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Found 12 papers, 6 papers with code
Multi-speaker Emotional Text-to-speech Synthesizer
We present a methodology to train our multi-speaker emotional text-to-speech synthesizer that can express speech for 10 speakers' 7 different emotions.
Unigram-Normalized Perplexity as a Language Model Performance Measure with Different Vocabulary Sizes
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 performance of the same corpus only.
Hierarchical GPT with Congruent Transformers for Multi-Sentence Language Models
First, we propose a hierarchical GPT which consists of three blocks, i. e., a sentence encoding block, a sentence generating block, and a sentence decoding block.
Semi-supervised Disentanglement with Independent Vector Variational Autoencoders
We aim to separate the generative factors of data into two latent vectors in a variational autoencoder.
Emotional Voice Conversion using Multitask Learning with Text-to-speech
The embedding space of seq2seq-based TTS has abundant information on the text.
Unpaired Speech Enhancement by Acoustic and Adversarial Supervision for Speech Recognition
Many speech enhancement methods try to learn the relationship between noisy and clean speech, obtained using an acoustic room simulator.
A Fully Time-domain Neural Model for Subband-based Speech Synthesizer
This paper introduces a deep neural network model for subband-based speech synthesizer.
End-to-end Multimodal Emotion and Gender Recognition with Dynamic Joint Loss Weights
In our experiments, emotion and gender recognition with the proposed method yielded a lower joint loss, which is computed as the negative log-likelihood, than using static weights for joint loss.
Voice Imitating Text-to-Speech Neural Networks
We propose a neural text-to-speech (TTS) model that can imitate a new speaker's voice using only a small amount of speech sample.
Emotional End-to-End Neural Speech Synthesizer
In this paper, we introduce an emotional speech synthesizer based on the recent end-to-end neural model, named Tacotron.
Deep CNNs along the Time Axis with Intermap Pooling for Robustness to Spectral Variations
Convolutional neural networks (CNNs) with convolutional and pooling operations along the frequency axis have been proposed to attain invariance to frequency shifts of features.
Compositional Sentence Representation from Character within Large Context Text
In the HCRN, word representations are built from characters, thus resolving the data-sparsity problem, and inter-sentence dependency is embedded into sentence representation at the level of sentence composition.
