Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-05-25T00:55:33.165353Z
Paper Citation Record · LEDGER
As of 5 August 2026, this Paper Citation Record lists 29 of 29 outbound references and 1 inbound Pith citation observation for arXiv:1907.03572.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-05-25T00:55:33.165353Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-05T06:32:48.257954+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-05-25T00:55:33.165353Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-05-25T00:56:30.432183Z
29 of 29 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 469abebe-6835-4a2c-83a8-b33028251e1b · outbound
Towards Explainable Music Emotion Recognition: The Route via Mid-level Features Towards Explainable Music Emotion Recognition: The Route via Mid-level Features
Reference 1
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Observation d97b07c9-a1a3-4da8-9ec8-bc5a95ff1160 · outbound
Towards Explainable Music Emotion Recognition: The Route via Mid-level Features Unresolved cited work
Reference 2
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Observation bdb98fbb-4753-45ba-8f12-d3a0dd26e78e · outbound
Towards Explainable Music Emotion Recognition: The Route via Mid-level Features The idea is that they should represent musi- cal characteristics that are easily perceived and recognized by most listeners, without any music-theoretical training
Reference 3
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Observation d6f583a0-c014-47fd-a40f-1138ae996453 · outbound
Towards Explainable Music Emotion Recognition: The Route via Mid-level Features Our starting point is Aljanaki & Soleymani’sMid-level Percep- tual Features dataset [1], which provides mid-level fea- ture annotations
Reference 4
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Towards Explainable Music Emotion Recognition: The Route via Mid-level Features The ratings range from 1 to 10 and were scaled by a factor of 0.1 before being used for our experiments
Reference 5
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Towards Explainable Music Emotion Recognition: The Route via Mid-level Features A2Mid2E-Joint
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Towards Explainable Music Emotion Recognition: The Route via Mid-level Features cost of explainability
Reference 7
Source-reported events for the cited work
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Towards Explainable Music Emotion Recognition: The Route via Mid-level Features minorness
Reference 8
Source-reported events for the cited work
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Towards Explainable Music Emotion Recognition: The Route via Mid-level Features Unresolved cited work
Reference 9
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Observation 6e9f6d03-64da-4be4-8f2e-74c90158769d · outbound
Towards Explainable Music Emotion Recognition: The Route via Mid-level Features Con Espressione
Reference 10
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Observation a90951f8-3214-4225-9b97-5a289ada61d0 · outbound
Towards Explainable Music Emotion Recognition: The Route via Mid-level Features A data- driven approach to mid-level perceptual musical fea- ture modeling
Reference 11
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Observation 7f085cb3-d40f-42ba-bec5-fcf894182f71 · outbound
Towards Explainable Music Emotion Recognition: The Route via Mid-level Features Developing a benchmark for emotional anal- ysis of music
Reference 12
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Observation b3733db9-099b-45f9-8ee5-6dcbdd49bdec · outbound
Towards Explainable Music Emotion Recognition: The Route via Mid-level Features Automatically esti- mating emotion in music with deep long-short term memory recurrent neural networks
Reference 13
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Observation 61656878-5352-46f7-bfe6-d29eae9377db · outbound
Towards Explainable Music Emotion Recognition: The Route via Mid-level Features Vuoskoski
Reference 14
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Observation c95ffa89-3589-434c-b60d-24f3540ac92e · outbound
Towards Explainable Music Emotion Recognition: The Route via Mid-level Features Using listener-based perceptual features as intermediate rep- resentations in music information retrieval
Reference 15
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Observation b9fe6fad-0916-4009-9519-4d4ca289ead1 · outbound
Towards Explainable Music Emotion Recognition: The Route via Mid-level Features Auto- mated music emotion recognition: A systematic evalu- ation
Reference 16
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Observation 46896de6-44d2-4ffc-a7c5-789178629a46 · outbound
Towards Explainable Music Emotion Recognition: The Route via Mid-level Features Music emotion recognition: A state of the art review
Reference 17
Source-reported events for the cited work
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Observation ac05970e-1cd0-49ba-ab69-b4a3b172f48a · outbound
Towards Explainable Music Emotion Recognition: The Route via Mid-level Features Neuron activation profiles for interpreting convolu- tional speech recognition models
Reference 18
Source-reported events for the cited work
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Observation 4cd5a1ef-fbb8-4dc7-9873-b9c9c9bb21fa · outbound
Towards Explainable Music Emotion Recognition: The Route via Mid-level Features Music emotion recognition based on two- level support vector classification
Reference 19
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Observation 3871df8d-1c11-45d6-a1fb-44f3bee147c0 · outbound
Towards Explainable Music Emotion Recognition: The Route via Mid-level Features Interpretable Machine Learn- ing
Reference 20
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Observation 53177972-26b6-4ccc-b772-ed67ac5d2f94 · outbound
Towards Explainable Music Emotion Recognition: The Route via Mid-level Features Multi-modal mu- sic emotion recognition: A new dataset, methodology and comparative analysis
Reference 21
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Towards Explainable Music Emotion Recognition: The Route via Mid-level Features Multi-modal mu- sic emotion recognition: A new dataset, methodology and comparative analysis
Reference 22
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Towards Explainable Music Emotion Recognition: The Route via Mid-level Features Speaker recogni- tion from raw waveform with sincnet
Reference 23
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Observation 94ebe304-87fb-4798-96b4-51338b4bcd69 · outbound
Towards Explainable Music Emotion Recognition: The Route via Mid-level Features Optimized scoring sys- tems: Toward trust in machine learning for healthcare and criminal justice
Reference 24
Source-reported events for the cited work
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Observation a994901f-321a-4aaa-a6fa-cc780d0bee59 · outbound
Towards Explainable Music Emotion Recognition: The Route via Mid-level Features A circumplex model of affect
Reference 25
Source-reported events for the cited work
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Observation db51e897-7e72-4e30-b3ca-038126363bc7 · outbound
Towards Explainable Music Emotion Recognition: The Route via Mid-level Features Very deep convolutional networks for large-scale image recogni- tion
Reference 26
Source-reported events for the cited work
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Observation 1ed60551-15ba-45ab-89bb-995eb60342c9 · outbound
Towards Explainable Music Emotion Recognition: The Route via Mid-level Features Getting closer to the essence of mu- sic: The Con Espressione Manifesto
Reference 27
Source-reported events for the cited work
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Observation 1f7e657c-5cce-418c-9ac4-52b0649af96b · outbound
Towards Explainable Music Emotion Recognition: The Route via Mid-level Features emotion in music
Reference 28
Source-reported events for the cited work
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Observation 3d7429d4-dbd6-4a29-a445-9296a52504ad · outbound
Towards Explainable Music Emotion Recognition: The Route via Mid-level Features Bridge the semantic gap between pop mu- sic acoustic feature and emotion: Build an interpretable model
Reference 29
Source-reported events for the cited work
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Observation 469abebe-6835-4a2c-83a8-b33028251e1b · inbound
Towards Explainable Music Emotion Recognition: The Route via Mid-level Features Towards Explainable Music Emotion Recognition: The Route via Mid-level Features
Reference 1
Source-reported events for the cited work
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