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Found 12 papers, 0 papers with code
LaughNet: synthesizing laughter utterances from waveform silhouettes and a single laughter example
Emotional and controllable speech synthesis is a topic that has received much attention.
Preliminary study on using vector quantization latent spaces for TTS/VC systems with consistent performance
Generally speaking, the main objective when training a neural speech synthesis system is to synthesize natural and expressive speech from the output layer of the neural network without much attention given to the hidden layers.
Latent linguistic embedding for cross-lingual text-to-speech and voice conversion
As the recently proposed voice cloning system, NAUTILUS, is capable of cloning unseen voices using untranscribed speech, we investigate the feasibility of using it to develop a unified cross-lingual TTS/VC system.
NAUTILUS: a Versatile Voice Cloning System
By using a multi-speaker speech corpus to train all requisite encoders and decoders in the initial training stage, our system can clone unseen voices using untranscribed speech of target speakers on the basis of the backpropagation algorithm.
Bootstrapping non-parallel voice conversion from speaker-adaptive text-to-speech
Voice conversion (VC) and text-to-speech (TTS) are two tasks that share a similar objective, generating speech with a target voice.
A Unified Speaker Adaptation Method for Speech Synthesis using Transcribed and Untranscribed Speech with Backpropagation
In this study, we propose a novel speech synthesis model, which can be adapted to unseen speakers by fine-tuning part of or all of the network using either transcribed or untranscribed speech.
Training Multi-Speaker Neural Text-to-Speech Systems using Speaker-Imbalanced Speech Corpora
When the available data of a target speaker is insufficient to train a high quality speaker-dependent neural text-to-speech (TTS) system, we can combine data from multiple speakers and train a multi-speaker TTS model instead.
Multimodal speech synthesis architecture for unsupervised speaker adaptation
Two new training schemes for the new architecture are also proposed in this paper.
Investigating accuracy of pitch-accent annotations in neural network-based speech synthesis and denoising effects
We investigated the impact of noisy linguistic features on the performance of a Japanese speech synthesis system based on neural network that uses WaveNet vocoder.
Wasserstein GAN and Waveform Loss-based Acoustic Model Training for Multi-speaker Text-to-Speech Synthesis Systems Using a WaveNet Vocoder
In order to reduce the mismatched characteristics between natural and generated acoustic features, we propose frameworks that incorporate either a conditional generative adversarial network (GAN) or its variant, Wasserstein GAN with gradient penalty (WGAN-GP), into multi-speaker speech synthesis that uses the WaveNet vocoder.
Scaling and bias codes for modeling speaker-adaptive DNN-based speech synthesis systems
Most neural-network based speaker-adaptive acoustic models for speech synthesis can be categorized into either layer-based or input-code approaches.
A non-expert Kaldi recipe for Vietnamese Speech Recognition System
In this paper we describe a non-expert setup for Vietnamese speech recognition system using Kaldi toolkit.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
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