Search Results for author: Ryo Ozaki

Found 3 papers, 2 papers with code

Unsupervised Multimodal Word Discovery based on Double Articulation Analysis with Co-occurrence cues

1 code implementation18 Jan 2022 Akira Taniguchi, Hiroaki Murakami, Ryo Ozaki, Tadahiro Taniguchi

The proposed method can acquire words and phonemes from speech signals using unsupervised learning and utilize object information based on multiple modalities-vision, tactile, and auditory-simultaneously.

StarGAN-based Emotional Voice Conversion for Japanese Phrases

no code implementations5 Apr 2021 Asuka Moritani, Ryo Ozaki, Shoki Sakamoto, Hirokazu Kameoka, Tadahiro Taniguchi

Through subjective evaluation experiments, we evaluated the performance of our StarGAN-EVC system in terms of its ability to achieve EVC for Japanese phrases.

Voice Conversion

Double Articulation Analyzer with Prosody for Unsupervised Word and Phoneme Discovery

1 code implementation15 Mar 2021 Yasuaki Okuda, Ryo Ozaki, Tadahiro Taniguchi

The main contributions of this study are as follows: 1) We develop a probabilistic generative model for time series data including prosody that potentially has a double articulation structure; 2) We propose the Prosodic DAA by deriving the inference procedure for Prosodic HDP-HLM and show that Prosodic DAA can discover words directly from continuous human speech signals using statistical information and prosodic information in an unsupervised manner; 3) We show that prosodic cues contribute to word segmentation more in naturally distributed case words, i. e., they follow Zipf's law.

Language Modelling Time Series +1

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