Paper Citation Record · LEDGER

learning discriminative features from spectrograms using center loss for speech emotion recognition

As of 18 August 2026, this Paper Citation Record lists 24 of 24 outbound references and 2 inbound Pith citation observations for arXiv:2501.01103.

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

pith.paper-citation-record.v1
2501.01103 v1

Coverage vector

measured 24 of 24 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T22:38:07.327578Z

measured 26 of 26 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T17:58:27.670639Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-10T22:38:07.442914Z

Reference resolution

24 of 24 outbound references displayed

verified exact1
verified fuzzy16
unresolved6
parse uncertain0
malformed identifier0
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 00d42533-dcd5-42cf-94d1-6900e135ca22 · outbound

This paper cites learning discriminative features from spectrograms using center loss for speech emotion recognition.

learning discriminative features from spectrograms using center loss for speech emotion recognition learning discriminative features from spectrograms using center loss for speech emotion recognition

Reference 1

Resolution: metadata mismatch; local_arxiv, observed 2026-08-10T22:38:07.448576Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 36bd4ca7-596b-461c-98ac-412d06a0d376 · outbound

This paper cites Softmax cross-entropy loss and center loss are utilized in our model.

learning discriminative features from spectrograms using center loss for speech emotion recognition Softmax cross-entropy loss and center loss are utilized in our model

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:38:07.811310Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 214d9255-56eb-441f-8930-e42f9558083a · outbound

This paper cites an unresolved cited work.

learning discriminative features from spectrograms using center loss for speech emotion recognition Unresolved cited work

Reference 3

Resolution: unresolved; raw_fallback, observed 2026-08-10T22:38:07.784147Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation c409bfdd-3359-4a0a-b935-ba461edfccb5 · outbound

This paper cites The 2-D PCA embedding illustrated the discriminative power when using center loss, which enables the neural network to learn more effective fea- tures for SER.

learning discriminative features from spectrograms using center loss for speech emotion recognition The 2-D PCA embedding illustrated the discriminative power when using center loss, which enables the neural network to learn more effective fea- tures for SER

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:38:07.748780Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 0af75344-cf35-438f-bd0a-a45a0e8d7176 · outbound

This paper cites High-level feature representation us- ing recurrent neural network for speech emotion recognition,.

learning discriminative features from spectrograms using center loss for speech emotion recognition High-level feature representation us- ing recurrent neural network for speech emotion recognition,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:38:07.657156Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation d3a38afb-5f58-468b-a044-453409d38692 · outbound

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

learning discriminative features from spectrograms using center loss for speech emotion recognition Survey on speech emotion recognition: Features, classification schemes, and databases,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:38:07.730883Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 5e126802-ded1-45b4-9c67-ac4ec2904a23 · outbound

This paper cites Representation learn- ing: A review and new perspectives,.

learning discriminative features from spectrograms using center loss for speech emotion recognition Representation learn- ing: A review and new perspectives,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:38:07.713518Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation fd50b331-1a34-4c8a-998a-c4bae09ade1c · outbound

This paper cites Deep learning,.

learning discriminative features from spectrograms using center loss for speech emotion recognition Deep learning,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:38:07.694533Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 6508531a-99da-4012-8c5e-dfe9b11d7c4f · outbound

This paper cites Speech emotion recognition using deep neural network and extreme learning machine,.

learning discriminative features from spectrograms using center loss for speech emotion recognition Speech emotion recognition using deep neural network and extreme learning machine,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:38:07.676541Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 5b1e43a5-d38d-41af-aba8-8120c44a911a · outbound

This paper cites A pairwise discriminative task for speech emotion recognition.

learning discriminative features from spectrograms using center loss for speech emotion recognition A pairwise discriminative task for speech emotion recognition

Reference 10

Resolution: verified exact; local_arxiv, observed 2026-08-10T22:38:07.423688Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 66dffbd0-2aa1-4c55-96dc-ed072601b11b · outbound

This paper cites Adieu features? end- to-end speech emotion recognition using a deep convolutional recurrent network,.

learning discriminative features from spectrograms using center loss for speech emotion recognition Adieu features? end- to-end speech emotion recognition using a deep convolutional recurrent network,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:38:07.633351Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 7220c9d3-ae53-4ec6-88d5-a366d33b0201 · outbound

This paper cites Efficient emotion recognition from speech using deep learning on spectrograms,.

learning discriminative features from spectrograms using center loss for speech emotion recognition Efficient emotion recognition from speech using deep learning on spectrograms,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:38:07.615437Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 5bc453a8-bb35-4dbc-8425-ef49311e26f5 · outbound

This paper cites Interpreting ambiguous emotional expressions,.

learning discriminative features from spectrograms using center loss for speech emotion recognition Interpreting ambiguous emotional expressions,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:38:07.599649Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation ebdd3147-434d-49de-898f-101606c40e08 · outbound

This paper cites Long short term memory recurrent neural network based encoding method for emotion recognition in video,.

learning discriminative features from spectrograms using center loss for speech emotion recognition Long short term memory recurrent neural network based encoding method for emotion recognition in video,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:38:07.582406Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation e8530d8d-f9b2-419f-a13d-3e1744b1555e · outbound

This paper cites Deep residual learning for image recognition,.

learning discriminative features from spectrograms using center loss for speech emotion recognition Deep residual learning for image recognition,

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-10T22:38:07.303804Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 45a46464-f96f-48fc-ade7-1e6a49e02ff6 · outbound

This paper cites Speech emotion recog- nition from variable-length inputs with triplet loss function,.

learning discriminative features from spectrograms using center loss for speech emotion recognition Speech emotion recog- nition from variable-length inputs with triplet loss function,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:38:07.566153Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 89e0c713-d30a-4584-bd90-853cbf50244a · outbound

This paper cites Facenet: A uni- fied embedding for face recognition and clustering,.

learning discriminative features from spectrograms using center loss for speech emotion recognition Facenet: A uni- fied embedding for face recognition and clustering,

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-10T22:38:07.285782Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eac04706-a383-463c-a9e5-9ca8ea23f47c · outbound

This paper cites A discriminative fea- ture learning approach for deep face recognition,.

learning discriminative features from spectrograms using center loss for speech emotion recognition A discriminative fea- ture learning approach for deep face recognition,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:38:07.537330Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation af4253cd-691e-4fc5-accb-a98ab5e6e898 · outbound

This paper cites Very Deep Convolutional Networks for Large-Scale Image Recognition.

learning discriminative features from spectrograms using center loss for speech emotion recognition Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-10T22:38:07.297168Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4f453310-dea6-4cb1-8463-9eb530c58abc · outbound

This paper cites Learning phrase representations using rnn encoder-decoder for statistical ma- chine translation,.

learning discriminative features from spectrograms using center loss for speech emotion recognition Learning phrase representations using rnn encoder-decoder for statistical ma- chine translation,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:38:07.506235Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 08c7f035-925f-4187-b5f7-37e0fc9c2840 · outbound

This paper cites Delving deep into rec- tifiers: Surpassing human-level performance on imagenet clas- sification,.

learning discriminative features from spectrograms using center loss for speech emotion recognition Delving deep into rec- tifiers: Surpassing human-level performance on imagenet clas- sification,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:38:07.484558Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 92d9f58e-fb2c-4903-a796-b7b01ddf931f · outbound

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

learning discriminative features from spectrograms using center loss for speech emotion recognition Iemocap: Interactive emotional dyadic motion capture database,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:38:07.466894Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 077eb142-083e-487c-8873-9904b6696e90 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

learning discriminative features from spectrograms using center loss for speech emotion recognition Adam: A Method for Stochastic Optimization

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-10T22:38:07.327578Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 66552f95-9898-45b6-ad76-149c984f4770 · outbound

This paper cites an unresolved cited work.

learning discriminative features from spectrograms using center loss for speech emotion recognition Unresolved cited work

Reference 32

Resolution: unresolved; raw_fallback, observed 2026-08-10T22:38:07.765647Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Pith citing papers

Observation 00d42533-dcd5-42cf-94d1-6900e135ca22 · inbound