Deep learning methods haverevolutionized speech recognition, image recognition, and
natural language processing since 2010. Each of these tasks involves a single modality in …

Transfer learning is a vital technique that generalizes models trained for one setting or task
to other settings or tasks. For example in speech recognition, an acoustic model trained for …

Text to speech (TTS), or speech synthesis, which aims to synthesize intelligible and natural
speech given text, is a hot research topic in speech, language, and machine learning …

Nowadays, deep learning is a current and a stimulating field of machine learning. Deep
learning is the most effective, supervised, time and cost efficient machine learning approach …

Voice cloning is a highly desired feature for personalized speech interfaces. We introduce a
neural voice cloning system that learns to synthesize a person's voice from only a few audio …

We present Char2Wav, an end-to-end model for speech synthesis. Char2Wav has two
components: a reader and a neural vocoder. The reader is an encoder-decoder model with …

We introduce a technique for augmenting neural text-to-speech (TTS) with low-dimensional
trainable speaker embeddings to generate different voices from a single model. As a starting …

This paper investigates a self-adaptation method for speech enhancement using auxiliary
speaker-aware features; we extract a speaker representation used for adaptation directly …

We introduce a technique for augmenting neural text-to-speech (TTS) with lowdimensional
trainable speaker embeddings to generate different voices from a single model. As a starting …

This review summarises the status of silent speech interface (SSI) research. SSIs rely on non-
acoustic biosignals generated by the human body during speech production to enable …