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YUSUF, B. ČERNOCKÝ, J. SARAÇLAR, M.
Original Title
End-to-End Open Vocabulary Keyword Search With Multilingual Neural Representations
Type
journal article in Web of Science
Language
English
Original Abstract
Conventional keyword search systems operate on automatic speech recognition (ASR) outputs, which causes them to have a complex indexing and search pipeline. This has led to interest in ASR-free approaches to simplify the search procedure. We recently proposed a neural ASR-free keyword search model which achieves competitive performance while maintaining an efficient and simplified pipeline, where queries and documents are encoded with a pair of recurrent neural network encoders and the encodings are combined with a dot-product. In this article, we extend this work with multilingual pretraining and detailed analysis of the model. Our experiments show that the proposed multilingual training significantly improves the model performance and that despite not matching a strong ASR-based conventional keyword search system for short queries and queries comprising in-vocabulary words, the proposed model outperforms the ASR-based system for long queries and queries that do not appear in the training data.
Keywords
Keyword search, spoken term detection, end-to-end keyword search, asr-free keyword search, keyword spotting.
Authors
YUSUF, B.; ČERNOCKÝ, J.; SARAÇLAR, M.
Released
2. 8. 2023
Publisher
IEEE
Location
PISCATAWAY, NJ
ISBN
2329-9290
Periodical
IEEE/ACM TRANSACTIONS ON AUDIO, SPEECH AND LANGUAGE PROCESSING
Year of study
31
Number
08
State
United States of America
Pages from
3070
Pages to
3080
Pages count
11
URL
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10201906
BibTex
@article{BUT185202, author="YUSUF, B. and ČERNOCKÝ, J. and SARAÇLAR, M.", title="End-to-End Open Vocabulary Keyword Search With Multilingual Neural Representations", journal="IEEE/ACM TRANSACTIONS ON AUDIO, SPEECH AND LANGUAGE PROCESSING", year="2023", volume="31", number="08", pages="3070--3080", doi="10.1109/TASLP.2023.3301239", issn="2329-9290", url="https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10201906" }