Ryu Takeda
10 papers · 2016–2024 · 3 venues · across top CS/AI venues
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Achievements
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π Interdisciplinary Bridge Β· Silver πΊοΈ Taxonomy Completionist (28) π Conference Polyglot Β· Bronze π£ Hot Topic Early Bird π Academic Marathon Β· Sprint
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Renaissance Researcher
(5)
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Research topics
Machine Learning
(8)
Artificial Intelligence
(5)
Deep Learning
(4)
Speech & Audio
(4)
Learning Types
(4)
Natural Language Processing
(3)
Core AI
(3)
Optimization & Theory
(3)
Recognition
(3)
Application Areas
(2)
Computer Vision
(1)
Mathematics & Optimization
(1)
Analysis
(1)
Applications
(1)
Bayesian & Probabilistic
(1)
Keywords
acoustic model
(2)
unsupervised learning
(2)
sound source separation
(2)
contrastive learning
(1)
blind source separation
(1)
sentiment analysis
(1)
variational inference
(1)
speech processing
(1)
word segmentation
(1)
automatic speech recognition
(1)
deep learning
(1)
affective computing
(1)
pitman-yor process
(1)
stick-breaking process
(1)
probability distribution
(1)
data augmentation
(1)
posterior probability
(1)
online learning
(1)
latent variable model
(1)
model compression
(1)
Papers
Collecting Human-Agent Dialogue Dataset with Frontal Brain Signal toward Capturing Unexpressed Sentiment
COLING 2024
Meta-domain Adversarial Contrastive Learning for Alleviating Individual Bias in Self-sentiment Predictions
Interspeech 2023
Recursive Sound Source Separation with Deep Learning-based Beamforming for Unknown Number of Sources
Interspeech 2023
Empirical Sampling from Latent Utterance-wise Evidence Model for Missing Data ASR based on Neural Encoder-Decoder Model
Interspeech 2022
Training Data Generation with DOA-based Selecting and Remixing for Unsupervised Training of Deep Separation Models
Interspeech 2022
Age Estimation with Speech-Age Model for Heterogeneous Speech Datasets
Interspeech 2021
Frame-Wise Online Unsupervised Adaptation of DNN-HMM Acoustic Model from Perspective of Robust Adaptive Filtering
Interspeech 2020
Node Pruning Based on Entropy of Weights and Node Activity for Small-Footprint Acoustic Model Based on Deep Neural Networks
Interspeech 2017
Unsupervised Segmentation of Phoneme Sequences based on Pitman-Yor Semi-Markov Model using Phoneme Length Context
IJCNLP 2017
Bayesian Language Model based on Mixture of Segmental Contexts for Spontaneous Utterances with Unexpected Words
COLING 2016