{"as_of":"2026-08-19T16:45:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:cbf2cfa5c2caf9e87f98d1a61169856941f564d3ca40a14f233eeaef390556a5","coverage":[{"denominator":13,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":13,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-10T16:58:54.892906Z","state":"measured"},{"denominator":13,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":13,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-19T06:32:44.657259+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2501.12674/citation-record","integrity":"/paper/2501.12674/integrity","json":"/paper/2501.12674/citation-record.json","paper":"/paper/2501.12674"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T16:58:55.203486Z","title":"Speech emotion recognition using speech feature and word embedding","venue":null,"work_id":"2a572c35-0cbd-46fe-8a03-7312687bb0b8","year":2019},"citing_paper":{"arxiv_id":"2501.12674","last_updated":"2025-01-22T06:23:36Z","snapshot_observed_at":"2026-08-19T12:45:48.884736Z","submitted_at":"2025-01-22T06:23:36Z","title":"EmoTech: A Multi-modal Speech Emotion Recognition Using Multi-source Low-level Information with Hybrid Recurrent Network","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-10T16:58:54.838548Z"},"links":{"citing_paper":"/paper/2501.12674"},"observation_digest":"sha256:7b5d0d463d6599ec52efb7c022ac7182c645c74d13d6e23fddcfb6b7de61156d","observation_id":"cc3d66b0-e429-49b5-94e2-ff1ec8c89469","resolution":{"observed_at":"2026-08-10T16:58:55.207651Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T16:58:55.190256Z","title":"Iemocap: Interactive emotional dyadic motion capture database","venue":null,"work_id":"1f5f915a-32c3-4835-ab3b-135f024efbca","year":2008},"citing_paper":{"arxiv_id":"2501.12674","last_updated":"2025-01-22T06:23:36Z","snapshot_observed_at":"2026-08-19T12:45:48.884736Z","submitted_at":"2025-01-22T06:23:36Z","title":"EmoTech: A Multi-modal Speech Emotion Recognition Using Multi-source Low-level Information with Hybrid Recurrent Network","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-10T16:58:54.843590Z"},"links":{"citing_paper":"/paper/2501.12674"},"observation_digest":"sha256:f30bcc20ae6d64fd772f5b0b3ab82038c6e33adb6c4206e1665e80a8b559ad25","observation_id":"94b75a0d-18dd-4c41-81b1-45eb41ed2951","resolution":{"observed_at":"2026-08-10T16:58:55.194292Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T16:58:55.176376Z","title":"Deep neural networks for emotion recognition combining audio and transcripts","venue":null,"work_id":"67ccfd91-8ae0-4362-91b2-9a839ce09486","year":2018},"citing_paper":{"arxiv_id":"2501.12674","last_updated":"2025-01-22T06:23:36Z","snapshot_observed_at":"2026-08-19T12:45:48.884736Z","submitted_at":"2025-01-22T06:23:36Z","title":"EmoTech: A Multi-modal Speech Emotion Recognition Using Multi-source Low-level Information with Hybrid Recurrent Network","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-10T16:58:54.847920Z"},"links":{"citing_paper":"/paper/2501.12674"},"observation_digest":"sha256:49ede0e70800d1d8a256ee7ec64d2e83c5b3b4b40920661538196d2951d83696","observation_id":"c51d7b0e-c523-4bb5-8d68-2d2bacaf4c38","resolution":{"observed_at":"2026-08-10T16:58:55.180886Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T16:58:55.161469Z","title":"Combining speech-based and linguistic classifiers to recognize emotion in user spoken utterances","venue":null,"work_id":"d0b8a982-32dc-4c54-b723-ce94be8e7664","year":2019},"citing_paper":{"arxiv_id":"2501.12674","last_updated":"2025-01-22T06:23:36Z","snapshot_observed_at":"2026-08-19T12:45:48.884736Z","submitted_at":"2025-01-22T06:23:36Z","title":"EmoTech: A Multi-modal Speech Emotion Recognition Using Multi-source Low-level Information with Hybrid Recurrent Network","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-10T16:58:54.852222Z"},"links":{"citing_paper":"/paper/2501.12674"},"observation_digest":"sha256:a711b850e35e16edae1c2dde1ecc7b1dbc25551e23b7fac24ec064f2a0b48ccd","observation_id":"b6aaeeb3-9454-4bcd-b530-9f817666a0d9","resolution":{"observed_at":"2026-08-10T16:58:55.166326Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T16:58:55.146378Z","title":"Speech emotion recognition with acoustic and lexical features","venue":null,"work_id":"88fdf3aa-ef8f-4a02-b682-dd0806f82179","year":2015},"citing_paper":{"arxiv_id":"2501.12674","last_updated":"2025-01-22T06:23:36Z","snapshot_observed_at":"2026-08-19T12:45:48.884736Z","submitted_at":"2025-01-22T06:23:36Z","title":"EmoTech: A Multi-modal Speech Emotion Recognition Using Multi-source Low-level Information with Hybrid Recurrent Network","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-10T16:58:54.857021Z"},"links":{"citing_paper":"/paper/2501.12674"},"observation_digest":"sha256:c699c4d66a63499f0d373f043b32e0611f250e9073958c46c931b10ebecee7e4","observation_id":"291fc7b0-e529-4972-859f-d2ae6bbf7e9b","resolution":{"observed_at":"2026-08-10T16:58:55.151376Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T16:58:55.027103Z","title":"Com- bining acoustic and language information for emotion recognition","venue":null,"work_id":"f015ff4d-c4ef-4b5e-b2dc-9234c3aed742","year":2002},"citing_paper":{"arxiv_id":"2501.12674","last_updated":"2025-01-22T06:23:36Z","snapshot_observed_at":"2026-08-19T12:45:48.884736Z","submitted_at":"2025-01-22T06:23:36Z","title":"EmoTech: A Multi-modal Speech Emotion Recognition Using Multi-source Low-level Information with Hybrid Recurrent Network","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-10T16:58:54.861849Z"},"links":{"citing_paper":"/paper/2501.12674"},"observation_digest":"sha256:601feb7122ead2920a31a6599269581ee43693d428b836e914b2e9e6db5402c1","observation_id":"01c9c80d-17e1-4bcf-8f87-c5992779c4da","resolution":{"observed_at":"2026-08-10T16:58:55.031713Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T16:58:55.011331Z","title":"Automatic speech emotion recognition using machine learning: digital transformation of mental health","venue":null,"work_id":"e6ab2597-ae74-424b-aab4-c2ec09532070","year":2022},"citing_paper":{"arxiv_id":"2501.12674","last_updated":"2025-01-22T06:23:36Z","snapshot_observed_at":"2026-08-19T12:45:48.884736Z","submitted_at":"2025-01-22T06:23:36Z","title":"EmoTech: A Multi-modal Speech Emotion Recognition Using Multi-source Low-level Information with Hybrid Recurrent Network","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-10T16:58:54.866760Z"},"links":{"citing_paper":"/paper/2501.12674"},"observation_digest":"sha256:9263e0c5b7e92dfe944bba563b91769b09d8d5002b01a54bbf59909b12c3b01d","observation_id":"cb100c73-3b54-4138-87de-f965635b6f65","resolution":{"observed_at":"2026-08-10T16:58:55.016573Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T16:58:54.995051Z","title":"Emotion in speech: Recognition and application to call centers","venue":null,"work_id":"51103202-c119-44c4-9cc6-177a616b819c","year":1999},"citing_paper":{"arxiv_id":"2501.12674","last_updated":"2025-01-22T06:23:36Z","snapshot_observed_at":"2026-08-19T12:45:48.884736Z","submitted_at":"2025-01-22T06:23:36Z","title":"EmoTech: A Multi-modal Speech Emotion Recognition Using Multi-source Low-level Information with Hybrid Recurrent Network","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-10T16:58:54.871108Z"},"links":{"citing_paper":"/paper/2501.12674"},"observation_digest":"sha256:37fcac800ff8dba2279991036b050656bcdb70a16e3512847d0d16f49bdc7284","observation_id":"aca4fe94-e260-40fc-81cb-5246d0cdb87b","resolution":{"observed_at":"2026-08-10T16:58:55.000516Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T16:58:54.981042Z","title":"A text independent speech emotion recognition based on convolutional neural network","venue":null,"work_id":"3ec39611-810f-4327-870f-1cbc0d7ac82b","year":2023},"citing_paper":{"arxiv_id":"2501.12674","last_updated":"2025-01-22T06:23:36Z","snapshot_observed_at":"2026-08-19T12:45:48.884736Z","submitted_at":"2025-01-22T06:23:36Z","title":"EmoTech: A Multi-modal Speech Emotion Recognition Using Multi-source Low-level Information with Hybrid Recurrent Network","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-10T16:58:54.875252Z"},"links":{"citing_paper":"/paper/2501.12674"},"observation_digest":"sha256:ef90baba0557a73bf7d97e44531ec51744b702c2249a25fa7ca542f9be0ab81b","observation_id":"60e79c1a-1fc8-4126-89ad-c333ec590c23","resolution":{"observed_at":"2026-08-10T16:58:54.985165Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1804.05788","last_updated":"2019-11-06T20:10:26Z","snapshot_observed_at":"2026-08-19T12:45:39.909787Z","submitted_at":"2018-04-16T16:58:37Z","title":"Multi-Modal Emotion recognition on IEMOCAP Dataset using Deep Learning","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1804.05788","snapshot_observed_at":"2026-08-10T16:58:54.879516Z","title":"Multi-modal emotion recognition on iemocap dataset using deep learning","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2501.12674","last_updated":"2025-01-22T06:23:36Z","snapshot_observed_at":"2026-08-19T12:45:48.884736Z","submitted_at":"2025-01-22T06:23:36Z","title":"EmoTech: A Multi-modal Speech Emotion Recognition Using Multi-source Low-level Information with Hybrid Recurrent Network","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-10T16:58:54.879516Z"},"links":{"cited_paper":"/paper/1804.05788","citing_paper":"/paper/2501.12674"},"observation_digest":"sha256:dbbee59d5ea8dd3d77e5e21438ba8ac925338f6e75dc92feb1aab990051aa602","observation_id":"2a045957-88fb-468c-8298-239066a8cfa2","resolution":{"observed_at":"2026-08-10T16:58:54.879516Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T16:58:54.967625Z","title":"Speech emotion recognition using spectrogram & phoneme embedding","venue":null,"work_id":"a89ec67c-7c76-44f4-b394-c492d641b497","year":2018},"citing_paper":{"arxiv_id":"2501.12674","last_updated":"2025-01-22T06:23:36Z","snapshot_observed_at":"2026-08-19T12:45:48.884736Z","submitted_at":"2025-01-22T06:23:36Z","title":"EmoTech: A Multi-modal Speech Emotion Recognition Using Multi-source Low-level Information with Hybrid Recurrent Network","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-10T16:58:54.884079Z"},"links":{"citing_paper":"/paper/2501.12674"},"observation_digest":"sha256:06648d3587e1c056add75eb2e2f82426caf1b9e0c30bbe747de427cbc5a3b102","observation_id":"2dddc164-b200-435a-b8dc-10b6cad7946e","resolution":{"observed_at":"2026-08-10T16:58:54.971782Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T16:58:54.953612Z","title":"Multimodal speech emotion recognition using audio and text","venue":null,"work_id":"e357be5c-84f2-4534-8fe3-6cd13e54916e","year":2018},"citing_paper":{"arxiv_id":"2501.12674","last_updated":"2025-01-22T06:23:36Z","snapshot_observed_at":"2026-08-19T12:45:48.884736Z","submitted_at":"2025-01-22T06:23:36Z","title":"EmoTech: A Multi-modal Speech Emotion Recognition Using Multi-source Low-level Information with Hybrid Recurrent Network","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-10T16:58:54.888412Z"},"links":{"citing_paper":"/paper/2501.12674"},"observation_digest":"sha256:092010edb4f47d5967d134544afdaaa7c1eac55077681196bb91b95a3d84ab92","observation_id":"35a70011-fa13-4aa9-9539-32f49eea1b3c","resolution":{"observed_at":"2026-08-10T16:58:54.957881Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T16:58:54.937991Z","title":"Emotional chatting machine: Emotional conversation generation with internal and external memory","venue":null,"work_id":"c013039a-3ee5-4ce4-a464-0b91fbc97c3e","year":2018},"citing_paper":{"arxiv_id":"2501.12674","last_updated":"2025-01-22T06:23:36Z","snapshot_observed_at":"2026-08-19T12:45:48.884736Z","submitted_at":"2025-01-22T06:23:36Z","title":"EmoTech: A Multi-modal Speech Emotion Recognition Using Multi-source Low-level Information with Hybrid Recurrent Network","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-10T16:58:54.892906Z"},"links":{"citing_paper":"/paper/2501.12674"},"observation_digest":"sha256:68a5483468686bcc5a76109d6060f5584518ce99a288a45345d848359d67ca0e","observation_id":"b9d321c8-bb49-4f84-8d85-1b0eae86d614","resolution":{"observed_at":"2026-08-10T16:58:54.943863Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2501.12674","last_updated":"2025-01-22T06:23:36Z","latest_version":1,"primary_category":"eess.AS","snapshot_observed_at":"2026-08-19T12:45:48.884736Z","submitted_at":"2025-01-22T06:23:36Z","title":"EmoTech: A Multi-modal Speech Emotion Recognition Using Multi-source Low-level Information with Hybrid Recurrent Network"},"reference_resolution":{"displayed":13,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":1,"verified_exact":0,"verified_fuzzy":12},"total_outbound_references":13},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"thesis":"As of 19 August 2026, this Paper Citation Record lists 13 of 13 outbound references and 0 inbound Pith citation observations for arXiv:2501.12674."}