhanced by Semi-supervised Learning wav2vec 2.0: A framework for self-supervised learning of speech representations,

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-06T18:36:05.723111Z

Source-reported events for the cited work

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Observation d065fe91-460a-44bd-b3fb-591ef18aefe7 · outbound

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

End-to-end Acoustic-linguistic Emotion and Intent Recognition Enhanced by Semi-supervised Learning HuBERT: Self-supervised speech representation learning by masked prediction of hidden units,

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-06T18:36:05.728104Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2ce85b3c-598a-4047-9c81-045551f209ee · outbound

This paper cites RoBERTa: A Robustly Optimized BERT Pretraining Approach.

End-to-end Acoustic-linguistic Emotion and Intent Recognition Enhanced by Semi-supervised Learning RoBERTa: A Robustly Optimized BERT Pretraining Approach

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-06T18:36:05.732683Z

Source-reported events for the cited work

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Observation 2c8f555c-d88b-415a-82c6-34febf89718f · outbound

This paper cites Semi- supervised spoken language understanding via self-supervised speech and language model pretraining,.

End-to-end Acoustic-linguistic Emotion and Intent Recognition Enhanced by Semi-supervised Learning Semi- supervised spoken language understanding via self-supervised speech and language model pretraining,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:36:06.223801Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 58d41bbd-c371-4e89-8edd-265107925fec · outbound

This paper cites Semi-supervised speech emotion recognition with ladder networks,.

End-to-end Acoustic-linguistic Emotion and Intent Recognition Enhanced by Semi-supervised Learning Semi-supervised speech emotion recognition with ladder networks,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:36:06.210406Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation c2e8a114-f010-45c6-97d0-b04a486eb775 · outbound

This paper cites Multi-task semi-supervised adversarial autoencoding for speech emo- tion recognition,.

End-to-end Acoustic-linguistic Emotion and Intent Recognition Enhanced by Semi-supervised Learning Multi-task semi-supervised adversarial autoencoding for speech emo- tion recognition,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:36:06.195528Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 6325551b-eadf-40b0-8e46-09157b491024 · outbound

This paper cites Speech emotion recognition using semi-supervised learning with ladder networks,.

End-to-end Acoustic-linguistic Emotion and Intent Recognition Enhanced by Semi-supervised Learning Speech emotion recognition using semi-supervised learning with ladder networks,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:36:06.179768Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 4d875591-4ab2-47d0-aee7-d56699f38268 · outbound

This paper cites Enhanced semi-supervised learning for multimodal emotion recognition,.

End-to-end Acoustic-linguistic Emotion and Intent Recognition Enhanced by Semi-supervised Learning Enhanced semi-supervised learning for multimodal emotion recognition,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:36:06.164547Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 92af3c29-9a59-43a5-a56a-fcb32b2330ce · outbound

This paper cites Semi-fedSER: Semi-supervised learning for speech emotion recognition on federated learning using multiview pseudo-labeling,.

End-to-end Acoustic-linguistic Emotion and Intent Recognition Enhanced by Semi-supervised Learning Semi-fedSER: Semi-supervised learning for speech emotion recognition on federated learning using multiview pseudo-labeling,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:36:06.150172Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 5fc4f503-3ea3-426e-b231-ab441a0fbe43 · outbound

This paper cites Combining active and semi-supervised learning for spoken language understanding,.

End-to-end Acoustic-linguistic Emotion and Intent Recognition Enhanced by Semi-supervised Learning Combining active and semi-supervised learning for spoken language understanding,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:36:06.135820Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation cd7981aa-8497-4e9f-a996-9ecbd247596c · outbound

This paper cites Semi-supervised acoustic model training by discriminative data selection from multiple asr systems’ hypotheses,.

End-to-end Acoustic-linguistic Emotion and Intent Recognition Enhanced by Semi-supervised Learning Semi-supervised acoustic model training by discriminative data selection from multiple asr systems’ hypotheses,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:36:06.121315Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 6bd3858c-75eb-49f7-8cf4-a14c21c90169 · outbound

This paper cites Fixmatch: Simplifying semi- supervised learning with consistency and confidence,.

End-to-end Acoustic-linguistic Emotion and Intent Recognition Enhanced by Semi-supervised Learning Fixmatch: Simplifying semi- supervised learning with consistency and confidence,

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-06T18:36:05.777583Z

Source-reported events for the cited work

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Observation 29cb90da-878c-4862-a41f-4be76dab7215 · outbound

This paper cites Combining cross-modal knowledge transfer and semi-supervised learning for speech emotion recognition,.

End-to-end Acoustic-linguistic Emotion and Intent Recognition Enhanced by Semi-supervised Learning Combining cross-modal knowledge transfer and semi-supervised learning for speech emotion recognition,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:36:06.095997Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 6658381c-74e2-477c-8c2c-c16b01af8de6 · outbound

This paper cites Multi-lingual multi-task speech emotion recognition using wav2vec 2.0,.

End-to-end Acoustic-linguistic Emotion and Intent Recognition Enhanced by Semi-supervised Learning Multi-lingual multi-task speech emotion recognition using wav2vec 2.0,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:36:06.080982Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 59abb32f-d2af-4bb5-9640-fe59d6c5104b · outbound

This paper cites Knowledge transfer for on-device speech emotion recognition with neural structured learning,.

End-to-end Acoustic-linguistic Emotion and Intent Recognition Enhanced by Semi-supervised Learning Knowledge transfer for on-device speech emotion recognition with neural structured learning,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:36:06.065283Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation e822ecf1-6d2a-44da-8ba2-e1245a6bdfaa · outbound

This paper cites Emotion and Intent Joint Understanding in Multimodal Conversation: A Benchmarking Dataset.

End-to-end Acoustic-linguistic Emotion and Intent Recognition Enhanced by Semi-supervised Learning Emotion and Intent Joint Understanding in Multimodal Conversation: A Benchmarking Dataset

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-06T18:36:05.795773Z

Source-reported events for the cited work

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Observation da1c8dfe-f627-47df-8578-b2784151eb11 · outbound

This paper cites Robust speech recognition via large-scale weak supervi- sion,.

End-to-end Acoustic-linguistic Emotion and Intent Recognition Enhanced by Semi-supervised Learning Robust speech recognition via large-scale weak supervi- sion,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:36:06.044993Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 6b5b5763-d904-4f93-a300-066ded8e6c91 · outbound

This paper cites Dynamic thresholding on fixmatch with weak and strong data augmentations for sound event detection,.

End-to-end Acoustic-linguistic Emotion and Intent Recognition Enhanced by Semi-supervised Learning Dynamic thresholding on fixmatch with weak and strong data augmentations for sound event detection,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:36:06.024941Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 4eae5d76-c074-4f83-8bb6-64be207a7ec4 · outbound

This paper cites EDA: Easy data augmentation techniques for boosting performance on text classification tasks,.

End-to-end Acoustic-linguistic Emotion and Intent Recognition Enhanced by Semi-supervised Learning EDA: Easy data augmentation techniques for boosting performance on text classification tasks,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:36:06.001116Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 5e7a5558-bbe2-4b37-abce-f5e28b1eca5e · outbound

This paper cites Deep scalogram representations for acoustic scene classification,.

End-to-end Acoustic-linguistic Emotion and Intent Recognition Enhanced by Semi-supervised Learning Deep scalogram representations for acoustic scene classification,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:36:05.985724Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 7735d5d8-7ce1-401c-ab72-6ad0da11d158 · outbound

This paper cites Verification of acoustical correlates of emotional speech using formant-synthesis,.

End-to-end Acoustic-linguistic Emotion and Intent Recognition Enhanced by Semi-supervised Learning Verification of acoustical correlates of emotional speech using formant-synthesis,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:36:05.970711Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 37dc512b-ef47-45d6-b875-ee6d531eaaaa · outbound

This paper cites The acoustic realization of anger, fear, joy and sadness in chinese,.

End-to-end Acoustic-linguistic Emotion and Intent Recognition Enhanced by Semi-supervised Learning The acoustic realization of anger, fear, joy and sadness in chinese,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:36:05.953608Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 89345faa-2a56-4924-a25b-06838cf13c53 · outbound

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

End-to-end Acoustic-linguistic Emotion and Intent Recognition Enhanced by Semi-supervised Learning WavLM: Large-scale self-supervised pre-training for full stack speech processing,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:36:05.937018Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 70925387-01ac-4823-b521-5d86d47255d9 · outbound

This paper cites Can Large Language Models Aid in Annotating Speech Emotional Data? Uncovering New Frontiers.

End-to-end Acoustic-linguistic Emotion and Intent Recognition Enhanced by Semi-supervised Learning Can Large Language Models Aid in Annotating Speech Emotional Data? Uncovering New Frontiers

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-06T18:36:05.834924Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.