Glossary>Generative AI Tools>DeepMind WaveNet

DeepMind WaveNet

DeepMind WaveNet is a generative model for creating raw audio waveforms. It produces high-quality, realistic human-like speech and can generate other types of audio, such as music and sound effects.

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About DeepMind WaveNet

DeepMind WaveNet was introduced in 2016 by DeepMind, a subsidiary of Alphabet Inc. It was developed to improve the naturalness and quality of synthetic speech, surpassing previous text-to-speech systems in realism and clarity.

Strengths of DeepMind WaveNet included its ability to generate highly realistic and natural-sounding speech. Weaknesses involved high computational requirements and latency issues. Competitors included Google's Tacotron, Amazon Polly, and IBM Watson Text to Speech.

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How to hire a DeepMind WaveNet expert

A DeepMind WaveNet expert must have skills in deep learning, neural networks, audio signal processing, Python programming, TensorFlow or PyTorch frameworks, and experience with generative models.

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