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{
    "pk": 31715,
    "title": "The Learning  of Weak Noun Declension in German: Children vs. Artificial Network Models",
    "subtitle": null,
    "abstract": "Different artificial networks are presented with\nthe task of learning weak noim declension in\nG e r m a n . This morphological rule is difficult for\ncue-based models because it requires the\nresolution of conflicting cue-predictions and a\ndynamic positional coding due to suffixation. In\naddition to that its 'task frequency* is very low in\nnatural language. This property is preserved in\nthe training input to study the models' abilities to\nhandle low frequency niles. The performances of\nthree kinds of networks:\n1) feedforward networks\n2) recurrent networks\n3) recurrent networks with short term memory\n( S T M ) capacity\nare compared to empirical findings of an\nelicitation experiment with 129 subjects of ages\n5-9 and adult age.",
    "language": "eng",
    "license": {
        "name": "",
        "short_name": "",
        "text": null,
        "url": ""
    },
    "keywords": [],
    "section": "Submitted Presentations",
    "is_remote": true,
    "remote_url": "https://escholarship.org/uc/item/3t03s5k3",
    "frozenauthors": [
        {
            "first_name": "Peter",
            "middle_name": "",
            "last_name": "Indefrey",
            "name_suffix": "",
            "institution": "Max-Planck-Institute for Psycholinguistics",
            "department": ""
        },
        {
            "first_name": "Rainer",
            "middle_name": "",
            "last_name": "Goebel",
            "name_suffix": "",
            "institution": "University of Braunschweig",
            "department": ""
        }
    ],
    "date_submitted": null,
    "date_accepted": null,
    "date_published": "1993-01-01T18:00:00Z",
    "render_galley": null,
    "galleys": [
        {
            "label": "PDF",
            "type": "pdf",
            "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/31715/galley/22783/download/"
        }
    ]
}