Score Normalization Methods for Relevant Documents Selection for Blind Relevance Feedback in Speech Information Retrieval

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F15%3A43926462" target="_blank" >RIV/49777513:23520/15:43926462 - isvavai.cz</a>

Výsledek na webu

<a href="http://link.springer.com/chapter/10.1007%2F978-3-319-24033-6_36" target="_blank" >http://link.springer.com/chapter/10.1007%2F978-3-319-24033-6_36</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-319-24033-6_36" target="_blank" >10.1007/978-3-319-24033-6_36</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Score Normalization Methods for Relevant Documents Selection for Blind Relevance Feedback in Speech Information Retrieval

Popis výsledku v původním jazyce

This paper aims at the automatic selection of the relevant documents for the blind relevance feedback method in speech information retrieval. Usually the relevant documents are selected only by simply determining the first N documents to be relevant. On the contrary, the previous first experiments with the automatic selection of the relevant documents for the blind relevance feedback method has shown the possibilities of the dynamical selection of the relevant documents for each query depending on the content of the retrieved documents instead of just blindly defining the number of the relevant documents to be used in advance. In the first experiments, the World Model Normalization method was used. Based on the promising results, the experiments presented in this paper try to thoroughly examine the possibilities of the application of different score normalization techniques used in the speaker identification task, which was successfully used in the related task of multi-label classification for finding the “correct” topics of a newspaper article in the output of a generative classifier.

Název v anglickém jazyce

Score Normalization Methods for Relevant Documents Selection for Blind Relevance Feedback in Speech Information Retrieval

Popis výsledku anglicky

This paper aims at the automatic selection of the relevant documents for the blind relevance feedback method in speech information retrieval. Usually the relevant documents are selected only by simply determining the first N documents to be relevant. On the contrary, the previous first experiments with the automatic selection of the relevant documents for the blind relevance feedback method has shown the possibilities of the dynamical selection of the relevant documents for each query depending on the content of the retrieved documents instead of just blindly defining the number of the relevant documents to be used in advance. In the first experiments, the World Model Normalization method was used. Based on the promising results, the experiments presented in this paper try to thoroughly examine the possibilities of the application of different score normalization techniques used in the speaker identification task, which was successfully used in the related task of multi-label classification for finding the “correct” topics of a newspaper article in the output of a generative classifier.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

20205 - Automation and control systems

Projekt

<a href="/cs/project/LM2010013" target="_blank" >LM2010013: LINDAT-CLARIN: Institut pro analýzu, zpracování a distribuci lingvistických dat</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2015

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Text, Speech, and Dialogue, 18th International Conference, TSD 2015, Pilsen, Czech Republic, 14-17, 2015. Proceedings

ISBN

978-3-319-24032-9

ISSN

0302-9743

e-ISSN

—

Počet stran výsledku

9

Strana od-do

316-324

Název nakladatele

Springer

Místo vydání

Berlin

Místo konání akce

Pilsen, Czech Republic

Datum konání akce

14. 9. 2015

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000365947800036