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| "date_generated": "2023-01-19T08:10:09.366314Z" | |
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| "title": "A Study on Representation Learning Techniques for Extractive Spoken Document Summarization", | |
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| "first": "Kai-Wun", | |
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| "institution": "Information Engineering National Taiwan Normal University {60247065S", | |
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| { | |
| "first": "Berlin", | |
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| "institution": "Information Engineering National Taiwan Normal University {60247065S", | |
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| "email": "berlin@ntnu.edu.tw" | |
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| { | |
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| "institution": "Information Engineering National Taiwan Normal University {60247065S", | |
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| "email": "kychen@iis.sinica.edu.tw" | |
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| { | |
| "first": "Kuan-Yu", | |
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| "last": "\u9673\u51a0\u5b87", | |
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| { | |
| "first": "Shih-Hung", | |
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| "last": "Chen", | |
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| }, | |
| { | |
| "first": "Hsin-Min", | |
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| "last": "Liu", | |
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| { | |
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| "last": "Wang", | |
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| "bib_entries": { | |
| "BIBREF0": { | |
| "ref_id": "b0", | |
| "title": "The automatic creation of literature abstracts", | |
| "authors": [ | |
| { | |
| "first": "H", | |
| "middle": [ | |
| "P" | |
| ], | |
| "last": "Luhn", | |
| "suffix": "" | |
| } | |
| ], | |
| "year": 1958, | |
| "venue": "IBM Journal of Research and Development", | |
| "volume": "2", | |
| "issue": "2", | |
| "pages": "159--165", | |
| "other_ids": {}, | |
| "num": null, | |
| "urls": [], | |
| "raw_text": "H. P. Luhn, \"The automatic creation of literature abstracts,\" IBM Journal of Research and Development, Vol. 2, No. 2, pp. 159-165, 1958.", | |
| "links": null | |
| }, | |
| "BIBREF1": { | |
| "ref_id": "b1", | |
| "title": "A risk-aware modeling framework for speech summarization", | |
| "authors": [ | |
| { | |
| "first": "B", | |
| "middle": [], | |
| "last": "Chen", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "S.-H", | |
| "middle": [], | |
| "last": "Lin", | |
| "suffix": "" | |
| } | |
| ], | |
| "year": 2012, | |
| "venue": "IEEE Transactions on Audio, Speech and Language Processing", | |
| "volume": "20", | |
| "issue": "1", | |
| "pages": "199--210", | |
| "other_ids": {}, | |
| "num": null, | |
| "urls": [], | |
| "raw_text": "B. Chen and S.-H. Lin, \"A risk-aware modeling framework for speech summarization,\" IEEE Transactions on Audio, Speech and Language Processing, Vol. 20, No. 1, pp. 199-210, 2012.", | |
| "links": null | |
| }, | |
| "BIBREF2": { | |
| "ref_id": "b2", | |
| "title": "Extractive broadcast news summarization leveraging recurrent neural network language modeling techniques", | |
| "authors": [ | |
| { | |
| "first": "K.-Y", | |
| "middle": [], | |
| "last": "Chen", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "S.-H", | |
| "middle": [], | |
| "last": "Liu", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "B", | |
| "middle": [], | |
| "last": "Chen", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "H.-M", | |
| "middle": [], | |
| "last": "Wang", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "E.-E", | |
| "middle": [], | |
| "last": "Jan", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "W.-L", | |
| "middle": [], | |
| "last": "Hsu", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "H.-H", | |
| "middle": [], | |
| "last": "Chen", | |
| "suffix": "" | |
| } | |
| ], | |
| "year": 2015, | |
| "venue": "Speech, and Language Processing", | |
| "volume": "23", | |
| "issue": "", | |
| "pages": "1322--1334", | |
| "other_ids": {}, | |
| "num": null, | |
| "urls": [], | |
| "raw_text": "K.-Y. Chen, S.-H. Liu, B. Chen, H.-M. Wang, E.-E. Jan, W.-L. Hsu and H.-H. Chen, \"Extractive broadcast news summarization leveraging recurrent neural network language modeling techniques,\" IEEE/ACM Transactions on Audio, Speech, and Language Processing, Vol. 23, No. 8, pp. 1322-1334, 2015.", | |
| "links": null | |
| }, | |
| "BIBREF3": { | |
| "ref_id": "b3", | |
| "title": "Combining relevance language modeling and clarity measure for extractive speech summarization", | |
| "authors": [ | |
| { | |
| "first": "S.-H", | |
| "middle": [], | |
| "last": "Liu", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "K.-Y", | |
| "middle": [], | |
| "last": "Chen", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "B", | |
| "middle": [], | |
| "last": "Chen", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "H.-M", | |
| "middle": [], | |
| "last": "Wang", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "H.-C", | |
| "middle": [], | |
| "last": "Yen", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "W.-L", | |
| "middle": [], | |
| "last": "Hsu", | |
| "suffix": "" | |
| } | |
| ], | |
| "year": null, | |
| "venue": "", | |
| "volume": "", | |
| "issue": "", | |
| "pages": "", | |
| "other_ids": {}, | |
| "num": null, | |
| "urls": [], | |
| "raw_text": "S.-H. Liu, K.-Y. Chen, B. Chen, H.-M. Wang, H.-C. Yen and W.-L. Hsu, \"Combining relevance language modeling and clarity measure for extractive speech summarization,\"", | |
| "links": null | |
| }, | |
| "BIBREF4": { | |
| "ref_id": "b4", | |
| "title": "Speech, and Language Processing", | |
| "authors": [], | |
| "year": 2015, | |
| "venue": "", | |
| "volume": "23", | |
| "issue": "", | |
| "pages": "957--969", | |
| "other_ids": {}, | |
| "num": null, | |
| "urls": [], | |
| "raw_text": "IEEE/ACM Transactions on Audio, Speech, and Language Processing, Vol. 23, No. 6, pp. 957-969, 2015.", | |
| "links": null | |
| }, | |
| "BIBREF5": { | |
| "ref_id": "b5", | |
| "title": "Learning distributed representations of concepts", | |
| "authors": [ | |
| { | |
| "first": "G", | |
| "middle": [ | |
| "E" | |
| ], | |
| "last": "Hinton", | |
| "suffix": "" | |
| } | |
| ], | |
| "year": 1986, | |
| "venue": "Proc. the Cognitive Science Society", | |
| "volume": "", | |
| "issue": "", | |
| "pages": "1--12", | |
| "other_ids": {}, | |
| "num": null, | |
| "urls": [], | |
| "raw_text": "G. E. Hinton, \"Learning distributed representations of concepts\", in Proc. the Cognitive Science Society, pp. 1-12, 1986.", | |
| "links": null | |
| }, | |
| "BIBREF6": { | |
| "ref_id": "b6", | |
| "title": "A neural probabilistic language model", | |
| "authors": [ | |
| { | |
| "first": "Y", | |
| "middle": [], | |
| "last": "Bengio", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "R", | |
| "middle": [], | |
| "last": "Ducharme", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "P", | |
| "middle": [], | |
| "last": "Vincent", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "C", | |
| "middle": [], | |
| "last": "Jauvin", | |
| "suffix": "" | |
| } | |
| ], | |
| "year": 2003, | |
| "venue": "Journal of Machine Learning Research", | |
| "volume": "3", | |
| "issue": "", | |
| "pages": "1137--1155", | |
| "other_ids": {}, | |
| "num": null, | |
| "urls": [], | |
| "raw_text": "Y. Bengio, R. Ducharme, P. Vincent and C. Jauvin, \"A neural probabilistic language model,\" Journal of Machine Learning Research, Vol. 3, pp. 1137-1155, 2003.", | |
| "links": null | |
| }, | |
| "BIBREF7": { | |
| "ref_id": "b7", | |
| "title": "Efficient estimation of word representations in vector space", | |
| "authors": [ | |
| { | |
| "first": "T", | |
| "middle": [], | |
| "last": "Mikolov", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "K", | |
| "middle": [], | |
| "last": "Chen", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "G", | |
| "middle": [], | |
| "last": "Corrado", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "J", | |
| "middle": [], | |
| "last": "Dean", | |
| "suffix": "" | |
| } | |
| ], | |
| "year": 2013, | |
| "venue": "Proc. the International Conference on Learning Representations", | |
| "volume": "", | |
| "issue": "", | |
| "pages": "1--12", | |
| "other_ids": {}, | |
| "num": null, | |
| "urls": [], | |
| "raw_text": "T. Mikolov, K. Chen, G. Corrado and J. Dean, \"Efficient estimation of word representations in vector space,\" in Proc. the International Conference on Learning Representations, pp. 1-12, 2013.", | |
| "links": null | |
| }, | |
| "BIBREF8": { | |
| "ref_id": "b8", | |
| "title": "Distributed representations of words and phrases and their compositionality", | |
| "authors": [ | |
| { | |
| "first": "T", | |
| "middle": [], | |
| "last": "Mikolov", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "I", | |
| "middle": [], | |
| "last": "Sutskever", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "K", | |
| "middle": [], | |
| "last": "Chen", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "G", | |
| "middle": [], | |
| "last": "Corrado", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "J", | |
| "middle": [], | |
| "last": "Dean", | |
| "suffix": "" | |
| } | |
| ], | |
| "year": 2013, | |
| "venue": "Proc. the International Conference on Learning Representations", | |
| "volume": "", | |
| "issue": "", | |
| "pages": "1--9", | |
| "other_ids": {}, | |
| "num": null, | |
| "urls": [], | |
| "raw_text": "T. Mikolov, I. Sutskever, K. Chen, G. Corrado and J. Dean, \"Distributed representations of words and phrases and their compositionality,\" in Proc. the International Conference on Learning Representations, pp. 1-9, 2013.", | |
| "links": null | |
| }, | |
| "BIBREF9": { | |
| "ref_id": "b9", | |
| "title": "Distributed representations of sentences and documents", | |
| "authors": [ | |
| { | |
| "first": "Q", | |
| "middle": [ | |
| "V" | |
| ], | |
| "last": "Le", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "T", | |
| "middle": [], | |
| "last": "Mikolov", | |
| "suffix": "" | |
| } | |
| ], | |
| "year": 2014, | |
| "venue": "Proc. the International Conference on Machine Learning", | |
| "volume": "", | |
| "issue": "", | |
| "pages": "", | |
| "other_ids": {}, | |
| "num": null, | |
| "urls": [], | |
| "raw_text": "Q. V. Le and T. Mikolov, \"Distributed representations of sentences and documents,\" in Proc. the International Conference on Machine Learning, 2014.", | |
| "links": null | |
| }, | |
| "BIBREF10": { | |
| "ref_id": "b10", | |
| "title": "Leveraging Kullback-Leibler divergence measures and information-rich cues for speech summarization", | |
| "authors": [ | |
| { | |
| "first": "S.-H", | |
| "middle": [], | |
| "last": "Lin", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "Y.-M", | |
| "middle": [], | |
| "last": "Yeh", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "B", | |
| "middle": [], | |
| "last": "Chen", | |
| "suffix": "" | |
| } | |
| ], | |
| "year": 2011, | |
| "venue": "IEEE Transactions on Audio, Speech and Language Processing", | |
| "volume": "19", | |
| "issue": "4", | |
| "pages": "871--882", | |
| "other_ids": {}, | |
| "num": null, | |
| "urls": [], | |
| "raw_text": "S.-H. Lin, Y.-M. Yeh and B. Chen, \"Leveraging Kullback-Leibler divergence measures and information-rich cues for speech summarization,\" IEEE Transactions on Audio, Speech and Language Processing, Vol. 19, No. 4, pp. 871-882, 2011.", | |
| "links": null | |
| }, | |
| "BIBREF11": { | |
| "ref_id": "b11", | |
| "title": "Extractive speech summarization using evaluation metric-related training criteria", | |
| "authors": [ | |
| { | |
| "first": "B", | |
| "middle": [], | |
| "last": "Chen", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "S.-H", | |
| "middle": [], | |
| "last": "Lin", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "Y.-M", | |
| "middle": [], | |
| "last": "Chang", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "J.-W", | |
| "middle": [], | |
| "last": "Liu", | |
| "suffix": "" | |
| } | |
| ], | |
| "year": 2013, | |
| "venue": "Information Processing & Management", | |
| "volume": "49", | |
| "issue": "1", | |
| "pages": "1--12", | |
| "other_ids": {}, | |
| "num": null, | |
| "urls": [], | |
| "raw_text": "B. Chen, S.-H. Lin, Y.-M. Chang, J.-W. Liu, \"Extractive speech summarization using evaluation metric-related training criteria,\" Information Processing & Management, Vol. 49, No. 1, pp. 1-12, 2013.", | |
| "links": null | |
| }, | |
| "BIBREF12": { | |
| "ref_id": "b12", | |
| "title": "MATBN: A Mandarin Chinese broadcast news corpus", | |
| "authors": [ | |
| { | |
| "first": "H", | |
| "middle": [ | |
| "M" | |
| ], | |
| "last": "Wang", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "B", | |
| "middle": [], | |
| "last": "Chen", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "J", | |
| "middle": [ | |
| "W" | |
| ], | |
| "last": "Kuo", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "S", | |
| "middle": [ | |
| "S" | |
| ], | |
| "last": "Cheng", | |
| "suffix": "" | |
| } | |
| ], | |
| "year": 2005, | |
| "venue": "Journal of Computational Linguistics and Chinese Language Processing", | |
| "volume": "10", | |
| "issue": "2", | |
| "pages": "219--236", | |
| "other_ids": {}, | |
| "num": null, | |
| "urls": [], | |
| "raw_text": "H. M. Wang, B. Chen, J. W. Kuo, and S. S. Cheng, \"MATBN: A Mandarin Chinese broadcast news corpus,\" Journal of Computational Linguistics and Chinese Language Processing, Vol. 10, No. 2, pp. 219-236, 2005.", | |
| "links": null | |
| } | |
| }, | |
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| "text": "Learning)\u662f\u8fd1\u671f\u76f8\u7576\u71b1\u9580\u7684\u4e00\u500b\u7814\u7a76\u8b70\u984c[5-7]\uff0c \u591a\u6578\u7684\u7814\u7a76\u6210\u679c\u4e5f\u8b49\u660e\u4e86\u9019\u9805\u6280\u8853\u5728\u8a31\u591a\u81ea\u7136\u8a9e\u8a00\u8655\u7406(Natural Language Proceeding, NLP)\u7684\u76f8\u95dc\u4efb\u52d9\u4e0a\uff0c\u53ef\u4ee5\u9032\u4e00\u6b65\u5730\u7372\u5f97\u512a\u826f\u7684\u6210\u6548\u3002\u6709\u9451\u65bc\u6b64\uff0c\u672c\uf941\u6587\u9996\u5148\u63a2\u8a0e\u4f7f\u7528 \u4e0d\u540c\u7684\u8a5e\u8868\u793a\u6cd5(Word Representations)\u53ca\u8a9e\u53e5\u8868\u793a\u6cd5(Sentence Representations)\uff0c\u5305\u62ec\u4e86 \u9023\u7e8c\u578b\u8a5e\u888b\u6a21\u578b(Continuous Bag-of-Words, CBOW)\u3001\u8df3\u8e8d\u5f0f\u6a21\u578b(Skip-Gram, SG)\u3001\u5206\u6563 \u5f0f\u5132\u5b58\u6a21\u578b(Distributed Memory Model of Paragraph Vector, PV-DM)\u4ee5\u53ca\u5206\u6563\u5f0f\u8a5e\u888b\u6a21\u578b (Distributed Bag-of-Words of Paragraph Vector, PV-DBOW)[8, 9]\uff0c\u65bc\u7bc0\uf93f\u5f0f\u4e2d\u6587\u5ee3\u64ad\u65b0\u805e \u8a9e\u97f3\u6587\u4ef6\u6458\u8981\u4e4b\u61c9\u7528\u3002\u5176\u6b21\uff0c\u57fa\u65bc\u8a5e\u8868\u793a\u6cd5\u53ca\u8a9e\u53e5\u8868\u793a\u6cd5\uff0c\u672c\u8ad6\u6587\u63d0\u51fa\u4f7f\u7528\u4e09\u7a2e\u7c21\u55ae\u4e14 \u6709\u6548\u7684\u6392\u5e8f\u6a21\u578b(Ranking Models)\uff0c\u5305\u62ec\u4e86\u9918\u5f26\u76f8\u4f3c\u5ea6(Cosine Similarity)\u3001\u99ac\u53ef\u592b\u96a8\u6a5f\u6f2b \u6b65(Markov Random Walk, MRW)\u4ee5\u53ca\u6587\u4ef6\u76f8\u4f3c\u5ea6\u91cf\u503c(Document Likelihood Measure, DLM)[10]\uff0c\u4f86\u9078\u53d6\u91cd\u8981\u8a9e\u53e5\u4ee5\u5f62\u6210\u6458\u8981\u3002\u518d\u8005\uff0c\u9664\u4e86\u4f7f\u7528\u6587\u4ef6\u4e2d\u7684\u6587\u5b57\u8cc7\u8a0a\u5916\uff0c\u672c\u8ad6 \u6587\u66f4\u9032\u4e00\u6b65\u5730\u7d50\u5408\u8a9e\u97f3\u6587\u4ef6\u4e0a\u7684\u5404\u5f0f\u8072\u5b78\u7279\u5fb5\uff0c\u8af8\u5982\u97fb\u5f8b\u7279\u5fb5(Prosodic Features)\u7b49[11]\uff0c \u4ee5\u671f\u671b\u80fd\u7372\u5f97\u66f4\u597d\u7684\u6458\u8981\u6210\u6548\u3002\u5728\u5be6\u9a57\u8a2d\u5b9a\u4e0a\uff0c\u672c\u8ad6\u6587\u7684\u8a9e\u97f3\u6587\u4ef6\u6458\u8981\u5be6\u9a57\u8a9e\u6599\u662f\u63a1\u7528 \u516c\u8996\u5ee3\u64ad\u65b0\u805e(Mandarin Chinese Broadcast News Corpus, MATBN)[12]\uff1b\u4e00\u7cfb\u5217\u7684\u5be6\u9a57\u7d50 \u679c\u986f\u793a\uff0c\u4e0d\u8ad6\u662f\u5728\u4f7f\u7528\u542b\u6709\u932f\u8aa4\u8cc7\u8a0a\u7684\u8a9e\u97f3\u8fa8\u8b58\u8f49\u5beb(Speech Recognition Transcripts)\u6216 \u8005\u662f\u4f7f\u7528\u6b63\u78ba\u53c3\u8003\u8f49\u5beb(Reference Transcripts)\u7684\u60c5\u6cc1\u4e0b\uff0c\u76f8\u8f03\u65bc\u5176\u5b83\u73fe\u6709\u7684\u6458\u8981\u65b9\u6cd5\uff0c The 2015 Conference on Computational Linguistics and Speech Processing ROCLING 2015, pp. 1-3 \uf0d3 The Association for Computational Linguistics and Chinese Language Processing \u6211\u5011\u6240\u63d0\u51fa\u7684\u65b0\u7a4e\u5f0f\u6458\u8981\u65b9\u6cd5\u7684\u78ba\u90fd\u80fd\u5920\u7372\u5f97\u4f9b\u986f\u8457\u7684\u6458\u8981\u6548\u80fd\u589e\u9032\u3002 \u95dc\u9375\u5b57: \u8a9e\u97f3\u6587\u4ef6\u3001\u7bc0\u9304\u5f0f\u6458\u8981\u3001\u8a5e\u8868\u793a\u6cd5\u3001\u8a9e\u53e5\u8868\u793a\u6cd5\u3001\u97fb\u5f8b\u7279\u5fb5 \u81f4\u8b1d \u672c\u8ad6\u6587\u4e4b\u7814\u7a76\u627f\u8499\u6559\u80b2\u90e8-\u570b\u7acb\u81fa\u7063\u5e2b\u7bc4\u5927\u5b78\u9081\u5411\u9802\u5c16\u5927\u5b78\u8a08\u756b(104-2911-I-003-301)\u8207 \u884c \u653f \u9662 \u79d1 \u6280 \u90e8 \u7814 \u7a76 \u8a08 \u756b (MOST 104-2221-E-003-018-MY3, MOST 103-2221-E-003-016-MY2, NSC 101-2221-E-003-024-MY3)\u4e4b\u7d93\u8cbb\u652f\u6301\uff0c\u8b39\u6b64\u81f4\u8b1d\u3002 \u53c3\u8003\u6587\u737b", | |
| "num": null, | |
| "uris": null, | |
| "type_str": "figure" | |
| } | |
| } | |
| } | |
| } |