SSCS '10 Pub Date : 2010-10-29 DOI: 10.1145/1878101.1878111

Andrei Popescu-Belis, J. Kilgour, Alexandre Nanchen, P. Poller

引用次数: 2

Automatic indexing of speech segments with spontaneity levels on large audio database 大型音频数据库中具有自发性水平的语音片段自动索引

SSCS '10 Pub Date : 2010-10-29 DOI: 10.1145/1878101.1878110

Richard Dufour, Y. Estève, P. Deléglise

{"title":"Automatic indexing of speech segments with spontaneity levels on large audio database","authors":"Richard Dufour, Y. Estève, P. Deléglise","doi":"10.1145/1878101.1878110","DOIUrl":"https://doi.org/10.1145/1878101.1878110","url":null,"abstract":"Spontaneous speech detection from a large audio database can be useful for different applications. For example, processing spontaneous speech is one of the many challenges that Automatic Speech Recognition (ASR) systems have to deal with. Spontaneous speech detection can also be an informative descriptor for information retrieval.\u0000 The main evidences characterizing spontaneous speech are disfluencies (filled pause, repetition, repair and false start) and many studies have focused on the detection and the correction of these disfluencies. In this study1 we define spontaneous speech as unprepared speech, in opposition to prepared speech where utterances contain well-formed sentences close to those that can be found in written documents. Disfluencies are of course very good indicators of unprepared speech, however they are not the only ones: ungrammaticality and language register are also important as well as prosodic patterns. This paper proposes a set of acoustic and linguistic features that can be used for characterizing and detecting spontaneous speech segments from large audio databases, and proposes a method to extract and to exploit these features in order to index audio documents with three speech spontaneity levels.","PeriodicalId":123226,"journal":{"name":"SSCS '10","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129477090","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Towards methods for efficient access to spoken content in the ami corpus 探讨如何有效地访问ami语料库中的口语内容

SSCS '10 Pub Date : 2010-10-29 DOI: 10.1145/1878101.1878108

G. Jones, Maria Eskevich, Ágnes Gyarmati

{"title":"Towards methods for efficient access to spoken content in the ami corpus","authors":"G. Jones, Maria Eskevich, Ágnes Gyarmati","doi":"10.1145/1878101.1878108","DOIUrl":"https://doi.org/10.1145/1878101.1878108","url":null,"abstract":"Increasing amounts of informal spoken content are being collected. This material does not have clearly defined document forms either in terms of structure or topical content, e.g. recordings of meetings, lectures and personal data sources. Automated search of this content poses challenges beyond retrieval of defined documents, including definition of search items and location of relevant content within them. While most existing work on speech search focused on clearly defined document units, in this paper we describe our initial investigation into search of meeting content using the AMI meeting collection. Manual and automated transcripts of meetings are first automatically segmented into topical units. A known-item search task is then performed using presentation slides from the meetings as search queries to locate relevant sections of the meetings. Query slides were selected corresponding to well recognised and poorly recognised spoken content, and randomly selected slides. Experimental results show that relevant items can be located with reasonable accuracy using a standard information retrieval approach, and that there is a clear relationship between automatic transcription accuracy and retrieval effectiveness.","PeriodicalId":123226,"journal":{"name":"SSCS '10","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132191039","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

World wide telecom web search: invited talk abstract 全球电信网搜索:特邀谈话摘要

SSCS '10 Pub Date : 2010-10-29 DOI: 10.1145/1878101.1878103

Nitendra Rajput

引用次数: 0

Large multimedia archive for world languages 世界语言的大型多媒体档案

SSCS '10 Pub Date : 2010-10-29 DOI: 10.1145/1878101.1878113

P. Wittenburg, Paul Trilsbeek, Przemek Lenkiewicz

引用次数: 4

Novel methods for query selection and query combination in query-by-example spoken term detection 基于实例查询的语音词检测中查询选择和查询组合的新方法

SSCS '10 Pub Date : 2010-10-29 DOI: 10.1145/1878101.1878106

Javier Tejedor, Igor Szöke, M. Fapšo