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Title:Context-dependent factored language models
Authors:ID Donaj, Gregor (Author)
ID Kačič, Zdravko (Author)
Files:.pdf EURASIP_Journal_on_Audio,_Speech,_and_Music_Processing_2017_Donaj,_Kacic_Context-dependent_factored_language_models.pdf (1,17 MB)
MD5: 9BFE3D3D19A9B226FC07011D79E111C4
 
URL http://asmp.eurasipjournals.springeropen.com/articles/10.1186/s13636-017-0104-6
 
Language:English
Work type:Scientific work
Typology:1.01 - Original Scientific Article
Organization:FERI - Faculty of Electrical Engineering and Computer Science
Abstract:The incorporation of grammatical information into speech recognition systems is often used to increase performance in morphologically rich languages. However, this introduces demands for sufficiently large training corpora and proper methods of using the additional information. In this paper, we present a method for building factored language models that use data obtained by morphosyntactic tagging. The models use only relevant factors that help to increase performance and ignore data from other factors, thus also reducing the need for large morphosyntactically tagged training corpora. Which data is relevant is determined at run-time, based on the current text segment being estimated, i.e., the context. We show that using a context-dependent model in a two-pass recognition algorithm, the overall speech recognition accuracy in a Broadcast News application improved by 1.73% relatively, while simpler models using the same data achieved only 0.07% improvement. We also present a more detailed error analysis based on lexical features, comparing first-pass and second-pass results.
Keywords:speech recognition, factored language model, dynamic backoff path, word context, inflectional language, morphosyntactic tags
Publication status:Published
Publication version:Version of Record
Year of publishing:2017
Number of pages:str. 1-16
Numbering:Letn. 2017
PID:20.500.12556/DKUM-66442 New window
ISSN:1687-4722
UDC:004.934
ISSN on article:1687-4722
COBISS.SI-ID:20330774 New window
DOI:10.1186/s13636-017-0104-6 New window
NUK URN:URN:SI:UM:DK:CKPFRA1L
Publication date in DKUM:26.06.2017
Views:1829
Downloads:379
Metadata:XML DC-XML DC-RDF
Categories:Misc.
:
DONAJ, Gregor and KAČIČ, Zdravko, 2017, Context-dependent factored language models. EURASIP Journal on Audio, Speech and Music Processing [online]. 2017. Vol. 2017, p. 1–16. [Accessed 31 March 2025]. DOI 10.1186/s13636-017-0104-6. Retrieved from: https://dk.um.si/IzpisGradiva.php?lang=eng&id=66442
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Record is a part of a journal

Title:EURASIP Journal on Audio, Speech and Music Processing
Shortened title:EURASIP J. Audio, Speech Music. Process.
Publisher:Springer
ISSN:1687-4722
COBISS.SI-ID:17964566 New window

Licences

License:CC BY 4.0, Creative Commons Attribution 4.0 International
Link:http://creativecommons.org/licenses/by/4.0/
Description:This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.
Licensing start date:26.06.2017

Secondary language

Language:Slovenian
Keywords:govorne tehnologije, razpoznavanje govora, avtomatsko razpoznavanje govora


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