{"title":"主题分割的声学指标","authors":"Julia Hirschberg, C. H. Nakatani","doi":"10.21437/ICSLP.1998-582","DOIUrl":null,"url":null,"abstract":"The segmentation of text and speech into topics and subtopics is an important step in document interpretation. For text, formatting information, such as headings and paragraphing, is available to aid in this endeavor, although this information is by no means su cient. For speech, the task is even more di cult. We present results of the application of machine learning techniques to the automatic identi cation of intonational phrases beginning and ending 'topics' determined independently by annotators for two corpora | the Boston Directions Corpus and the Broadcast News (HUB-4) DARPA/NIST database.","PeriodicalId":117113,"journal":{"name":"5th International Conference on Spoken Language Processing (ICSLP 1998)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1998-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"88","resultStr":"{\"title\":\"Acoustic indicators of topic segmentation\",\"authors\":\"Julia Hirschberg, C. H. Nakatani\",\"doi\":\"10.21437/ICSLP.1998-582\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The segmentation of text and speech into topics and subtopics is an important step in document interpretation. For text, formatting information, such as headings and paragraphing, is available to aid in this endeavor, although this information is by no means su cient. For speech, the task is even more di cult. We present results of the application of machine learning techniques to the automatic identi cation of intonational phrases beginning and ending 'topics' determined independently by annotators for two corpora | the Boston Directions Corpus and the Broadcast News (HUB-4) DARPA/NIST database.\",\"PeriodicalId\":117113,\"journal\":{\"name\":\"5th International Conference on Spoken Language Processing (ICSLP 1998)\",\"volume\":\"32 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1998-11-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"88\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"5th International Conference on Spoken Language Processing (ICSLP 1998)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.21437/ICSLP.1998-582\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"5th International Conference on Spoken Language Processing (ICSLP 1998)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.21437/ICSLP.1998-582","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The segmentation of text and speech into topics and subtopics is an important step in document interpretation. For text, formatting information, such as headings and paragraphing, is available to aid in this endeavor, although this information is by no means su cient. For speech, the task is even more di cult. We present results of the application of machine learning techniques to the automatic identi cation of intonational phrases beginning and ending 'topics' determined independently by annotators for two corpora | the Boston Directions Corpus and the Broadcast News (HUB-4) DARPA/NIST database.
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