{
    "paper_id": "O12-1011",
    "header": {
        "generated_with": "S2ORC 1.0.0",
        "date_generated": "2023-01-19T08:03:12.930517Z"
    },
    "title": "The Design of Chinese Character Learning System Based on Phonetic Components",
    "authors": [
        {
            "first": "Chia-Hui",
            "middle": [],
            "last": "Chang",
            "suffix": "",
            "affiliation": {
                "laboratory": "",
                "institution": "National Central University",
                "location": {}
            },
            "email": ""
        },
        {
            "first": "Wen-Pen",
            "middle": [],
            "last": "Wu",
            "suffix": "",
            "affiliation": {
                "laboratory": "",
                "institution": "National Central University",
                "location": {}
            },
            "email": ""
        }
    ],
    "year": "",
    "venue": null,
    "identifiers": {},
    "abstract": "An increasing number of people learn Chinese as second language in the world. About 60% of Chinese characters are picto-phonetic compounds which are composed of a phonetic component (PC) and semantic component. Therefore one can make a guess at a character's pronunciation and meaning from its phonetic and semantic component for a new character. For this reason we propose an order of phonetic components based on pronunciation strength frequency and number of strokes for efficient learning with proper pronunciation rules and graph recognition. We adopt stem-deriving instructional method which extends each phonetic component with different radical component to derive new picto-phonetic compounds of similar pronunciation. Via simulation, the top 400 phonetic components and their",
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        "paper_id": "O12-1011",
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        "abstract": [
            {
                "text": "An increasing number of people learn Chinese as second language in the world. About 60% of Chinese characters are picto-phonetic compounds which are composed of a phonetic component (PC) and semantic component. Therefore one can make a guess at a character's pronunciation and meaning from its phonetic and semantic component for a new character. For this reason we propose an order of phonetic components based on pronunciation strength frequency and number of strokes for efficient learning with proper pronunciation rules and graph recognition. We adopt stem-deriving instructional method which extends each phonetic component with different radical component to derive new picto-phonetic compounds of similar pronunciation. Via simulation, the top 400 phonetic components and their",
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                "section": "Abstract",
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        ],
        "body_text": [
            {
                "text": "picto-phonetic extensions are enough for the recognition of 60% characters in general articles; and top 800 phonetic components can help recognition of 90% characters of general news articles.",
                "cite_spans": [],
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                "section": "",
                "sec_num": null
            },
            {
                "text": "Keywords: picto-phonetic compounds phonetic component component stem-deriving instructional method. ",
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                "sec_num": null
            },
            {
                "text": "EQUATION",
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                        "end": 8,
                        "text": "EQUATION",
                        "ref_id": "EQREF",
                        "raw_str": ") P C ( ) P C ( * ) ( ) ( 4 2 PC PC Score (2) (2) (1) ( (2) )",
                        "eq_num": "(2)"
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            {
                "text": ":",
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            },
            {
                "text": "(1) ",
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                "section": "",
                "sec_num": null
            },
            {
                "text": "K-NN K Jaccard x y Similarity(x,y)=Jaccard(M x M y ) B A B A B A Jaccard ) , ( M x wW(x) RC(w) W(x) x RC(w) w",
                "cite_spans": [],
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                "section": "",
                "sec_num": null
            },
            {
                "text": "Proceedings of the Twenty-Fourth Conference on Computational Linguistics and Speech Processing(ROCLING 2012)",
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                "section": "",
                "sec_num": null
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        ],
        "back_matter": [],
        "bib_entries": {
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                "ref_id": "b0",
                "title": "Proceedings of the Twenty-Fourth Conference on Computational Linguistics and Speech Processing",
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                "raw_text": "Proceedings of the Twenty-Fourth Conference on Computational Linguistics and Speech Processing (ROCLING 2012)",
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        "ref_entries": {
            "FIGREF0": {
                "type_str": "figure",
                "text": "Proceedings of the Twenty-Fourth Conference on Computational Linguistics and Speech Processing(ROCLING 2012)",
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            "TABREF0": {
                "content": "<table><tr><td colspan=\"9\">Proceedings of the Twenty-Fourth Conference on Computational Linguistics and Speech Processing (ROCLING 2012)</td></tr><tr><td/><td/><td/><td/><td/><td/><td/><td/><td>[11]</td></tr><tr><td/><td/><td/><td/><td/><td colspan=\"2\">1453</td><td/><td/></tr><tr><td>3.1</td><td/><td/><td/><td/><td/><td colspan=\"3\">(pictograph system)</td></tr><tr><td colspan=\"3\">(alphabet system) ROCLING2011</td><td/><td/><td/><td/><td/><td/></tr><tr><td>(Hanyu pinyin)</td><td/><td colspan=\"5\">(Chinese phonetic symbols) 2012[8] [10]</td><td/><td/></tr><tr><td>400</td><td/><td/><td/><td/><td/><td/><td/><td/></tr><tr><td/><td/><td>800</td><td/><td/><td/><td/><td/><td/></tr><tr><td/><td/><td/><td/><td/><td/><td>1993</td><td/><td/></tr><tr><td colspan=\"2\">[5]</td><td/><td/><td/><td/><td/><td/><td/></tr><tr><td>2010</td><td/><td/><td/><td/><td colspan=\"4\">ROCLING 2010[3]</td></tr><tr><td/><td/><td colspan=\"2\">: 14598</td><td/><td/><td/><td/><td/></tr><tr><td colspan=\"3\">ROCLING 2011[2]</td><td/><td/><td/><td/><td/><td/></tr><tr><td/><td/><td>:</td><td/><td/><td/><td/><td/><td/></tr><tr><td>( 1 PC Score</td><td>[1] )</td><td>PC(</td><td>P C (</td><td>*</td><td>) P C (</td><td>4783</td><td>)</td><td>3026 (1)</td></tr><tr><td/><td/><td/><td/><td/><td/><td colspan=\"2\">2011 [4]</td><td>[1+1]</td></tr></table>",
                "text": "Proceedings of the Twenty-Fourth Conference on Computational Linguistics and Speech Processing(ROCLING 2012)",
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