ReadSpeaker Neural TTS Engine to be made available in October 2020

ReadSpeaker, the most trusted, independent digital voice partner for global businesses, unveiled ReadSpeaker Neural TTS Engine, a Deep Neural Network (DNN) engine powering the company’s voice enablement platform. With its Neural TTS Engine, ReadSpeaker can generate superior-quality speech using DNN-trained models and produce voice solutions at a fraction of the time required by legacy offerings. The enhanced platform comes amid explosive interest among businesses to use voice technology to best engage audiences in an increasingly contactless world.

The Neural TTS Engine builds on ReadSpeaker’s foundational voice enablement platform, which today provides 90 text-to-speech (TTS), off-the-shelf voices available in 40 languages. By adding the capability to create a voice with DNN-trained models, ReadSpeaker will now be able to not only produce voice solutions faster—in six to eight weeks, versus six months—but also customize those voices to meet brands’ unique needs.

“The COVID-19 pandemic is changing the way that organizations connect with their target audiences,” said Matt Muldoon, President, North America, ReadSpeaker. “Physical interactions are being replaced with contactless ones, and brands need to quickly identify new ways to engage consumers—or risk losing market share. Custom voice is an innovative, safe solution for fostering human connection between brand and audience. With ReadSpeaker Neural TTS Engine, we allow brands to quickly develop unique, lifelike voices that can be used across various customer touchpoints. Brands can’t afford to wait on integrating custom voice into their customer engagement mix.”   

The unveiling of Neural TTS Engine follows the launch of ReadSpeaker’s VoiceLab earlier this year, designed to help companies create user-centric, expressive voice interfaces. Now, ReadSpeaker makes it even easier to create compelling custom voices by leveraging DNN models that capture various aspects of voice—including speaking style, dialect and gender.

 “We’ve spent the last three years building ReadSpeaker Neural TTS Engine,” said Niclas Bergstrom, CTO, ReadSpeaker. “With DNN technology, we can use less recording data to create higher-quality custom voices, as well as standard voices. This means faster development cycles, rapid ability to scale and accelerated ROI for our customers. We believe this solution will catalyze voice adoption.”