62 citations · 116 across the 14 of their papers we have counts for
14 papers
Multi-speaker Emotional Text-to-speech Synthesizer
Sungjae Cho, Soo-Young Lee
We present a methodology to train our multi-speaker emotional text-to-speech synthesizer that can express speech for 10 speakers' 7 different emotions. All silences from audio samp…
Unigram-Normalized Perplexity as a Language Model Performance Measure with Different Vocabulary Sizes
Jihyeon Roh, Sang-Hoon Oh, Soo-Young Lee
Although Perplexity is a widely used performance metric for language models, the values are highly dependent upon the number of words in the corpus and is useful to compare perform…
Hierarchical GPT with Congruent Transformers for Multi-Sentence Language Models
Jihyeon Roh, Huiseong Gim, Soo-Young Lee
We report a GPT-based multi-sentence language model for dialogue generation and document understanding. First, we propose a hierarchical GPT which consists of three blocks, i.e., a…
Semi-supervised Disentanglement with Independent Vector Variational Autoencoders
Bo-Kyeong Kim, Sungjin Park, Geonmin Kim +1
We aim to separate the generative factors of data into two latent vectors in a variational autoencoder. One vector captures class factors relevant to target classification tasks, w…
Emotional Voice Conversion using Multitask Learning with Text-to-speech
Tae-Ho Kim, Sungjae Cho, Shinkook Choi +2
Voice conversion (VC) is a task to transform a person's voice to different style while conserving linguistic contents. Previous state-of-the-art on VC is based on sequence-to-seque…
Adjusting Pleasure-Arousal-Dominance for Continuous Emotional Text-to-speech Synthesizer
Azam Rabiee, Tae-Ho Kim, Soo-Young Lee
Emotion is not limited to discrete categories of happy, sad, angry, fear, disgust, surprise, and so on. Instead, each emotion category is projected into a set of nearly independent…