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{
    "paper_id": "O12-1009",
    "header": {
        "generated_with": "S2ORC 1.0.0",
        "date_generated": "2023-01-19T08:03:02.780978Z"
    },
    "title": "A Prediction Module for Taiwanese Tone Sandhi Based on the Decision Tree Algorithm",
    "authors": [
        {
            "first": "Neng-Huang",
            "middle": [],
            "last": "Pan",
            "suffix": "",
            "affiliation": {
                "laboratory": "",
                "institution": "Chienkuo Technology University",
                "location": {}
            },
            "email": "nhpan@cc.ctu.edu.tw"
        },
        {
            "first": "Ming-Shing",
            "middle": [],
            "last": "Yu",
            "suffix": "",
            "affiliation": {},
            "email": "msyu@dragon.nchu.edu.tw"
        },
        {
            "first": "Pei-Chun",
            "middle": [],
            "last": "Tsai",
            "suffix": "",
            "affiliation": {},
            "email": ""
        }
    ],
    "year": "",
    "venue": null,
    "identifiers": {},
    "abstract": "Taiwanese tone sandhi problem is one of the important research issues for Taiwanese Text-to-Speech systems. In word level, we can use the general tone sandhi rules to deal with the Taiwanese tone sandhi problem. The tone sandhi becomes more difficult in sentence level because of that the general tone sandhi rules for words may not apply at each word in a sentence. In this paper we proposed a module to deal with the Taiwanese tone sandhi problem for Chinese to Taiwanese Text-to-Speech systems. We adopt Decision tree C5.0 algorithm accompanied with three Special Cases generated from training data to predict the tone sandhi of each syllable. In this module, the accuracy of the inside test and outside test are 93.42%",
    "pdf_parse": {
        "paper_id": "O12-1009",
        "_pdf_hash": "",
        "abstract": [
            {
                "text": "Taiwanese tone sandhi problem is one of the important research issues for Taiwanese Text-to-Speech systems. In word level, we can use the general tone sandhi rules to deal with the Taiwanese tone sandhi problem. The tone sandhi becomes more difficult in sentence level because of that the general tone sandhi rules for words may not apply at each word in a sentence. In this paper we proposed a module to deal with the Taiwanese tone sandhi problem for Chinese to Taiwanese Text-to-Speech systems. We adopt Decision tree C5.0 algorithm accompanied with three Special Cases generated from training data to predict the tone sandhi of each syllable. In this module, the accuracy of the inside test and outside test are 93.42%",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Abstract",
                "sec_num": null
            }
        ],
        "body_text": [
            {
                "text": "and 91.13%, respectively. Keywords: Taiwanese Tone Sandhi, Text-to-Speech System, Decision Tree.",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "",
                "sec_num": null
            },
            {
                "text": "(Tonal Language) (Tone Sandhi)",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "",
                "sec_num": null
            },
            {
                "text": "/ / / / / / / / / / / / /to2/ /de7/ /to1 de7/ /ziim2/ /sien1/ /ziim3/ /dong1/ /dong2/ /dong3/ /dok4/ /dong5/ /dong6/ /dong7/ /dok8/ /dong0/ /dok0/ 9 8 /tau5 tiann3/ [3] [4]",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "",
                "sec_num": null
            },
            {
                "text": "Proceedings of the Twenty-Fourth Conference on Computational Linguistics and Speech Processing (ROCLING 2012) ",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "",
                "sec_num": null
            },
            {
                "text": "dong0 dong0 dong1 dong2 dong6 dong3 dong5 dong7 dok0 dok0 dok2 dok2 dok3 dok3 dok4 dok8 dok9",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "",
                "sec_num": null
            },
            {
                "text": "Proceedings of the Twenty-Fourth Conference on Computational Linguistics and Speech Processing(ROCLING 2012)",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "",
                "sec_num": null
            }
        ],
        "back_matter": [],
        "bib_entries": {
            "BIBREF0": {
                "ref_id": "b0",
                "title": "A Mandarin to Taiwanese Min Nan Machine Translation System with Speech Synthesis of Taiwanese Min Nan",
                "authors": [
                    {
                        "first": "C",
                        "middle": [
                            "J"
                        ],
                        "last": "Lin",
                        "suffix": ""
                    },
                    {
                        "first": "H",
                        "middle": [
                            "H"
                        ],
                        "last": "Chen",
                        "suffix": ""
                    }
                ],
                "year": 1999,
                "venue": "Internal Journal of Computational Linguistic and Chinese Language Processing",
                "volume": "4",
                "issue": "1",
                "pages": "59--84",
                "other_ids": {},
                "num": null,
                "urls": [],
                "raw_text": "C. J. Lin and H. H. Chen,\"A Mandarin to Taiwanese Min Nan Machine Translation System with Speech Synthesis of Taiwanese Min Nan,\" Internal Journal of Computational Linguistic and Chinese Language Processing, Vol. 4, No. 1, pp. 59-84, 1999.",
                "links": null
            },
            "BIBREF1": {
                "ref_id": "b1",
                "title": "Proceedings of the Twenty-Fourth Conference on Computational Linguistics and Speech Processing",
                "authors": [],
                "year": null,
                "venue": "",
                "volume": "",
                "issue": "",
                "pages": "",
                "other_ids": {},
                "num": null,
                "urls": [],
                "raw_text": "Proceedings of the Twenty-Fourth Conference on Computational Linguistics and Speech Processing (ROCLING 2012)",
                "links": null
            },
            "BIBREF3": {
                "ref_id": "b3",
                "title": "Proceedings of the Twenty-Fourth Conference on Computational Linguistics and Speech Processing",
                "authors": [],
                "year": null,
                "venue": "",
                "volume": "",
                "issue": "",
                "pages": "",
                "other_ids": {},
                "num": null,
                "urls": [],
                "raw_text": "Proceedings of the Twenty-Fourth Conference on Computational Linguistics and Speech Processing (ROCLING 2012)",
                "links": null
            }
        },
        "ref_entries": {
            "TABREF0": {
                "content": "<table><tr><td colspan=\"6\">Proceedings of the Twenty-Fourth Conference on Computational Linguistics and Speech Processing (ROCLING 2012)</td></tr><tr><td/><td colspan=\"4\">[12] Special Case</td></tr><tr><td/><td>C5.0</td><td>(</td><td>) [7]</td><td>(</td><td>)</td></tr><tr><td colspan=\"4\">/sim1/ Chinese Gigaword Third Edition 1.</td><td>/sim7/</td></tr><tr><td/><td/><td colspan=\"2\">/gu2/</td><td>/gu1/</td></tr><tr><td/><td/><td colspan=\"2\">/kiam3/</td><td>/kiam2/</td></tr><tr><td/><td/><td colspan=\"2\">/kut4/</td><td>/kut2/</td></tr><tr><td>( )</td><td>Special Case</td><td colspan=\"2\">/dai5/</td><td>/dai3/ ( /dai7/ (</td><td>) )</td></tr><tr><td/><td/><td colspan=\"2\">/ghua7/</td><td>/ghua3/ Vt</td><td>94.74%</td></tr><tr><td/><td>Vt</td><td colspan=\"2\">/ik8/</td><td>/ik3/</td><td>Special Case</td></tr><tr><td>( )</td><td>C5.0</td><td/><td/><td/></tr><tr><td colspan=\"2\">[1][4][8-10]</td><td/><td>[1]</td><td/></tr><tr><td/><td colspan=\"2\">(Decision Tree)</td><td/><td/></tr><tr><td/><td/><td colspan=\"3\">/zong1 tong1 hu2/</td><td>[9]</td></tr><tr><td>[2]</td><td/><td/><td/><td/></tr><tr><td/><td/><td>[8]</td><td/><td/></tr><tr><td/><td>3672</td><td/><td colspan=\"2\">[6] 50960</td><td>2772</td><td>38508</td><td>(</td></tr><tr><td>75.5%)</td><td>900</td><td/><td>12452</td><td colspan=\"2\">6593 ( 24.5%)</td><td>35543</td></tr><tr><td>5</td><td colspan=\"2\">84%</td><td/><td>[7]</td></tr><tr><td/><td>583</td><td colspan=\"2\">8138</td><td/><td>85.84%</td></tr><tr><td/><td/><td/><td colspan=\"2\">C5.0</td><td>Special Case</td></tr><tr><td/><td/><td/><td colspan=\"3\">C5.0 CART CHAID</td><td>QUEST</td></tr><tr><td/><td>C5.0</td><td/><td/><td/><td>C5.0</td></tr><tr><td/><td/><td/><td/><td/><td>C5.0</td></tr><tr><td/><td/><td/><td/><td>(</td><td>)</td><td>(Information Gain Value)</td></tr><tr><td/><td>[11]</td><td/><td/><td/></tr><tr><td>( )</td><td/><td/><td/><td/></tr><tr><td/><td>C5.0</td><td/><td/><td/></tr></table>",
                "text": "Proceedings of the Twenty-Fourth Conference on Computational Linguistics and Speech Processing (ROCLING 2012)Proceedings of the Twenty-Fourth Conference on Computational Linguistics and Speech Processing (ROCLING 2012)",
                "type_str": "table",
                "num": null,
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}