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Analyzing the Predictability of Lexeme-specific Prosodic Features as a Cue to Sentence Prominence.

, и . CogSci, cognitivesciencesociety.org, (2015)

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Sofoklis Sotiriou

 

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Predicting Prosodic Prominence from Text with Pre-trained Contextualized Word Representations., , , , , и . NODALIDA, стр. 281-290. Linköping University Electronic Press, (2019)Statistical Unpredictability of F0 Trajectories as a Cue to Sentence Stress., и . CogSci, cognitivesciencesociety.org, (2014)Prosodic Representations of Prominence Classification Neural Networks and Autoencoders Using Bottleneck Features., , , и . INTERSPEECH, стр. 1946-1950. ISCA, (2019)Attention based temporal filtering of sensory signals for data redundancy reduction., , и . ICASSP, стр. 3188-3192. IEEE, (2013)Perception of sentence stress in English infant directed speech., и . INTERSPEECH, стр. 1821-1825. ISCA, (2014)Speech-Based Emotion Recognition with Self-Supervised Models Using Attentive Channel-Wise Correlations and Label Smoothing., , , и . ICASSP, стр. 1-5. IEEE, (2023)Evaluation of Spectral Tilt Measures for Sentence Prominence Under Different Noise Conditions., , и . INTERSPEECH, стр. 3211-3215. ISCA, (2017)Automatic detection of sentence prominence in speech using predictability of word-level acoustic features., и . INTERSPEECH, стр. 568-572. ISCA, (2015)Does the Importance of Word-Initial and Word-Final Information Differ in Native versus Non-Native Spoken-Word Recognition?, , , и . INTERSPEECH, стр. 858-862. ISCA, (2016)Extracting Speaker and Emotion Information from Self-Supervised Speech Models via Channel-Wise Correlations., , , , , и . SLT, стр. 1136-1143. IEEE, (2022)