15 citations · 16 across the 6 of their papers we have counts for
6 papers · 1 filter
Robust and Unbounded Length Generalization in Autoregressive Transformer-Based Text-to-Speech
Eric Battenberg, RJ Skerry-Ryan, Daisy Stanton +4
Autoregressive (AR) Transformer-based sequence models are known to have difficulty generalizing to sequences longer than those seen during training. When applied to text-to-speech…
Spoken Question Answering and Speech Continuation Using Spectrogram-Powered LLM
Eliya Nachmani, Alon Levkovitch, Roy Hirsch +6
We present Spectron, a novel approach to adapting pre-trained large language models (LLMs) to perform spoken question answering (QA) and speech continuation. By endowing the LLM wi…
Wave-Tacotron: Spectrogram-free end-to-end text-to-speech synthesis
Ron J. Weiss, RJ Skerry-Ryan, Eric Battenberg +2
We describe a sequence-to-sequence neural network which directly generates speech waveforms from text inputs. The architecture extends the Tacotron model by incorporating a normali…
Semi-Supervised Generative Modeling for Controllable Speech Synthesis
Raza Habib, Soroosh Mariooryad, Matt Shannon +5
We present a novel generative model that combines state-of-the-art neural text-to-speech (TTS) with semi-supervised probabilistic latent variable models. By providing partial super…
Location-Relative Attention Mechanisms For Robust Long-Form Speech Synthesis
Eric Battenberg, RJ Skerry-Ryan, Soroosh Mariooryad +4
Despite the ability to produce human-level speech for in-domain text, attention-based end-to-end text-to-speech (TTS) systems suffer from text alignment failures that increase in f…
Effective Use of Variational Embedding Capacity in Expressive End-to-End Speech Synthesis
Eric Battenberg, Soroosh Mariooryad, Daisy Stanton +4
Recent work has explored sequence-to-sequence latent variable models for expressive speech synthesis (supporting control and transfer of prosody and style), but has not presented a…