Neural technology generates audio with humanlike intonation,and 1000 times faster then before
Add voice to your website, grow your subscribers by creating podcasts and audiobooks,which nowadays is a very popular trend
Enable text-to-speech technology on your site to read content out loud for your audience. With GSpeech your audience can finally listen in to your content while being busy working, commuting, exercising, and having their eyes and hands full. With GSpeech you can increase user engagement and time spent on your site by allowing your visitors to listen in to the content of your website in the background while they’re working, commuting, eating, or having their hands busy.
You can improve your website’s accessibility which is often times forgotten and to empower visitors who have visual impairment and reading disabilities to still completely consume your content without the complications of reading.
Lastly, you can grow your subscribers and cast a wider net of audience who are more into listening to podcasts and audiobooks which nowadays is a very popular trend and growing behavior of people to consume content.
Are you ready to add voice to your website? Try GSpeech now!
Free version of GSpeech is using parametric speech synthesis algorithm, the same used by Google Translate.
Paid versions are using WaveNet Technology, which is a generative model for raw audio, and is some of the most advanced and realistic in the business(including Apple's Siri, which is using concatenative algorithm). WaveNet is a deep neural network for generating raw audio, based on Machine Learning, using Artificial Intelligence algorithms, and is developed by DeepMind. Currently it is a part of Google.
The following figure shows the quality of WaveNets on a scale from 1 to 5, compared with current best TTS systems (parametric and concatenative), and with human speech using Mean Opinion Scores (MOS).
MOS are a standard measure for subjective sound quality tests, and were obtained in blind tests with human subjects (from over 500 ratings on 100 test sentences). As we can see, WaveNets reduce the gap between the state of the art and human-level performance by over 50% for both US English and Mandarin Chinese.