Search Results for author:
Found 9 papers, 0 papers with code
Predicting phoneme-level prosody latents using AR and flow-based Prior Networks for expressive speech synthesis
A large part of the expressive speech synthesis literature focuses on learning prosodic representations of the speech signal which are then modeled by a prior distribution during inference.
Generating Gender-Ambiguous Text-to-Speech Voices
While a female voice is a common choice, there is an increasing interest in alternative approaches where the gender is ambiguous rather than clearly identifying as female or male.
Learning utterance-level representations through token-level acoustic latents prediction for Expressive Speech Synthesis
We show that the fine-grained latent space also captures coarse-grained information, which is more evident as the dimension of latent space increases in order to capture diverse prosodic representations.
Cross-lingual Text-To-Speech with Flow-based Voice Conversion for Improved Pronunciation
When used in a cross-lingual setting, acoustic features are initially produced with a native speaker of the target language and then voice conversion is applied by the same model in order to convert these features to the target speaker's voice.
Fine-grained Noise Control for Multispeaker Speech Synthesis
A text-to-speech (TTS) model typically factorizes speech attributes such as content, speaker and prosody into disentangled representations. Recent works aim to additionally model the acoustic conditions explicitly, in order to disentangle the primary speech factors, i. e. linguistic content, prosody and timbre from any residual factors, such as recording conditions and background noise. This paper proposes unsupervised, interpretable and fine-grained noise and prosody modeling.
Self-supervised learning for robust voice cloning
This method enables us to train our model in an unlabeled multispeaker dataset as well as use unseen speaker embeddings to copy a speaker's voice.
Word-Level Style Control for Expressive, Non-attentive Speech Synthesis
This paper presents an expressive speech synthesis architecture for modeling and controlling the speaking style at a word level.
High Quality Streaming Speech Synthesis with Low, Sentence-Length-Independent Latency
This paper presents an end-to-end text-to-speech system with low latency on a CPU, suitable for real-time applications.
Using Audio Books for Training a Text-to-Speech System
Creating new voices for a TTS system often requires a costly procedure of designing and recording an audio corpus, a time consuming and effort intensive task.
