Artificial intelligence has become part of nearly every aspect of our lives, from content-aware fills for video and photos, facial recognition to unlock your phone and even recommendations for your mobile coffee order. The field is growing so rapidly, it’s becoming increasingly difficult to nail down a definitive definition. Machine learning, deep learning, natural language processing (NLP), computer vision, voice recognition and speech synthesis… all these and many more fall under the umbrella of artificial intelligence.
IBM, Google, Amazon and many others have created API endpoints for developers to integrate and start leveraging AI in their own projects. AI trained on millions of data sets and models are at your fingertips. Hooking into machine learning power has never been easier.
Imagine building a web-based app that can not only understand what a user is saying to it, but also respond in a voice customised to their liking. All in real time. Combining chatbot dialog models with voice recognition and now voice synthesis, this scenario has become a reality. You can develop solutions for education, hands-free communications, call-centre automation and engaging games and web experiences.
In this tutorial, you are going to create a simple app to enable you to return AI-powered, human-sounding speech, based on values you choose.
SPEECH SYNTHESIS (TEXT-TO-SPEECH)
Speech synthesis, or text-to-speech, is the conversion of text input into human-like speech. Although on the surface the concept may seem simple, the complexity of making a sound humanlike requires vast amounts of AI training. DeepMind has developed groundbreaking technology called WaveNet that can create extremely human-sounding voices. Combining this with neural networks yields an increasing range of voices and options.
SOME KEY FEATURES OF SPEECH SYNTHESIS
This story is from the April 2020 edition of NET.
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This story is from the April 2020 edition of NET.
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