Alexander C.S. Hendorf: Speech Synthesis with Tacotron2 and PyTorch | PyData Amsterdam 2019

Описание: Computer generated speech has existed for a while, parameters being painfully engineered by hand. Deep Learning models can be efficient at learning inherent features of data - how well does this work out for audio?

There are different DL-models as WaveNet, SampleRNN and Tacotron2. After a quick overview, I'm going to focus on Tacotron2 - how it works, it's benefits and how to implement it with PyTorch.

With Tacotron2 we make no assumption what features should be passed to the vocoder. All there is required are audio-snippets and corresponding text. Non-English language audio datasets are hard to get. I had to generate my own dataset. This talk will also cover how I have created my own dataset in a semi-automatic efficiently with tools like audiotok and methods as Speaker diarisation.

The talks will feature synthesised speech audio demos. I will also cover some failures and reason about them.

Alexander C.S. Hendorf is an independent AI strategy consultant with over 20 years of experience in digitalization and data-driven transformation. Through his commitment as a speaker and chair of various international conferences, he is a proven expert in the field of data intelligence. He has extensive experience in the practical application, introduction and communication of data and AI-driven strategies and decision-making processes.
https://hendorf.com

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