Named entity recognition from spontaneous open-domain speech

Mihai Surdeanu; Jordi Turmo; Eli Comelles

Named entity recognition from spontaneous open-domain speech

Mihai Surdeanu, Jordi Turmo, Eli Comelles

Research output: Contribution to conference › Paper › peer-review

Abstract

This paper presents an analysis of named entity recognition and classification in spontaneous speech transcripts. We annotated a significant fraction of the Switchboard corpus with six named entity classes and investigated a battery of machine learning models that include lexical, syntactic, and semantic attributes. The best recognition and classification model obtains promising results, approaching within 5% a system evaluated on clean textual data.

Original language	English (US)
Pages	3433-3436
Number of pages	4
State	Published - Dec 1 2005
Externally published	Yes
Event	9th European Conference on Speech Communication and Technology - Lisbon, Portugal Duration: Sep 4 2005 → Sep 8 2005

Other

Other	9th European Conference on Speech Communication and Technology
Country	Portugal
City	Lisbon
Period	9/4/05 → 9/8/05

ASJC Scopus subject areas

Engineering(all)

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title = "Named entity recognition from spontaneous open-domain speech",

abstract = "This paper presents an analysis of named entity recognition and classification in spontaneous speech transcripts. We annotated a significant fraction of the Switchboard corpus with six named entity classes and investigated a battery of machine learning models that include lexical, syntactic, and semantic attributes. The best recognition and classification model obtains promising results, approaching within 5% a system evaluated on clean textual data.",

author = "Mihai Surdeanu and Jordi Turmo and Eli Comelles",

year = "2005",

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language = "English (US)",

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AU - Turmo, Jordi

AU - Comelles, Eli

PY - 2005/12/1

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N2 - This paper presents an analysis of named entity recognition and classification in spontaneous speech transcripts. We annotated a significant fraction of the Switchboard corpus with six named entity classes and investigated a battery of machine learning models that include lexical, syntactic, and semantic attributes. The best recognition and classification model obtains promising results, approaching within 5% a system evaluated on clean textual data.

AB - This paper presents an analysis of named entity recognition and classification in spontaneous speech transcripts. We annotated a significant fraction of the Switchboard corpus with six named entity classes and investigated a battery of machine learning models that include lexical, syntactic, and semantic attributes. The best recognition and classification model obtains promising results, approaching within 5% a system evaluated on clean textual data.

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M3 - Paper

AN - SCOPUS:33745191401

SP - 3433

EP - 3436

T2 - 9th European Conference on Speech Communication and Technology

Y2 - 4 September 2005 through 8 September 2005

ER -

Named entity recognition from spontaneous open-domain speech

Abstract

Other

ASJC Scopus subject areas

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