Transformer-Based Encoder-Encoder Architecture for Spoken Term Detection
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F23%3A43969820" target="_blank" >RIV/49777513:23520/23:43969820 - isvavai.cz</a>
Result on the web
<a href="https://link.springer.com/chapter/10.1007/978-3-031-47665-5_28" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-031-47665-5_28</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-031-47665-5_28" target="_blank" >10.1007/978-3-031-47665-5_28</a>
Alternative languages
Result language
angličtina
Original language name
Transformer-Based Encoder-Encoder Architecture for Spoken Term Detection
Original language description
The paper presents a method for spoken term detection based on the Transformer architecture. We propose the encoder-encoder architecture employing two BERT-like encoders with additional modifications, including attention masking, convolutional and upsampling layers. The encoders project a recognized hypothesis and a searched term into a shared embedding space, where the score of the putative hit is computed using the calibrated dot product. In the experiments, we used the Wav2Vec 2.0 speech recognizer. The proposed system outperformed a baseline method based on deep LSTMs on the English and Czech STD datasets based on USC Shoah Foundation Visual History Archive (MALACH).
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
20205 - Automation and control systems
Result continuities
Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Pattern Recognition, 7th Asian Conference, ACPR 2023 Kitakyushu, Japan, November 5–8, 2023 Proceedings, Part III
ISBN
978-3-031-47664-8
ISSN
0302-9743
e-ISSN
1611-3349
Number of pages
12
Pages from-to
346-357
Publisher name
Springer
Place of publication
Heidelberg
Event location
Kitakyushu, Japan
Event date
Nov 5, 2023
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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