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Vocal Effort Based Speaking Style Conversion Using Vocoder Features and Parallel Learning.

, , , and . IEEE Access, (2019)

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Vocal Effort Based Speaking Style Conversion Using Vocoder Features and Parallel Learning., , , and . IEEE Access, (2019)Comparison of Syllabification Algorithms and Training Strategies for Robust Word Count Estimation across Different Languages and Recording Conditions., , and . INTERSPEECH, page 1200-1204. ISCA, (2018)Augmented CycleGANs for Continuous Scale Normal-to-Lombard Speaking Style Conversion., , , and . INTERSPEECH, page 2838-2842. ISCA, (2019)Automatic word count estimation from daylong child-centered recordings in various language environments using language-independent syllabification of speech., , , , , , , , , and 1 other author(s). Speech Commun., (2019)Dirichlet process mixture models for clustering i-vector data., , and . ICASSP, page 5470-5474. IEEE, (2017)SylNet: An Adaptable End-to-End Syllable Count Estimator for Speech., and . IEEE Signal Process. Lett., 26 (9): 1359-1363 (2019)Emphasis Control for Parallel Neural TTS., , , and . INTERSPEECH, page 3378-3382. ISCA, (2022)Speaking Style Conversion from Normal to Lombard Speech Using a Glottal Vocoder and Bayesian GMMs., , , , and . INTERSPEECH, page 1363-1367. ISCA, (2017)Comparison of Non-Parametric Bayesian Mixture Models for Syllable Clustering and Zero-Resource Speech Processing., , and . INTERSPEECH, page 2744-2748. ISCA, (2017)Cycle-consistent Adversarial Networks for Non-parallel Vocal Effort Based Speaking Style Conversion., , , , and . ICASSP, page 6835-6839. IEEE, (2019)