AI has provided us with the ability to automate tasks, extract information from vast amounts of
data, and synthesize media that is nearly indistinguishable from the real thing. However …

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 …

Neural network based end-to-end text to speech (TTS) has significantly improved the quality
of synthesized speech. Prominent methods (eg, Tacotron 2) usually first generate mel …

Background: The number of publications in supply chain management (SCM) and artificial
intelligence (AI) has risen significantly in the last two decades, and their quality and …

This paper introduces a new end-to-end text-to-speech (E2E-TTS) toolkit named ESPnet-
TTS, which is an extension of the open-source speech processing toolkit ESPnet. The toolkit …

Unsupervised speech recognition has shown great potential to make Automatic Speech
Recognition (ASR) systems accessible to every language. However, existing methods still …

Speech synthesis (text to speech, TTS) and recognition (automatic speech recognition, ASR)
are important speech tasks, and require a large amount of text and speech pairs for model …

In this paper, we propose MixSpeech, a simple yet effective data augmentation method
based on mixup for automatic speech recognition (ASR). MixSpeech trains an ASR model …

Neural architecture search (NAS) relies on a good controller to generate better architectures
or predict the accuracy of given architectures. However, training the controller requires both …

An unsupervised text-to-speech synthesis (TTS) system learns to generate speech
waveforms corresponding to any written sentence in a language by observing: 1) a …