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Ensemble Deep Neural Network Based Waveform-Driven Stress Model for Speech Synthesis.

, , , и . SPECOM, том 9811 из Lecture Notes in Computer Science, стр. 271-278. Springer, (2016)

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György Jákli

György Szikszay

György Iványi

György Irmey

György Csanády

 

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Summarization of Spontaneous Speech using Automatic Speech Recognition and a Speech Prosody based Tokenizer., , и . KDIR, стр. 221-227. SciTePress, (2016)Examination of Pronunciation Variation from Hand-Labelled Corpora., и . TSD, том 3206 из Lecture Notes in Computer Science, стр. 473-480. Springer, (2004)Using prosody to improve automatic speech recognition., и . Speech Commun., 52 (5): 413-426 (2010)Investigation on N-Gram Approximated RNNLMs for Recognition of Morphologically Rich Speech., , , и . SLSP, том 11816 из Lecture Notes in Computer Science, стр. 223-234. Springer, (2019)On the Effects of Automatic Transcription and Segmentation Errors in Hungarian Spoken Language Processing., , и . Period. Polytech. Electr. Eng. Comput. Sci., 63 (4): 254-262 (2019)Automatic Assessment Of Spoken English Proficiency Based on Multimodal and Multitask Transformers., и . RANLP, стр. 769-776. INCOMA Ltd., Shoumen, Bulgaria, (2023)Atom decomposition based stress detection and automatic phrasing of speech., , , и . CogInfoCom, стр. 25-30. IEEE, (2016)A szupraszegmentális jellemzők szerepe és felhasználása a gépi beszédfelismerésben. Budapest University of Technology and Economics, Hungary, (2009)Unsupervised Clustering of Prosodic Patterns in Spontaneous Speech., и . TSD, том 7499 из Lecture Notes in Computer Science, стр. 648-655. Springer, (2012)Joint Word- and Character-level Embedding CNN-RNN Models for Punctuation Restoration., и . CogInfoCom, стр. 135-140. IEEE, (2018)