Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-06-26T22:32:15.878239Z
Paper Citation Record · LEDGER
As of 16 August 2026, this Paper Citation Record lists 79 of 79 outbound references and 0 inbound Pith citation observations for arXiv:2606.18228.
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 2026-06-26T22:32:15.878239Z
One-hop event checks from named stored sources.
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Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
79 of 79 outbound references displayed
External citation measurements
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Observation 757680e2-a735-454e-b821-44402f7f40ac · outbound
MAJIC: Leveraging Articulatory Motion for Speech-based Emotion Recognition Ai-powered chatbots as emotion-aware virtual assistants: Enhancing student support and engagement in higher education,
Reference 1
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Observation 0997e9bc-eb2f-4108-9a75-9f9a404a889e · outbound
MAJIC: Leveraging Articulatory Motion for Speech-based Emotion Recognition emotion2vec: Self-supervised pre-training for speech emotion repre- sentation,
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Observation 4074abb3-65c8-479d-8044-0dda9e28bc5b · outbound
MAJIC: Leveraging Articulatory Motion for Speech-based Emotion Recognition Enhancing speech emotion recognition through a cross-dataset analysis: Exploring improved models,
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Observation a017f571-08a4-4c7d-85b4-0271501d5aaf · outbound
MAJIC: Leveraging Articulatory Motion for Speech-based Emotion Recognition Exploring the potential of convolutional neural networks in sequential data analysis: A comparative study with lstms and bilstms,
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Observation 660abba8-a77c-4fe4-b687-715b95911ea4 · outbound
MAJIC: Leveraging Articulatory Motion for Speech-based Emotion Recognition Iemocap: Interactive emotional dyadic motion capture database,
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Observation 51d69b0b-01c1-4e76-aca1-d5f3e1d03f95 · outbound
MAJIC: Leveraging Articulatory Motion for Speech-based Emotion Recognition The ryerson audio-visual database of emotional speech and song (ravdess): A dynamic, multimodal set of facial and vocal expressions in north american english,
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MAJIC: Leveraging Articulatory Motion for Speech-based Emotion Recognition Text-based emo- tion detection: Advances, challenges, and opportunities,
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Observation 40b4a428-a469-49a1-b6e3-8faba54b39d2 · outbound
MAJIC: Leveraging Articulatory Motion for Speech-based Emotion Recognition A survey of state-of-the-art approaches for emotion recognition in text,
Reference 8
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Observation d94cef6a-8015-47e4-ad39-563e55fae4d1 · outbound
MAJIC: Leveraging Articulatory Motion for Speech-based Emotion Recognition Kjeldsen: Design issues for vision-based computer... - google scholar,
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Observation 77177e46-7863-450d-93e4-b8eb4fc056a8 · outbound
MAJIC: Leveraging Articulatory Motion for Speech-based Emotion Recognition The limitations for expression recognition in computer vision introduced by facial masks,
Reference 10
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Observation 2a938058-5853-43fc-985d-f5d24dc2d3e5 · outbound
MAJIC: Leveraging Articulatory Motion for Speech-based Emotion Recognition M3er: Multiplicative multimodal emotion recognition using facial, textual, and speech cues,
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Observation ccfb7920-ab2c-4b59-9d2f-de6b327acf34 · outbound
MAJIC: Leveraging Articulatory Motion for Speech-based Emotion Recognition Deap: A database for emotion analysis; using physiological signals,
Reference 12
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Observation 6b54b2e2-2f3c-4a77-94ce-0a5022845ee7 · outbound
MAJIC: Leveraging Articulatory Motion for Speech-based Emotion Recognition A multimodal database for affect recognition and implicit tagging,
Reference 13
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Observation a5e0432f-5f0f-4a7c-8153-8307e0efcc6f · outbound
MAJIC: Leveraging Articulatory Motion for Speech-based Emotion Recognition Decaf: Meg-based multimodal database for decoding affective physiological responses,
Reference 14
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Observation 8f3d583f-cee3-436f-ac15-891222ab0b8c · outbound
MAJIC: Leveraging Articulatory Motion for Speech-based Emotion Recognition Articulatory correlates of prosodic control: Emotion and emphasis,
Reference 15
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Observation 9f9955e8-dec1-4825-ab23-d9878f343c43 · outbound
MAJIC: Leveraging Articulatory Motion for Speech-based Emotion Recognition Measure- ments of articulatory variation in expressive speech for a set of swedish vowels,
Reference 16
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Observation 6463b0f6-bc7d-44e4-ad60-d07baab04962 · outbound
MAJIC: Leveraging Articulatory Motion for Speech-based Emotion Recognition Articu- lation constrained learning with application to speech emotion recogni- tion,
Reference 17
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Observation 4ebd54b9-55e4-49ab-bc1a-63c3b5990131 · outbound
MAJIC: Leveraging Articulatory Motion for Speech-based Emotion Recognition A study of emotional speech articulation using a fast magnetic resonance imaging technique
Reference 18
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Observation 71345edb-8b32-4687-8f19-bc5347147ada · outbound
MAJIC: Leveraging Articulatory Motion for Speech-based Emotion Recognition Robust Speech Recognition via Large-Scale Weak Supervision
Reference 19
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Observation 6f171147-b62a-4c82-908a-63045e7b08ec · outbound
MAJIC: Leveraging Articulatory Motion for Speech-based Emotion Recognition bert-base-uncased-emotion,
Reference 20
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Observation 9edbab7b-0c85-4009-8ed2-308c01edae6b · outbound
MAJIC: Leveraging Articulatory Motion for Speech-based Emotion Recognition A circumplex model of affect
Reference 21
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Observation 9a465b36-23ac-4b6c-80d3-96cb422a9bf1 · outbound
MAJIC: Leveraging Articulatory Motion for Speech-based Emotion Recognition Muteit: Jaw motion based unvoiced command recognition using earable,
Reference 22
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Observation 400ba333-9685-4850-831b-628449ceee07 · outbound
MAJIC: Leveraging Articulatory Motion for Speech-based Emotion Recognition Jawthenticate: Microphone-free speech-based authentication using jaw motion and facial vibrations,
Reference 23
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Observation 412d6971-e46c-413b-b546-1cd34774cb3d · outbound
MAJIC: Leveraging Articulatory Motion for Speech-based Emotion Recognition Unvoiced: Designing an llm-assisted unvoiced user interface using earables,
Reference 24
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Observation 9e654e13-2278-486a-894b-44626248b1ce · outbound
MAJIC: Leveraging Articulatory Motion for Speech-based Emotion Recognition Face-mic: inferring live speech and speaker identity via subtle facial dynamics captured by ar/vr motion sensors,
Reference 25
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Observation ae7a3154-451d-4591-b9cc-82fcc0ba8f88 · outbound
MAJIC: Leveraging Articulatory Motion for Speech-based Emotion Recognition Prosody in Phonetics: Definition and Examples,
Reference 26
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Observation 6561a0e8-2ce8-4ada-ae8c-a945c796376f · outbound
MAJIC: Leveraging Articulatory Motion for Speech-based Emotion Recognition A new approach of audio emotion recognition,
Reference 27
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Observation 24dd37fc-af78-4a13-8004-6d1d2e201262 · outbound
MAJIC: Leveraging Articulatory Motion for Speech-based Emotion Recognition The acoustic cue of fear: investigation of acoustic param- eters of speech containing fear,
Reference 28
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Observation 0811f08c-237b-4134-8a00-0c1ffb405555 · outbound
MAJIC: Leveraging Articulatory Motion for Speech-based Emotion Recognition Analysis of emotion recog- nition using facial expressions, speech and multimodal information,
Reference 29
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Observation 55596e0f-7898-45cf-8b48-786355a1a83a · outbound
MAJIC: Leveraging Articulatory Motion for Speech-based Emotion Recognition Control of coarticulatory patterns of tongue and jaw movement in speech,
Reference 30
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Observation c80776ea-840a-48ed-85c0-ed794e1e8b8d · outbound
MAJIC: Leveraging Articulatory Motion for Speech-based Emotion Recognition An articu- latory study of emotional speech production
Reference 31
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Observation 100df60b-9290-42a4-811e-bed41a19dfd4 · outbound
MAJIC: Leveraging Articulatory Motion for Speech-based Emotion Recognition Articulatory characteristics of expressive speech in activation-evaluation space,
Reference 32
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Observation 398f3fbc-3951-4cbd-ba41-547aa41f743c · outbound
MAJIC: Leveraging Articulatory Motion for Speech-based Emotion Recognition Articulatory-acoustic analyses of mandarin words in emotional context speech for smart campus,
Reference 33
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Observation 34994827-67e5-4edb-9ef9-9f5321d67318 · outbound
MAJIC: Leveraging Articulatory Motion for Speech-based Emotion Recognition Emotion recog- nition involving physiological and speech signals: A comprehensive review,
Reference 34
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Observation 4057d159-8292-4396-9f07-15f70d43951e · outbound
MAJIC: Leveraging Articulatory Motion for Speech-based Emotion Recognition Jawsense: recognizing unvoiced sound using a low-cost ear-worn system,
Reference 35
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Observation 9a25a143-a12f-40c1-816e-31209acfe18e · outbound
MAJIC: Leveraging Articulatory Motion for Speech-based Emotion Recognition Tramba: A hybrid transformer and mamba architecture for practical audio and bone conduction speech super resolution and enhancement on mobile and wearable platforms,
Reference 36
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Observation 35e3b136-406f-4470-bc3a-eacc07ec0edf · outbound
MAJIC: Leveraging Articulatory Motion for Speech-based Emotion Recognition Rethinking gesture phases: Articulatory features of gestural movement?
Reference 37
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Observation 9db808f7-7d3e-4ad9-b831-4ddafbbe7d77 · outbound
MAJIC: Leveraging Articulatory Motion for Speech-based Emotion Recognition Specific respiratory pat- terns distinguish among human basic emotions,
Reference 38
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Observation 6d567c54-6000-46f3-b121-2ef345edb314 · outbound
MAJIC: Leveraging Articulatory Motion for Speech-based Emotion Recognition Evaluation of gait smoothness in patients with stroke undergoing rehabilitation: Comparison between two metrics,
Reference 39
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Observation 4a56a4d0-84ce-456a-9345-768634e4b4b2 · outbound
MAJIC: Leveraging Articulatory Motion for Speech-based Emotion Recognition Spectral arc length as a method to quantify pharyngeal high-resolution manometric curve smoothness,
Reference 40
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Observation 23fdcc45-9d53-43eb-8a64-c101bb4847f4 · outbound
MAJIC: Leveraging Articulatory Motion for Speech-based Emotion Recognition Affect bursts as evolutionary precursors of speech and music,
Reference 41
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Observation bc01fcdf-b064-4f20-8623-19b492b927a4 · outbound
MAJIC: Leveraging Articulatory Motion for Speech-based Emotion Recognition Validity and reliability of nonverbal voice measures as indicators of stressor-provoked anxiety,
Reference 42
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MAJIC: Leveraging Articulatory Motion for Speech-based Emotion Recognition Comparing fear and anxiety chemosignals: Do they modulate facial muscle activity and facilitate identifying facial expressions?
Reference 43
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Observation 27d44506-02c4-4495-8eca-f0c99caafbf3 · outbound
MAJIC: Leveraging Articulatory Motion for Speech-based Emotion Recognition Emotion recognition in the noise applying large acoustic feature sets,
Reference 44
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Observation ddb2338e-d4ee-4290-8c8f-8b28a1e4f4a0 · outbound
MAJIC: Leveraging Articulatory Motion for Speech-based Emotion Recognition opensmile–the munich versatile and fast open-source audio feature extractor,
Reference 45
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Observation 462ae446-5b39-45a8-acb2-fbf0183231a0 · outbound
MAJIC: Leveraging Articulatory Motion for Speech-based Emotion Recognition A comparison of machine learning algorithms and feature sets for automatic vocal emotion recognition in speech,
Reference 46
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Observation 19957c49-9dcc-4d51-84f0-6a74af187b7f · outbound
MAJIC: Leveraging Articulatory Motion for Speech-based Emotion Recognition RoBERTa: A Robustly Optimized BERT Pretraining Approach
Reference 47
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Observation ed75b989-e633-4c77-8e80-39dbe4780284 · outbound
MAJIC: Leveraging Articulatory Motion for Speech-based Emotion Recognition A survey on multi-task learning,
Reference 48
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Observation 8f694f02-886c-4025-9690-8dbbeb26c541 · outbound
MAJIC: Leveraging Articulatory Motion for Speech-based Emotion Recognition Whispering wearables: Multimodal approach to silent speech recognition with head-worn devices,
Reference 49
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Reference 50
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Reference 53
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Reference 54
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Reference 55
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Reference 58
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MAJIC: Leveraging Articulatory Motion for Speech-based Emotion Recognition Emotional Voice Messages (EMOVOME) database: emotion recognition in spontaneous voice messages
Reference 59
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Reference 67
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Reference 70
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Reference 74
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Reference 77
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Reference 78
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MAJIC: Leveraging Articulatory Motion for Speech-based Emotion Recognition Each participant expressed each emotion 20 times
Reference 79
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