Lexicon-based vs. Lexicon-free ASR for Norwegian Parliament Speech Transcription
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F46747885%3A24220%2F22%3A00009900" target="_blank" >RIV/46747885:24220/22:00009900 - isvavai.cz</a>
Result on the web
<a href="https://link.springer.com/chapter/10.1007/978-3-031-16270-1_33" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-031-16270-1_33</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-031-16270-1_33" target="_blank" >10.1007/978-3-031-16270-1_33</a>
Alternative languages
Result language
angličtina
Original language name
Lexicon-based vs. Lexicon-free ASR for Norwegian Parliament Speech Transcription
Original language description
Norwegian is a challenging language for automatic speech recognition research because it has two written standards (Bokmal and Nynorsk) and a large number of distinct dialects, from which none has status of an official spoken norm. A traditional lexicon-based approach to ASR leads to a huge lexicon (because of the two standards and also due to compound words) with many spelling and pronunciation variants, and consequently to a large (and sparse) language model (LM). We have built a system with 601k-word lexicon and an acoustic model (AM) based on several types of neural networks and compare its performance with a lexicon-free end-to-end system developed in the ESPnet framework. For evaluation we use a publically available dataset of Norwegian parliament speeches that offers 100 h for training and 12 h for testing. In spite of this rather limited training resource, the lexicon-free approach yields significantly better results (13.0% word-error rate) compared to the best system with the lexicon, LM and neural network AM (that achieved 22.5% WER).
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/TO01000027" target="_blank" >TO01000027: NORDTRANS - Technology for automatic speech transcription in selected Nordic languages</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Lecture Notes in Computer Science
ISBN
978-303116269-5
ISSN
0302-9743
e-ISSN
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Number of pages
9
Pages from-to
401-409
Publisher name
SPRINGER-VERLAG BERLIN
Place of publication
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Event location
Brno
Event date
Jan 1, 2022
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000866222300033