The Impact of Inaccurate Phonetic Annotations on Speech Recognition Performance

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F46747885%3A24220%2F17%3A00004818" target="_blank" >RIV/46747885:24220/17:00004818 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/978-3-319-64206-2_45" target="_blank" >http://dx.doi.org/10.1007/978-3-319-64206-2_45</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-319-64206-2_45" target="_blank" >10.1007/978-3-319-64206-2_45</a>

Result language
angličtina
Original language name
The Impact of Inaccurate Phonetic Annotations on Speech Recognition Performance
Original language description
This paper focuses on impact of phonetic inaccuracies of acoustic training data on performance of automatic speech recognition system. This is especially important if the training data is created in automated way. In this case, the data often contains errors in a form of wrong phonetic transcriptions. A series of experiments simulating various common errors in phonetic transcriptions based on parts of GlobalPhone data set (for Croatian, Czech and Russian) is conducted. These experiments show the influence of various errors on different languages and acoustic models (Gaussian mixture models, deep neural networks). The impact of errors is also shown for real data obtained by our automated ASR creation process for Belarusian. The results show that the best performance is achieved by using the most accurate data; however, certain amount of errors (up to 5%) does have relatively small impact on speech recognition accuracy
Czech name
—
Czech description
—

Project
<a href="/en/project/TA04010199" target="_blank" >TA04010199: MULTILINMEDIA - Multilingual Multimedia Monitoring and Analyzing Platform</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year
2017
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISBN
9783319642055
ISSN
0302-9743
e-ISSN
—
Number of pages
9
Pages from-to
402-410
Publisher name
Springer Verlag
Place of publication
Německo
Event location
Praha, Česká Republika
Event date
Jan 1, 2017
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
—

Similar results(10)