{"title":"什么是会议摘要?会议语料库人类摘录摘要分析","authors":"Fei Liu, Yang Liu","doi":"10.3115/1622064.1622079","DOIUrl":null,"url":null,"abstract":"Significant research efforts have been devoted to speech summarization, including automatic approaches and evaluation metrics. However, a fundamental problem about what summaries are for the speech data and whether humans agree with each other remains unclear. This paper performs an analysis of human annotated extractive summaries using the ICSI meeting corpus with an aim to examine their consistency and the factors impacting human agreement. In addition to using Kappa statistics and ROUGE scores, we also proposed a sentence distance score and divergence distance as a quantitative measure. This study is expected to help better define the speech summarization problem.","PeriodicalId":426429,"journal":{"name":"SIGDIAL Workshop","volume":"27 6","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"16","resultStr":"{\"title\":\"What Are Meeting Summaries? An Analysis of Human Extractive Summaries in Meeting Corpus\",\"authors\":\"Fei Liu, Yang Liu\",\"doi\":\"10.3115/1622064.1622079\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Significant research efforts have been devoted to speech summarization, including automatic approaches and evaluation metrics. However, a fundamental problem about what summaries are for the speech data and whether humans agree with each other remains unclear. This paper performs an analysis of human annotated extractive summaries using the ICSI meeting corpus with an aim to examine their consistency and the factors impacting human agreement. In addition to using Kappa statistics and ROUGE scores, we also proposed a sentence distance score and divergence distance as a quantitative measure. This study is expected to help better define the speech summarization problem.\",\"PeriodicalId\":426429,\"journal\":{\"name\":\"SIGDIAL Workshop\",\"volume\":\"27 6\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-06-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"16\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"SIGDIAL Workshop\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3115/1622064.1622079\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"SIGDIAL Workshop","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3115/1622064.1622079","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
What Are Meeting Summaries? An Analysis of Human Extractive Summaries in Meeting Corpus
Significant research efforts have been devoted to speech summarization, including automatic approaches and evaluation metrics. However, a fundamental problem about what summaries are for the speech data and whether humans agree with each other remains unclear. This paper performs an analysis of human annotated extractive summaries using the ICSI meeting corpus with an aim to examine their consistency and the factors impacting human agreement. In addition to using Kappa statistics and ROUGE scores, we also proposed a sentence distance score and divergence distance as a quantitative measure. This study is expected to help better define the speech summarization problem.