Described herein are systems and methods for augmenting neural speech synthesis
networks with low-dimensional trainable speaker embeddings in order to generate speech …

Described herein are embodiments of an end-to-end text-to speech (TTS) system with
parallel wave generation. In one or more embodiments, a Gaussian inverse autoregressive …

Embodiments of a production-quality text-to-speech (TTS) system constructed from deep
neural networks described. System embodiments comprise five major build ing blocks: a …

Presented herein are embodiments of a non-autoregressive sequence-to-sequence model
that converts text to an audio representation. Embodiment are fully convolutional, and a …

Described herein are embodiments of a fully-convolutional attention-based neural text-to-
speech (TTS) system, which various embodiments may generally be referred to as Deep …

Described herein are embodiments of an end-to-end text-to-speech (TTS) system with
parallel wave generation. In one or more embodiments, a Gaussian inverse autoregressive …

A system and method are presented for outlier identification to remove poor alignments in
speech synthesis. The quality of the output of a text-to-speech system directly depends on …

Disclosed is a pronunciation transcription method performed by a computing device. The
method may include: acquiring a partial audio signal of a first sound unit generated by …

An acoustic model training method, a speech recognition method, an apparatus, a device
and a medium. The acoustic model training method comprises: performing feature extraction …

the present disclosure relates generally to systems and methods for machine learning that
can provide improved computer performance, features, and uses. More particularly, the …