21 citations · 36 across the 5 of their papers we have counts for
5 papers
Multimodal Sequential Generative Models for Semi-Supervised Language Instruction Following
Kei Akuzawa, Yusuke Iwasawa, Yutaka Matsuo
Agents that can follow language instructions are expected to be useful in a variety of situations such as navigation. However, training neural network-based agents requires numerou…
Conditional Deep Hierarchical Variational Autoencoder for Voice Conversion
Kei Akuzawa, Kotaro Onishi, Keisuke Takiguchi +2
Variational autoencoder-based voice conversion (VAE-VC) has the advantage of requiring only pairs of speeches and speaker labels for training. Unlike the majority of the research i…
Estimating Disentangled Belief about Hidden State and Hidden Task for Meta-RL
Kei Akuzawa, Yusuke Iwasawa, Yutaka Matsuo
There is considerable interest in designing meta-reinforcement learning (meta-RL) algorithms, which enable autonomous agents to adapt new tasks from small amount of experience. In…
Adversarial Invariant Feature Learning with Accuracy Constraint for Domain Generalization
Kei Akuzawa, Yusuke Iwasawa, Yutaka Matsuo
Learning domain-invariant representation is a dominant approach for domain generalization (DG), where we need to build a classifier that is robust toward domain shifts. However, pr…
Expressive Speech Synthesis via Modeling Expressions with Variational Autoencoder
Kei Akuzawa, Yusuke Iwasawa, Yutaka Matsuo
Recent advances in neural autoregressive models have improve the performance of speech synthesis (SS). However, as they lack the ability to model global characteristics of speech (…