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TTS-by-TTS 2: Data-Selective Augmentation for Neural Speech Synthesis Using Ranking Support Vector Machine with Variational Autoencoder.

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Technology convergence in the Internet of Things (IoT) startup ecosystem: A network analysis., , and . Telematics Informatics, 35 (7): 1887-1899 (2018)Innovation patterns of big data technology in large companies and start-ups: an empirical analysis., , and . Technol. Anal. Strateg. Manag., 33 (9): 1052-1067 (2021)Neural Text-to-Speech with a Modeling-by-Generation Excitation Vocoder., , , , , and . INTERSPEECH, page 3570-3574. ISCA, (2020)Effective Data Augmentation Methods for Neural Text-to-Speech Systems., , , , and . ICEIC, page 1-4. IEEE, (2022)An Effective Style Token Weight Control Technique for End-to-End Emotional Speech Synthesis., , , and . IEEE Signal Process. Lett., 26 (9): 1383-1387 (2019)TTS-by-TTS 2: Data-Selective Augmentation for Neural Speech Synthesis Using Ranking Support Vector Machine with Variational Autoencoder., , , , , , , , and . INTERSPEECH, page 1941-1945. ISCA, (2022)Effective parameter estimation methods for an ExcitNet model in generative text-to-speech systems., , , and . CoRR, (2019)Unified Speech-Text Pretraining for Spoken Dialog Modeling., , , , , , , , , and . CoRR, (2024)Language Model-Based Emotion Prediction Methods for Emotional Speech Synthesis Systems., , , , , , and . INTERSPEECH, page 4596-4600. ISCA, (2022)Improved Parallel Wavegan Vocoder with Perceptually Weighted Spectrogram Loss., , , , , and . SLT, page 470-476. IEEE, (2021)