Results 131 to 140 of about 288,136 (202)

Modified Checklist for Autism in Toddlers in a Neonatal High-Risk Population.

JAMA Netw Open
Lassebro B, Morin M, Yin W, Sandin S, Ådén U.   +4 more
europepmc   +1 more source

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Multilingual spoken term detection: a review

International Journal of Speech Technology, 2020
In modern multilingual societies, there is a demand for multilingual Automatic Speech Recognition (ASR) and Spoken Term Detection (STD). Multilingual Spoken Term Detection refers to the process of retrieving appropriate audio files from a vast multilingual database using audio queries.
G. Deekshitha, L. Mary
semanticscholar   +4 more sources

Introducing Self-Supervised Learning Models for Spoken Query-Spoken Term Detection

2025 Asia Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)
This study was undertaken to improve the performance of Spoken Query Spoken Term Detection (SQ-STD) by introducing Self-Supervised Learning (SSL) models.
Masato Nagase, K. Kojima, Shi-wook Lee, Y. Itoh   +3 more
semanticscholar   +2 more sources

Query-by-Example Spoken Term Detection for Zero-Resource Languages Using Heuristic Search

ACM Transactions on Asian and Low-Resource Language Information Processing, 2023
Query-by-Example spoken content retrieval is a demanding and challenging task when a large volume of spoken content is piled up in the repositories without annotation.
Sudhakar P, S. K., Pabitra Mitra
semanticscholar   +1 more source

Self-Paced Pattern Augmentation for Spoken Term Detection in Zero-Resource

Interspeech, 2023
The spoken term detection task is challenging when a large volume of spoken content is generated without annotation. The pattern discovery approach aims to overcome the challenges by capturing the pattern similarities directly from the representation of ...
Sudhakar P, Sreenivasa Rao, Pabitra Mitra   +2 more
semanticscholar   +1 more source

Fast QBE: Towards Real-Time Spoken Term Detection with Separable Model

2022 International Conference on Machine Learning and Intelligent Systems Engineering (MLISE), 2022
State-of-the-art spoken term detection or query-by-example networks depend on recurrent neural network (RNN), which extract fixed-dimensional vectors (embedded vectors) from both spoken query and the search content, and then calculate cosine distances ...
Ziwei Tian, Shiqing Yang, Minqiang Xu
semanticscholar   +1 more source

Frame-Level Matching Scheme Using Posteriorgram Probability Distance of Spoken Data to Improve Search Accuracy of Spoken Term Detection

Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, 2022
Active research has been conducted of Spoken Term Detection (STD), which uses text queries (search words) to seek specific scenes in large amounts of data, including audio data. In subword-to-subword and state-to-state matching using results of automatic
Reo Minakawa, K. Kojima, Shi-wook Lee, Y. Itoh   +3 more
semanticscholar   +1 more source

Vocabulary independent spoken term detection

Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval, 2007
We are interested in retrieving information from speech data like broadcast news, telephone conversations and roundtable meetings. Today, most systems use large vocabulary continuous speech recognition tools to produce word transcripts; the transcripts are indexed and query terms are retrieved from the index.
Jonathan Mamou, Bhuvana Ramabhadran, Olivier Siohan   +2 more
openaire   +1 more source