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Found 9 papers, 2 papers with code
VocGAN: A High-Fidelity Real-time Vocoder with a Hierarchically-nested Adversarial Network
Additionally, compared with Parallel WaveGAN, another recently developed high-fidelity vocoder, VocGAN is 6. 98x faster on a CPU and exhibits higher MOS.
FastPitchFormant: Source-filter based Decomposed Modeling for Speech Synthesis
Methods for modeling and controlling prosody with acoustic features have been proposed for neural text-to-speech (TTS) models.
Detecting Mismatch between Text Script and Voice-over Using Utterance Verification Based on Phoneme Recognition Ranking
The purpose of this study is to detect the mismatch between text script and voice-over.
A Neural Text-to-Speech Model Utilizing Broadcast Data Mixed with Background Music
Second, the GST-TTS model with an auxiliary quality classifier is trained with the filtered speech and a small amount of clean speech.
GANSpeech: Adversarial Training for High-Fidelity Multi-Speaker Speech Synthesis
Recent advances in neural multi-speaker text-to-speech (TTS) models have enabled the generation of reasonably good speech quality with a single model and made it possible to synthesize the speech of a speaker with limited training data.
N-Singer: A Non-Autoregressive Korean Singing Voice Synthesis System for Pronunciation Enhancement
N-Singer consists of a Transformer-based mel-generator, a convolutional network-based postnet, and voicing-aware discriminators.
Hierarchical Context-Aware Transformers for Non-Autoregressive Text to Speech
Therefore, to improve the modeling performance of the TNA-TTS model we propose a hierarchical Transformer structure-based text encoder and audio decoder that are designed to accommodate the characteristics of each module.
An Empirical Study on L2 Accents of Cross-lingual Text-to-Speech Systems via Vowel Space
With the recent developments in cross-lingual Text-to-Speech (TTS) systems, L2 (second-language, or foreign) accent problems arise.
Latent Filling: Latent Space Data Augmentation for Zero-shot Speech Synthesis
Previous works in zero-shot text-to-speech (ZS-TTS) have attempted to enhance its systems by enlarging the training data through crowd-sourcing or augmenting existing speech data.
