Google has launched a voice synthesiser services called “Cloud Text-to-Speech” which is powered by its Britain-based Artificial Intelligence (AI) subsidiary DeepMind. The service which is being used by Cisco and Dolphin ONE is now available for developers to add it in their own applications. In a blog post, Dan Aharon, Product Manager, Cloud AI at Google said, “Many Google products (e.g., the Google Assistant, Search, Maps) come with built-in high-quality text-to-speech synthesis that produces natural sounding speech. Developers have been telling us they'd like to add text-to-speech to their own applications, so today we're bringing this technology to Google Cloud Platform with Cloud Text-to-Speech.”
A text-to-speech service is a form of speech synthesis that converts text into spoken voice output. Google's text-to-speech are already an integral part of the voices in service like Google Assistant, Search and Maps. A text-to-speech can be used in variety of ways such as to power voice response systems for call centers (IVRs) and enabling real-time natural language conversations; to enable IoT devices (e.g., TVs, cars, robots) to talk back or to convert text-based media (e.g., news articles, books) into spoken format (e.g., podcast or audiobook).
“Cloud Text-to-Speech lets you choose from 32 different voices from 12 languages and variants. Cloud Text-to-Speech correctly pronounces complex text such as names, dates, times and addresses for authentic sounding speech right out of the gate. Cloud Text-to-Speech also allows you to customize pitch, speaking rate, and volume gain, and supports a variety of audio formats, including MP3 and WAV,” said Aharon,
Cloud Text-to-Speech also includes a selection of high-fidelity voices built using WaveNet, a generative model for raw audio created by DeepMind. Company informed that in late 2016, DeepMind introduced the first version of WaveNet — a neural network trained with a large volume of speech samples that's able to create raw audio waveforms from scratch. During training, the network extracts the underlying structure of the speech, for example which tones follow one another and what shape a realistic speech waveform should have. When given text input, the trained WaveNet model generates the corresponding speech waveforms, one sample at a time, achieving higher accuracy than alternative approaches.
Now company is using an updated version of WaveNet that runs on Google's Cloud TPU infrastructure. The new, improved WaveNet model generates raw waveforms 1,000 times faster than the original model, and can generate one second of speech in just 50 milliseconds. “In fact, the model is not just quicker, but also higher-fidelity, capable of creating waveforms with 24,000 samples a second. We've also increased the resolution of each sample from 8 bits to 16 bits, producing higher quality audio for a more human sound,” said Aharon.
Google said with these adjustments, the new WaveNet model produces more natural sounding speech. “As WaveNet voices also require less recorded audio input to produce high quality models, we expect to continue to improve both the variety as well as quality of the WaveNet voices available to Cloud customers in the coming months,” said Aharon
For Google, Cloud Text-to-Speech customers include Cisco and Dolphin ONE. “As the leading provider of collaboration solutions, Cisco has a long history of bringing the latest technology advances into the enterprise. Google's Cloud Text-to-Speech has enabled us to achieve the natural sound quality that our customers desire,” said Tim Tuttle, CTO of Cognitive Collaboration, Cisco
“Dolphin ONE's Calll.io telephony platform offers connectivity from a multitude of devices, at practically any location. We've integrated Cloud Text-to-Speech into our products and allow our users to create natural call center experiences. By using Google Cloud's machine learning tools, we're instantly delivering cutting-edge technology to our users,” said Jason Berryman, Dolphin ONE
