2.2k citations · 7.1k across the 72 of their papers we have counts for
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VANI: Very-lightweight Accent-controllable TTS for Native and Non-native speakers with Identity Preservation
Rohan Badlani, Akshit Arora, Subhankar Ghosh +5
We introduce VANI, a very lightweight multi-lingual accent controllable speech synthesis system. Our model builds upon disentanglement strategies proposed in RADMMM and supports ex…
Multilingual Multiaccented Multispeaker TTS with RADTTS
Rohan Badlani, Rafael Valle, Kevin J. Shih +3
We work to create a multilingual speech synthesis system which can generate speech with the proper accent while retaining the characteristics of an individual voice. This is challe…
BigVGAN: A Universal Neural Vocoder with Large-Scale Training
Sang-gil Lee, Wei Ping, Boris Ginsburg +2
Despite recent progress in generative adversarial network (GAN)-based vocoders, where the model generates raw waveform conditioned on acoustic features, it is challenging to synthe…
Generative Modeling for Low Dimensional Speech Attributes with Neural Spline Flows
Kevin J. Shih, Rafael Valle, Rohan Badlani +2
Despite recent advances in generative modeling for text-to-speech synthesis, these models do not yet have the same fine-grained adjustability of pitch-conditioned deterministic mod…
Speech Denoising in the Waveform Domain with Self-Attention
Zhifeng Kong, Wei Ping, Ambrish Dantrey +1
In this work, we present CleanUNet, a causal speech denoising model on the raw waveform. The proposed model is based on an encoder-decoder architecture combined with several self-a…
One TTS Alignment To Rule Them All
Rohan Badlani, Adrian Łancucki, Kevin J. Shih +3
Speech-to-text alignment is a critical component of neural textto-speech (TTS) models. Autoregressive TTS models typically use an attention mechanism to learn these alignments on-l…