Pith. sign in

Paper Citation Record · LEDGER

Leveraging Cross-Attention Transformer and Multi-Feature Fusion for Cross-Linguistic Speech Emotion Recognition

As of 11 August 2026, this Paper Citation Record lists 68 of 68 outbound references and 0 inbound Pith citation observations for arXiv:2501.10408.

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

pith.paper-citation-record.v1
2501.10408 v1

Coverage vector

measured 68 of 68 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T22:03:46.423506Z

measured 68 of 68 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+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

68 of 68 outbound references displayed

  • verified exact1
  • verified fuzzy52
  • unresolved15
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 5d9f458a-2b9d-42e0-97c9-c9e1efbf47d0 · outbound

This paper cites Survey on speech emotion recognition: Features, classification schemes, and databases,.

Leveraging Cross-Attention Transformer and Multi-Feature Fusion for Cross-Linguistic Speech Emotion Recognition Survey on speech emotion recognition: Features, classification schemes, and databases,

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-10T22:03:46.158505Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:03:46.158505Z digest=sha256:142ec5891cadbf6eae688ea1bd4fae74237fb0a2081eee62f1c7b7e9fb0d4f48

Observation 7fcfe993-29b8-4819-9a9d-b516735e2180 · outbound

This paper cites Automated screening for distress: A perspective for the future,.

Leveraging Cross-Attention Transformer and Multi-Feature Fusion for Cross-Linguistic Speech Emotion Recognition Automated screening for distress: A perspective for the future,

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:03:47.235024Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:03:46.163148Z digest=sha256:16c41d41706ac6658ecb5ddfc36fbf68eb714ab8609f86758547a47314348856

Observation 2136bb00-d04d-4c7c-8408-55edfd3d2f94 · outbound

This paper cites A comprehensive review of speech emotion recognition systems,.

Leveraging Cross-Attention Transformer and Multi-Feature Fusion for Cross-Linguistic Speech Emotion Recognition A comprehensive review of speech emotion recognition systems,

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:03:47.222037Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:03:46.167285Z digest=sha256:ab05c3edba545460ba06cc7c8ed2fa7f76f559bf65aeaa55e5a561ce361f0245

Observation 6bfd99bb-f33e-4e79-b448-8ddcb0ce83e9 · outbound

This paper cites A systematic review on affective computing: Emotion models, databases, and recent advances,.

Leveraging Cross-Attention Transformer and Multi-Feature Fusion for Cross-Linguistic Speech Emotion Recognition A systematic review on affective computing: Emotion models, databases, and recent advances,

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:03:47.208815Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:03:46.171506Z digest=sha256:e8df4435baca4fcc6cca7e630e9fdc13f0bac04717e93fc9634c1da68d38ce1e

Observation f4bdc4c7-2d10-403c-aced-091b912dd74e · outbound

This paper cites Speech emotion recognition based on hmm and svm,.

Leveraging Cross-Attention Transformer and Multi-Feature Fusion for Cross-Linguistic Speech Emotion Recognition Speech emotion recognition based on hmm and svm,

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:03:47.196125Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:03:46.175572Z digest=sha256:d7eeb625f2257e8dc7fddddde95de5e4509977fe1f7c8166053c020e3d799e09

Observation 8e9a929a-100d-4543-a310-aea698f690b2 · outbound

This paper cites Speech emotion recognition using fourier parameters,.

Leveraging Cross-Attention Transformer and Multi-Feature Fusion for Cross-Linguistic Speech Emotion Recognition Speech emotion recognition using fourier parameters,

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:03:47.183388Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:03:46.179384Z digest=sha256:072f0abce5b0ca4ebe7bc42859392ab080d21b8c2d39b7be9070290607fb7b36

Observation cafb2ea4-c30f-4b5d-804b-71580730622a · outbound

This paper cites Implementation and comparison of speech emotion recognition system using gaussian mix- ture model (gmm) and k-nearest neighbor K-NN techniques,.

Leveraging Cross-Attention Transformer and Multi-Feature Fusion for Cross-Linguistic Speech Emotion Recognition Implementation and comparison of speech emotion recognition system using gaussian mix- ture model (gmm) and k-nearest neighbor K-NN techniques,

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:03:47.171983Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:03:46.183781Z digest=sha256:9c2aa26bb61395afcd5fab680ed135075573d451fdb103335de4ef388d30b801

Observation 53bd97bb-f986-429d-bb1e-b3e633253f65 · outbound

This paper cites Speech emotion recognition using deep learning techniques: A review,.

Leveraging Cross-Attention Transformer and Multi-Feature Fusion for Cross-Linguistic Speech Emotion Recognition Speech emotion recognition using deep learning techniques: A review,

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-10T22:03:46.187538Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:03:46.187538Z digest=sha256:0ffa2d80b99a2764a357f773c83e9c5b58b97c1fa07f194b2ce8abe1eb0b0e79

Observation eba3a012-aedf-4141-aac3-2c045f8600fa · outbound

This paper cites Deep learning approaches for speech emotion recognition: State of the art and research challenges,.

Leveraging Cross-Attention Transformer and Multi-Feature Fusion for Cross-Linguistic Speech Emotion Recognition Deep learning approaches for speech emotion recognition: State of the art and research challenges,

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:03:47.151911Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:03:46.191149Z digest=sha256:0aedd165a0fd735cc0ae03c04ad3dc4dd8f68c339e1e58c65ade8c94c026e13d

Observation 10111b15-b7e0-4516-a1bb-3847a9d1bf30 · outbound

This paper cites Speech emotion recognition: A review,.

Leveraging Cross-Attention Transformer and Multi-Feature Fusion for Cross-Linguistic Speech Emotion Recognition Speech emotion recognition: A review,

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:03:47.140142Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:03:46.194664Z digest=sha256:f98189e4d5aabdb9b7e95d293cd2b0d995f39c255469cffd34fb96f88a22d6f9

Observation 7ca597b3-62f9-495e-a587-5efba9288d31 · outbound

This paper cites Self-supervised speech representation learning: A review,.

Leveraging Cross-Attention Transformer and Multi-Feature Fusion for Cross-Linguistic Speech Emotion Recognition Self-supervised speech representation learning: A review,

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:03:47.129132Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:03:46.198403Z digest=sha256:f508d3fcdf39282d90284820b8516b8efd661e49eaa561af8a5ec47d4cc6d3f7

Observation 54ea93b7-b461-4e08-ac93-dcf46326a465 · outbound

This paper cites Cross-corpus speech emotion recognition using semi-supervised transfer non-negative matrix factorization with adapta- tion regularization.

Leveraging Cross-Attention Transformer and Multi-Feature Fusion for Cross-Linguistic Speech Emotion Recognition Cross-corpus speech emotion recognition using semi-supervised transfer non-negative matrix factorization with adapta- tion regularization

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:03:47.117859Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:03:46.202037Z digest=sha256:9ec13884cd39c3500ffaa24766e6eb13f4030b98f3a628ff713eac5fec2f7d03

Observation 5aafa406-d37a-4a45-b8ff-02121f1d7764 · outbound

This paper cites Multisource i-vectors domain adaptation using maximum mean discrepancy based autoencoders,.

Leveraging Cross-Attention Transformer and Multi-Feature Fusion for Cross-Linguistic Speech Emotion Recognition Multisource i-vectors domain adaptation using maximum mean discrepancy based autoencoders,

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:03:47.107450Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:03:46.205681Z digest=sha256:7216ecbea7b0cb490189a973687751d1df11429df7468430fa223f3191785118

Observation 6004547b-3651-4129-b6c9-89687eefa887 · outbound

This paper cites Self-supervised learning for multimedia recommendation,.

Leveraging Cross-Attention Transformer and Multi-Feature Fusion for Cross-Linguistic Speech Emotion Recognition Self-supervised learning for multimedia recommendation,

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-10T22:03:46.209137Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:03:46.209137Z digest=sha256:d48d2bbca15143897ee7cfd77d0c501bbc0f8de447358e37a7bfe838ec1caf4b

Observation f35da031-9485-42b1-8e35-3962b573b406 · outbound

This paper cites V oicepm: A robust privacy measurement on voice anonymity,.

Leveraging Cross-Attention Transformer and Multi-Feature Fusion for Cross-Linguistic Speech Emotion Recognition V oicepm: A robust privacy measurement on voice anonymity,

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:03:47.089422Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:03:46.212888Z digest=sha256:427484f3d36469a0f36963778c5a95d063f5ff737b86b7fbfa3c66f0c7d5059f

Observation 9b40a672-56f6-44db-bbc9-79e3aa93cda2 · outbound

This paper cites EmoBox: Multilingual Multi-corpus Speech Emotion Recognition Toolkit and Benchmark.

Leveraging Cross-Attention Transformer and Multi-Feature Fusion for Cross-Linguistic Speech Emotion Recognition EmoBox: Multilingual Multi-corpus Speech Emotion Recognition Toolkit and Benchmark

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-10T22:03:46.216697Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:03:46.216697Z digest=sha256:80a730fb505ff311a934012f256d86d90c2a8bc51c7e7da1ec68ce34c9df9da2

Observation 93248707-0b57-4517-b528-d7068f787745 · outbound

This paper cites Distilhubert: Speech rep- resentation learning by layer-wise distillation of hidden-unit bert,.

Leveraging Cross-Attention Transformer and Multi-Feature Fusion for Cross-Linguistic Speech Emotion Recognition Distilhubert: Speech rep- resentation learning by layer-wise distillation of hidden-unit bert,

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:03:47.078403Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:03:46.221057Z digest=sha256:269c6fa0ffd6a68a2503eecb3f0136af9f0f60abaa39db99e24ab9bc6bc44a34

Observation 400e1269-1d19-4870-beeb-31daa841da73 · outbound

This paper cites Cross- corpus speech emotion recognition with hubert self-supervised represen- tation,.

Leveraging Cross-Attention Transformer and Multi-Feature Fusion for Cross-Linguistic Speech Emotion Recognition Cross- corpus speech emotion recognition with hubert self-supervised represen- tation,

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:03:47.054835Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:03:46.228550Z digest=sha256:5cd7d722bf4f6bc7ee69f33b3596b93e92c328065dbf14bf8ed0ba9a12327374

Observation 9ca3722d-d12f-4a91-a515-6e85776180bb · outbound

This paper cites Representation learning through cross-modal conditional teacher-student training for speech emotion recognition,.

Leveraging Cross-Attention Transformer and Multi-Feature Fusion for Cross-Linguistic Speech Emotion Recognition Representation learning through cross-modal conditional teacher-student training for speech emotion recognition,

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:03:47.032530Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:03:46.236144Z digest=sha256:94c0f13b6c449035e74a43d0beb755e7471a28007eb3c822c10afcd4566d41a0

Observation e9528ff4-ea07-44b5-8e2c-e783a2cdc060 · outbound

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

Leveraging Cross-Attention Transformer and Multi-Feature Fusion for Cross-Linguistic Speech Emotion Recognition Multi-lingual multi-task speech emotion recognition using wav2vec 2.0,

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:03:47.043852Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:03:46.239811Z digest=sha256:3fbfb331038ac3de03b90060bd81fc7336d84ed1e0ecdcbc672ceca1d0ce7de0

Observation 97025186-4438-4199-ab80-91f3e70e8bf6 · outbound

This paper cites A systematic literature review of speech emotion recognition approaches,.

Leveraging Cross-Attention Transformer and Multi-Feature Fusion for Cross-Linguistic Speech Emotion Recognition A systematic literature review of speech emotion recognition approaches,

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:03:47.020648Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:03:46.243277Z digest=sha256:8c168d91db7faafb938a1e8fa0d97b877130ddaf0b78d9b40a5e6c498af5d9e3

Observation 43f0ceff-e65e-4675-806d-ec65f6e7d3bf · outbound

This paper cites Speech emotion recognition using sequential capsule net- works,.

Leveraging Cross-Attention Transformer and Multi-Feature Fusion for Cross-Linguistic Speech Emotion Recognition Speech emotion recognition using sequential capsule net- works,

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:03:47.008668Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:03:46.246846Z digest=sha256:dcc1fe5e49ed7554b0de3b88f415cf0e267e36bc52f1221018a5f54e3a1ef223

Observation f0550e3e-0284-4f9e-958b-b921ddc39129 · outbound

This paper cites Transformer based unsupervised pre-training for acoustic representation learning,.

Leveraging Cross-Attention Transformer and Multi-Feature Fusion for Cross-Linguistic Speech Emotion Recognition Transformer based unsupervised pre-training for acoustic representation learning,

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:03:46.996977Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:03:46.250373Z digest=sha256:9520b4ff936ed9669e049060349d13598c0bd894f8a58ebbbe67cb427811cf93

Observation 4b49e13e-484d-49cb-9b74-d3734ff4ceff · outbound

This paper cites Contrastive unsupervised learning for speech emotion recognition,.

Leveraging Cross-Attention Transformer and Multi-Feature Fusion for Cross-Linguistic Speech Emotion Recognition Contrastive unsupervised learning for speech emotion recognition,

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:03:46.985001Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:03:46.253761Z digest=sha256:d5f5cad79d58266ffdcf3e6a321bb597284b8e84db3926e85b321aac86a8b530

Observation 343226f7-59e1-4756-ace0-0a571e0216ac · outbound

This paper cites Cross-corpus classification of realistic emotions–some pilot experiments,.

Leveraging Cross-Attention Transformer and Multi-Feature Fusion for Cross-Linguistic Speech Emotion Recognition Cross-corpus classification of realistic emotions–some pilot experiments,

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:03:46.972663Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:03:46.256684Z digest=sha256:53cf8435911a3165321f2c5d6752e607b5869142961315a33b119ae97a890d51

Observation 90c716c7-c6bf-4905-94a4-07fe633321bb · outbound

This paper cites Using multiple databases for training in emotion recognition: To unite or to vote?.

Leveraging Cross-Attention Transformer and Multi-Feature Fusion for Cross-Linguistic Speech Emotion Recognition Using multiple databases for training in emotion recognition: To unite or to vote?

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:03:46.962020Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:03:46.259863Z digest=sha256:9585065fa8e87b32379035fb06537471b02f0bd0ee806294b48c92b56e227ba3

Observation e89833ab-4ca0-44a7-984c-3b6c2cf0ecf0 · outbound

This paper cites Cross lingual speech emotion recognition: Urdu vs. western languages,.

Leveraging Cross-Attention Transformer and Multi-Feature Fusion for Cross-Linguistic Speech Emotion Recognition Cross lingual speech emotion recognition: Urdu vs. western languages,

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:03:46.937417Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:03:46.265679Z digest=sha256:6085acb6b19d600bc43e6d8919b73e23fc883aed8a9f718c5e63af882d02d951

Observation 0b3c17dd-5112-46e6-a076-36c1360e710b · outbound

This paper cites A study on cross-corpus speech emotion recognition and data augmenta- tion,.

Leveraging Cross-Attention Transformer and Multi-Feature Fusion for Cross-Linguistic Speech Emotion Recognition A study on cross-corpus speech emotion recognition and data augmenta- tion,

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:03:46.923837Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:03:46.268532Z digest=sha256:255155bbb7af5de67b6e9409a141c268f4a58a3635dcb59d50c71e20ba787b8c

Observation f14ac591-040d-4b74-b210-26fa306e9e72 · outbound

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

Leveraging Cross-Attention Transformer and Multi-Feature Fusion for Cross-Linguistic Speech Emotion Recognition Wavlm: Large-scale self-supervised pre- training for full stack speech processing,

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-10T22:03:46.271286Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:03:46.271286Z digest=sha256:06389df872adcbbfa2012c370246bcd7b60ea9ead0dc5cd9bb2ab8edfd0bcb59

Observation fa02346d-452d-47ac-91a8-54bdf61fe6c4 · outbound

This paper cites Emotion Recognition from Speech Using Wav2vec 2.0 Embeddings.

Leveraging Cross-Attention Transformer and Multi-Feature Fusion for Cross-Linguistic Speech Emotion Recognition Emotion Recognition from Speech Using Wav2vec 2.0 Embeddings

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-10T22:03:46.274112Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:03:46.274112Z digest=sha256:d958313699de9669fcbf1168940c70d9433d4f2c20b9a0f911306b0f5bdcd0c2

Observation 1a3dadf8-57c4-421f-9ee0-4d15698724f0 · outbound

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

Leveraging Cross-Attention Transformer and Multi-Feature Fusion for Cross-Linguistic Speech Emotion Recognition Hubert: Self-supervised speech representation learning by masked prediction of hidden units,

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-10T22:03:46.277544Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:03:46.277544Z digest=sha256:851c8e079495c03d054983e95213b5ba4ea9697b8d67df787031a405dec96974

Observation c68edca5-7a1a-426c-a7ff-02e20c3b098d · outbound

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

Leveraging Cross-Attention Transformer and Multi-Feature Fusion for Cross-Linguistic Speech Emotion Recognition BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-10T22:03:46.280610Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:03:46.280610Z digest=sha256:0317100a1b90c4684c0b85f42c7717d0e9db9825f346a3e6512c2c9f386d24a1

Observation 037f3f20-ed5d-4395-84af-fe1224603bdc · outbound

This paper cites Unveiling em- bedded features in wav2vec2 and hubert msodels for speech emotion recognition,.

Leveraging Cross-Attention Transformer and Multi-Feature Fusion for Cross-Linguistic Speech Emotion Recognition Unveiling em- bedded features in wav2vec2 and hubert msodels for speech emotion recognition,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:03:46.894905Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:03:46.284910Z digest=sha256:e42161211badc3bce35a6297e443d6bc50e50c0bed2ed7e2c0209b645620a4f8

Observation 338da2a7-2f0a-4d57-b961-6368ccf41018 · outbound

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

Leveraging Cross-Attention Transformer and Multi-Feature Fusion for Cross-Linguistic Speech Emotion Recognition Layer-wise analysis of a self- supervised speech representation model,

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:03:46.879795Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:03:46.288780Z digest=sha256:e61e97fcad234a6749ae4c2d19aebc3bd20670a5aa28c28a6e2a20b777453e3d

Observation 1fa10ff4-f3f1-48d7-ba42-7b07a6951420 · outbound

This paper cites Multiple acoustic features speech emotion recognition using cross-attention transformer,.

Leveraging Cross-Attention Transformer and Multi-Feature Fusion for Cross-Linguistic Speech Emotion Recognition Multiple acoustic features speech emotion recognition using cross-attention transformer,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:03:46.867830Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:03:46.292238Z digest=sha256:ecc05bc130ce93e8fe397ffdf0fdd7f5f4a492a3944c2d68c29e62b8696dab61

Observation f685dcdd-657d-4155-84ac-8a6c61275ade · outbound

This paper cites Speech emotion recognition using local and global features,.

Leveraging Cross-Attention Transformer and Multi-Feature Fusion for Cross-Linguistic Speech Emotion Recognition Speech emotion recognition using local and global features,

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:03:46.854580Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:03:46.295572Z digest=sha256:7078468424cb67d81f8f9b5e24a6750437eb1e71456e5c60eb909e043e133076

Observation cb2f5bd9-4d17-4cab-8f74-c2793d99fdaf · outbound

This paper cites Modeling prosodic features with joint factor analysis for speaker verification,.

Leveraging Cross-Attention Transformer and Multi-Feature Fusion for Cross-Linguistic Speech Emotion Recognition Modeling prosodic features with joint factor analysis for speaker verification,

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-10T22:03:46.299358Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:03:46.299358Z digest=sha256:131a2a2f39bad7cd9a69aafc9fd27e33db6d7da2dfd3a968a9437721a67d717f

Observation d292971c-9eb5-4d50-bf3c-69d234cad1e6 · outbound

This paper cites A novel feature selection method for speech emotion recognition,.

Leveraging Cross-Attention Transformer and Multi-Feature Fusion for Cross-Linguistic Speech Emotion Recognition A novel feature selection method for speech emotion recognition,

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:03:46.833622Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:03:46.302957Z digest=sha256:72f71f8f9bb54b8fa28610d1d09e4ce17a3e06dca77c4515e0f7f06a39586caf

Observation dfc004f2-7f58-48e6-89a4-2625872800b5 · outbound

This paper cites Analysis of linguistic and prosodic features of bilingual arabic–english speakers for speech emotion recognition,.

Leveraging Cross-Attention Transformer and Multi-Feature Fusion for Cross-Linguistic Speech Emotion Recognition Analysis of linguistic and prosodic features of bilingual arabic–english speakers for speech emotion recognition,

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:03:46.819871Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:03:46.306418Z digest=sha256:799b6de981dd33ececfc5961cda86be5d6b00f3f3adac13973b1c64466cb1bfa

Observation 8af5c4ff-fc55-4de5-b71d-676536114824 · outbound

This paper cites Towards an automatic evaluation of the dysarthria level of patients with parkinson’s disease,.

Leveraging Cross-Attention Transformer and Multi-Feature Fusion for Cross-Linguistic Speech Emotion Recognition Towards an automatic evaluation of the dysarthria level of patients with parkinson’s disease,

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-10T22:03:46.310892Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:03:46.310892Z digest=sha256:21c4e23cadfb312ef2df0a2af74f6b24ee6cb6750eb02c15aa36686c1ff3549f

Observation 5337d1f6-a749-4037-a1d9-b67e06b47cbd · outbound

This paper cites Speech emotion recognition based on multiple acoustic features and deep convolutional neural network,.

Leveraging Cross-Attention Transformer and Multi-Feature Fusion for Cross-Linguistic Speech Emotion Recognition Speech emotion recognition based on multiple acoustic features and deep convolutional neural network,

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:03:46.799357Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:03:46.314890Z digest=sha256:9ef123b2ff338d5e3825a0e8a3be7487dbe9028bcfddd53e4b8444d6aac5de51

Observation c56a6026-5de0-47d0-b64f-14c5bcbfcb22 · outbound

This paper cites Speech emotion recognition using mel frequency log spectrogram and deep convolutional neural network,.

Leveraging Cross-Attention Transformer and Multi-Feature Fusion for Cross-Linguistic Speech Emotion Recognition Speech emotion recognition using mel frequency log spectrogram and deep convolutional neural network,

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:03:46.788227Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:03:46.318695Z digest=sha256:b14500b0ab5d6c3c3c1f214f7a82bdcc2e04374ab22f16f41c03f0ff49e752cd

Observation 2e3501cb-d60e-466a-8c92-4c2ec6c94b6a · outbound

This paper cites Learning deep features to recognise speech emotion using merged deep CNN,.

Leveraging Cross-Attention Transformer and Multi-Feature Fusion for Cross-Linguistic Speech Emotion Recognition Learning deep features to recognise speech emotion using merged deep CNN,

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:03:46.778509Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:03:46.323360Z digest=sha256:733486df6a28d7afcd334496ed55afdeb6fe8fb8c2fd03cb5b039c22188944db

Observation aaa42b2d-2d11-4800-a419-be10441767e2 · outbound

This paper cites The SpeakIn Speaker Verification System for Far-Field Speaker Verification Challenge 2022.

Leveraging Cross-Attention Transformer and Multi-Feature Fusion for Cross-Linguistic Speech Emotion Recognition The SpeakIn Speaker Verification System for Far-Field Speaker Verification Challenge 2022

Reference 47

Resolution
verified exact
local_arxiv, observed 2026-08-10T22:03:46.491560Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:03:46.327790Z digest=sha256:c8b500e97e482df3c1052e51e4b9b82f6e08a603777224302a01b65bc555ca4d

Observation 1adcb3af-0096-48bd-982d-03183cda01fb · outbound

This paper cites IEMOCAP: Interactive emotional dyadic motion capture database,.

Leveraging Cross-Attention Transformer and Multi-Feature Fusion for Cross-Linguistic Speech Emotion Recognition IEMOCAP: Interactive emotional dyadic motion capture database,

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:03:46.768265Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:03:46.332005Z digest=sha256:1070c978855125bb9abf828c356fb83834c01c2e026115ebb1154f1130a2bfcb

Observation 10d4eb0b-110f-4a64-8e1b-463a04f36d52 · outbound

This paper cites The ryerson audio-visual database of emotional speech and song RA VDESS: A dynamic, multimodal set of facial and vocal expressions in north american english,.

Leveraging Cross-Attention Transformer and Multi-Feature Fusion for Cross-Linguistic Speech Emotion Recognition The ryerson audio-visual database of emotional speech and song RA VDESS: A dynamic, multimodal set of facial and vocal expressions in north american english,

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:03:46.755318Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:03:46.335878Z digest=sha256:9007d3fb7e5264dffa389cffdda314376f896e4ad1af3d0c7829d74d368187e9

Observation bc1a721e-f373-4eb8-9588-e8a26d4e8a97 · outbound

This paper cites Real- time end-to-end speech emotion recognition with cross-domain adapta- tion,.

Leveraging Cross-Attention Transformer and Multi-Feature Fusion for Cross-Linguistic Speech Emotion Recognition Real- time end-to-end speech emotion recognition with cross-domain adapta- tion,

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:03:46.742387Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:03:46.339578Z digest=sha256:93495f88febca3344c35216cdb6598cfc7b211e993449e900ca615b8cc6b7058

Observation caa75239-bb26-49a2-a7f8-401f5e1cd636 · outbound

This paper cites A database of german emotional speech.

Leveraging Cross-Attention Transformer and Multi-Feature Fusion for Cross-Linguistic Speech Emotion Recognition A database of german emotional speech

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:03:46.729141Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:03:46.343453Z digest=sha256:99d3fcdd5a05bf56a65c45fca8d832964b94b3f77d66dea83879e35412b0b94a

Observation b185e9a2-5251-4935-9818-eec808a3723e · outbound

This paper cites Emovo corpus: an italian emotional speech database,.

Leveraging Cross-Attention Transformer and Multi-Feature Fusion for Cross-Linguistic Speech Emotion Recognition Emovo corpus: an italian emotional speech database,

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:03:46.716831Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:03:46.347276Z digest=sha256:9b6e18e248e9498e6e20538d0d72f500e5e9bea3693a64a93e564d31f2b737fb

Observation 7db1f795-113e-4958-87b5-8f0d9812ddd4 · outbound

This paper cites The mexican emotional speech database (mesd): elaboration and assessment based on machine learning,.

Leveraging Cross-Attention Transformer and Multi-Feature Fusion for Cross-Linguistic Speech Emotion Recognition The mexican emotional speech database (mesd): elaboration and assessment based on machine learning,

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:03:46.703398Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:03:46.351021Z digest=sha256:79d05c4d8504258e60aa549dd53beb8cbc1de159f4fb4f6f7daf6acccaa395a7

Observation 2b29674c-226a-49af-92e2-a3054f1ea25a · outbound

This paper cites Emotional voice conversion: Theory, databases and esd,.

Leveraging Cross-Attention Transformer and Multi-Feature Fusion for Cross-Linguistic Speech Emotion Recognition Emotional voice conversion: Theory, databases and esd,

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-10T22:03:46.354658Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:03:46.354658Z digest=sha256:a5d76c0ffc86fedeeb6575d2cf7a7ac9f313863d5834d410f9e733969a5d91e6

Observation b28167ab-7754-40e5-bda5-81796de291b3 · outbound

This paper cites Towards discriminative representations and unbiased predictions: Class-specific angular softmax for speech emotion recognition.

Leveraging Cross-Attention Transformer and Multi-Feature Fusion for Cross-Linguistic Speech Emotion Recognition Towards discriminative representations and unbiased predictions: Class-specific angular softmax for speech emotion recognition

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:03:46.681547Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:03:46.358869Z digest=sha256:35df4ddabba3151e88446c2168c3e1be6290a8065e8518752076a4c122777757

Observation f877a1a3-1829-47ba-af7a-88ba5f563faf · outbound

This paper cites Improving speech emotion recognition using graph attentive bi-directional gated recurrent unit network,.

Leveraging Cross-Attention Transformer and Multi-Feature Fusion for Cross-Linguistic Speech Emotion Recognition Improving speech emotion recognition using graph attentive bi-directional gated recurrent unit network,

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:03:46.669951Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:03:46.362435Z digest=sha256:886ebb5817e0115cae0ef598f950dd7e83288a4ca08c3fb4e97ad30e8cefc690

Observation 910aa210-3996-44b8-a6af-1394c5706a06 · outbound

This paper cites Hgfm: A hierarchical grained and feature model for acoustic emotion recognition,.

Leveraging Cross-Attention Transformer and Multi-Feature Fusion for Cross-Linguistic Speech Emotion Recognition Hgfm: A hierarchical grained and feature model for acoustic emotion recognition,

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:03:46.657924Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:03:46.366274Z digest=sha256:06ff42480081db49ad83ddb81adf9a3209f0fe309ffb9b63c53f67a40b309559

Observation a9dcfab3-f59b-4bc0-a18a-3285263b20b0 · outbound

This paper cites Cross- corpus speech emotion recognition with hubert self-supervised represen- tation,.

Leveraging Cross-Attention Transformer and Multi-Feature Fusion for Cross-Linguistic Speech Emotion Recognition Cross- corpus speech emotion recognition with hubert self-supervised represen- tation,

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:03:46.646773Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:03:46.370150Z digest=sha256:40367096b37a86438e5b1bddfa1d113e845802fe83c11560321d91c37766fc2b

Observation b319171d-682a-4f14-bbf7-d215ffdd5c9b · outbound

This paper cites Temporal modeling matters: A novel temporal emotional modeling approach for speech emotion recognition,.

Leveraging Cross-Attention Transformer and Multi-Feature Fusion for Cross-Linguistic Speech Emotion Recognition Temporal modeling matters: A novel temporal emotional modeling approach for speech emotion recognition,

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:03:46.635793Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:03:46.374518Z digest=sha256:b66a3b456d14b60c6cabaf232ddbe9610c103a2090e2e837365993a9ff24d2b6

Observation 12670868-5e41-4cfc-ba70-eaa9de08a6bb · outbound

This paper cites Learning multi-scale features for speech emotion recognition with connection attention mechanism,.

Leveraging Cross-Attention Transformer and Multi-Feature Fusion for Cross-Linguistic Speech Emotion Recognition Learning multi-scale features for speech emotion recognition with connection attention mechanism,

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:03:46.622964Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:03:46.378567Z digest=sha256:8c02be9ad99868fd12869cfec7809a7939e39ef7aa64ab3383d829f3abc38940

Observation 9b089bd3-6681-4a5b-bdf6-203a974d190d · outbound

This paper cites Exploring wav2vec 2.0 fine tuning for improved speech emotion recognition,.

Leveraging Cross-Attention Transformer and Multi-Feature Fusion for Cross-Linguistic Speech Emotion Recognition Exploring wav2vec 2.0 fine tuning for improved speech emotion recognition,

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:03:47.065910Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:03:46.382309Z digest=sha256:fa023392f646facd1b6d00d20e60003316327cde17eff311407e135a44f08f8b

Observation ef116f2c-77f8-4266-ba98-430ea4343ea2 · outbound

This paper cites Unsupervised adversarial domain adaptation for cross-lingual speech emotion recognition,.

Leveraging Cross-Attention Transformer and Multi-Feature Fusion for Cross-Linguistic Speech Emotion Recognition Unsupervised adversarial domain adaptation for cross-lingual speech emotion recognition,

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:03:46.610408Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:03:46.385929Z digest=sha256:127e6762d5fba8a19871e565f0ef29ef3babe481bd768d8b198cbc31077424b1

Observation 66fd3c04-cf38-4ab0-897b-42ef636f72b9 · outbound

This paper cites Speech emotion recognition from 3D log-mel spectrograms with deep learning network,.

Leveraging Cross-Attention Transformer and Multi-Feature Fusion for Cross-Linguistic Speech Emotion Recognition Speech emotion recognition from 3D log-mel spectrograms with deep learning network,

Reference 63

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:03:46.597142Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:03:46.390039Z digest=sha256:ee080cf7151bf370322f9c0a8995e5736ab7a9a6102ea02e6830e0279102ee38

Observation 1a243e78-a50c-4836-b71b-d274313efb63 · outbound

This paper cites Fusing visual attention CNN and bag of visual words for cross-corpus speech emotion recognition,.

Leveraging Cross-Attention Transformer and Multi-Feature Fusion for Cross-Linguistic Speech Emotion Recognition Fusing visual attention CNN and bag of visual words for cross-corpus speech emotion recognition,

Reference 64

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:03:46.583333Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:03:46.393861Z digest=sha256:699b86f2c070a11fd958361be2306bb7ef35b3a09081714bdbf52b8eb9400f9c

Observation 0dd1f7e1-74d4-475d-8937-b7ce804bb2bf · outbound

This paper cites Cross corpus multi-lingual speech emotion recognition using ensemble learning,.

Leveraging Cross-Attention Transformer and Multi-Feature Fusion for Cross-Linguistic Speech Emotion Recognition Cross corpus multi-lingual speech emotion recognition using ensemble learning,

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:03:46.949879Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:03:46.397391Z digest=sha256:b285c73d66f37be7762819264dbe9a433d3a04cf048e98031ad23bf1463b4949

Observation 7fe177a5-5e7c-4965-8f01-0b397131db6e · outbound

This paper cites Cross-corpus speech emotion recognition based on few-shot learning and domain adaptation,.

Leveraging Cross-Attention Transformer and Multi-Feature Fusion for Cross-Linguistic Speech Emotion Recognition Cross-corpus speech emotion recognition based on few-shot learning and domain adaptation,

Reference 66

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:03:46.572085Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:03:46.400427Z digest=sha256:2526a48459d49f9a657fd3d01daf6452d979a9f90204efc0a1abe7df762a8a15

Observation 01a88162-f488-419d-9c08-11aa484af918 · outbound

This paper cites Crema-d: Crowd-sourced emotional multimodal actors dataset,.

Leveraging Cross-Attention Transformer and Multi-Feature Fusion for Cross-Linguistic Speech Emotion Recognition Crema-d: Crowd-sourced emotional multimodal actors dataset,

Reference 67

Resolution
unresolved
no resolver link, observed 2026-08-10T22:03:46.404732Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:03:46.404732Z digest=sha256:021b618093b78d2efec43f0fdd400b5b30e420336ad46b32231dd101d9832e96

Observation e771e516-c8f7-4423-9b4d-68f39fb96eb9 · outbound

This paper cites Enhancing cross-language multimodal emotion recognition with dual attention transformers,.

Leveraging Cross-Attention Transformer and Multi-Feature Fusion for Cross-Linguistic Speech Emotion Recognition Enhancing cross-language multimodal emotion recognition with dual attention transformers,

Reference 68

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:03:46.550903Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:03:46.409923Z digest=sha256:4ab9c71f13797a01af0ae59c82f6da16ca62d404b652b7651dc7f957dff88660

Observation 76638cb0-65de-4f8a-8bdc-db5c787a6d3e · outbound

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

Leveraging Cross-Attention Transformer and Multi-Feature Fusion for Cross-Linguistic Speech Emotion Recognition RoBERTa: A Robustly Optimized BERT Pretraining Approach

Reference 69

Resolution
unresolved
no resolver link, observed 2026-08-10T22:03:46.414254Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:03:46.414254Z digest=sha256:bf147d5751e60ac293c433037f9f58e709235215480c72b48ed3e5f391bd9072

Observation 438ddb48-b1ce-4bc2-871a-c440909606d6 · outbound

This paper cites XLS-R: Self-supervised Cross-lingual Speech Representation Learning at Scale.

Leveraging Cross-Attention Transformer and Multi-Feature Fusion for Cross-Linguistic Speech Emotion Recognition XLS-R: Self-supervised Cross-lingual Speech Representation Learning at Scale

Reference 70

Resolution
unresolved
no resolver link, observed 2026-08-10T22:03:46.418497Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:03:46.418497Z digest=sha256:f25676b55937c74e7f12d1354f955560f0a40b37e9ba8907c83b824cc23ae5df

Observation f224eeb2-635a-4306-8855-a694e17bbd5d · outbound

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

Leveraging Cross-Attention Transformer and Multi-Feature Fusion for Cross-Linguistic Speech Emotion Recognition Robust speech recognition via large-scale weak supervi- sion,

Reference 71

Resolution
unresolved
no resolver link, observed 2026-08-10T22:03:46.423506Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:03:46.423506Z digest=sha256:e93bd33a45f6894180722395003f2e5f4f0d0d966353b8276ae0e1640892855a

Pith citing papers

No inbound Pith citation observations are available.