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Intensive acoustic models constructed by integrating low-occurrence models for spoken term detection.

, , , , , , , and . INTERSPEECH, page 25-28. ISCA, (2013)

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High priority in highly ranked documents in spoken term detection., , , , , and . APSIPA, page 1-4. IEEE, (2013)A bimodal Korean address entry/retrieval system., , and . ICSLP, ISCA, (1998)Ensemble of Domain Adversarial Neural Networks for Speech Emotion Recognition.. ASRU, page 374-379. IEEE, (2021)Multiple Deep Learning Models and Architectures with Different Numbers of States Used to Improve Retrieval Accuracy of Query-by-Example., , , , and . APSIPA ASC, page 1067-1071. IEEE, (2021)An integration method of retrieval results using plural subword models for vocabulary-free spoken document retrieval., , , , , and . INTERSPEECH, page 2389-2392. ISCA, (2007)Spoken Term Detection Results Using Plural Subword Models by Estimating Detection Performance for Each Query., , , , and . INTERSPEECH, page 2117-2120. ISCA, (2011)Open vocabulary spoken document retrieval by subword sequence obtained from speech recognizer., , , , , and . SLT, page 301-304. IEEE, (2008)Rescoring by a deep neural network for spoken term detection., , , , and . APSIPA, page 1207-1211. IEEE, (2015)Automatic Music Boundary Detection Using Short Segmental Acoustic Similarity in a Music Piece., , , , , and . EURASIP J. Audio, Speech and Music Processing, (2008)The Generalization Effect for Multilingual Speech Emotion Recognition across Heterogeneous Languages.. ICASSP, page 5881-5885. IEEE, (2019)