Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-10T16:58:54.892906Z
Paper Citation Record · LEDGER
As of 18 August 2026, this Paper Citation Record lists 13 of 13 outbound references and 0 inbound Pith citation observations for arXiv:2501.12674.
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 2026-08-10T16:58:54.892906Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00
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
13 of 13 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation cc3d66b0-e429-49b5-94e2-ff1ec8c89469 · outbound
EmoTech: A Multi-modal Speech Emotion Recognition Using Multi-source Low-level Information with Hybrid Recurrent Network Speech emotion recognition using speech feature and word embedding
Reference 1
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 94b75a0d-18dd-4c41-81b1-45eb41ed2951 · outbound
EmoTech: A Multi-modal Speech Emotion Recognition Using Multi-source Low-level Information with Hybrid Recurrent Network Iemocap: Interactive emotional dyadic motion capture database
Reference 2
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation c51d7b0e-c523-4bb5-8d68-2d2bacaf4c38 · outbound
EmoTech: A Multi-modal Speech Emotion Recognition Using Multi-source Low-level Information with Hybrid Recurrent Network Deep neural networks for emotion recognition combining audio and transcripts
Reference 3
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation b6aaeeb3-9454-4bcd-b530-9f817666a0d9 · outbound
EmoTech: A Multi-modal Speech Emotion Recognition Using Multi-source Low-level Information with Hybrid Recurrent Network Combining speech-based and linguistic classifiers to recognize emotion in user spoken utterances
Reference 4
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 291fc7b0-e529-4972-859f-d2ae6bbf7e9b · outbound
EmoTech: A Multi-modal Speech Emotion Recognition Using Multi-source Low-level Information with Hybrid Recurrent Network Speech emotion recognition with acoustic and lexical features
Reference 5
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 01c9c80d-17e1-4bcf-8f87-c5992779c4da · outbound
EmoTech: A Multi-modal Speech Emotion Recognition Using Multi-source Low-level Information with Hybrid Recurrent Network Com- bining acoustic and language information for emotion recognition
Reference 6
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation cb100c73-3b54-4138-87de-f965635b6f65 · outbound
EmoTech: A Multi-modal Speech Emotion Recognition Using Multi-source Low-level Information with Hybrid Recurrent Network Automatic speech emotion recognition using machine learning: digital transformation of mental health
Reference 7
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation aca4fe94-e260-40fc-81cb-5246d0cdb87b · outbound
EmoTech: A Multi-modal Speech Emotion Recognition Using Multi-source Low-level Information with Hybrid Recurrent Network Emotion in speech: Recognition and application to call centers
Reference 8
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 60e79c1a-1fc8-4126-89ad-c333ec590c23 · outbound
EmoTech: A Multi-modal Speech Emotion Recognition Using Multi-source Low-level Information with Hybrid Recurrent Network A text independent speech emotion recognition based on convolutional neural network
Reference 9
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 2a045957-88fb-468c-8298-239066a8cfa2 · outbound
EmoTech: A Multi-modal Speech Emotion Recognition Using Multi-source Low-level Information with Hybrid Recurrent Network Multi-Modal Emotion recognition on IEMOCAP Dataset using Deep Learning
Reference 10
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2dddc164-b200-435a-b8dc-10b6cad7946e · outbound
EmoTech: A Multi-modal Speech Emotion Recognition Using Multi-source Low-level Information with Hybrid Recurrent Network Speech emotion recognition using spectrogram & phoneme embedding
Reference 11
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 35a70011-fa13-4aa9-9539-32f49eea1b3c · outbound
EmoTech: A Multi-modal Speech Emotion Recognition Using Multi-source Low-level Information with Hybrid Recurrent Network Multimodal speech emotion recognition using audio and text
Reference 12
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation b9d321c8-bb49-4f84-8d85-1b0eae86d614 · outbound
EmoTech: A Multi-modal Speech Emotion Recognition Using Multi-source Low-level Information with Hybrid Recurrent Network Emotional chatting machine: Emotional conversation generation with internal and external memory
Reference 13
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
No inbound Pith citation observations are available.