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Entropy-based pruning of hidden units to reduce DNN parameters., и . SLT, стр. 672-679. IEEE, (2016)The Blizzard Challenge 2013 - Indian Language Task., , , , , , , , , и . Blizzard Challenge, ISCA, (2013)Joint acoustic factor learning for robust deep neural network based automatic speech recognition., , , , , и . ICASSP, стр. 5025-5029. IEEE, (2016)Adaptation of Deep Neural Network Acoustic Models for Robust Automatic Speech Recognition., , , , , и . New Era for Robust Speech Recognition, Exploiting Deep Learning, Springer, (2017)Bandwidth Embeddings for Mixed-Bandwidth Speech Recognition., , , и . INTERSPEECH, стр. 3203-3207. ISCA, (2019)Speed improvements to Information Retrieval-based dynamic time warping using hierarchical K-Means clustering., и . ICASSP, стр. 8515-8519. IEEE, (2013)IIIT-H System for MediaEval 2014 QUESST., , и . MediaEval, том 1263 из CEUR Workshop Proceedings, CEUR-WS.org, (2014)Unsupervised query-by-example spoken term detection using bag of acoustic words and non-segmental dynamic time warping., , , , и . INTERSPEECH, стр. 1742-1746. ISCA, (2014)Corpus Synthesis for Zero-Shot ASR Domain Adaptation Using Large Language Models., , , , , , , и . ICASSP, стр. 12326-12330. IEEE, (2024)Use of articulatory bottle-neck features for query-by-example spoken term detection in low resource scenarios., и . ICASSP, стр. 7128-7132. IEEE, (2014)