Open Voice Network Aims for Standards-based Voice Assistants

The Linux Foundation, a nonprofit organization dedicated to advancing open-source development, recently launched the Open Voice Network. Along with other partners, the alliance hopes to use open-source solutions to advance the development of AI-enabled voice assistance systems.

Delivering standards to an open field

As different organizations develop programs independent of major voice platforms, the Open Voice Network will deliver much-needed standards and usage guidelines to enable trustworthy, inclusive AI programs. Because much development centers around delivering an end-to-end experience, companies are concerned about developing solutions that focus on and protect the consumer.

Founding members include Target, Microsoft, and Wegmans, among others. The mission is to bring together different aspects of development to ensure that it follows an ethical and comprehensive path.

How the open voice network works

The initial offering will be a unified interface to the digital world, bringing together billions of sites, smart environments, and bots. It will standardize development much like development in the early days of the internet. Linux hopes that this standardization will bring greater rates of development and innovation in the world.

Initially, the network will focus on:

• Developing standards that enable inclusivity and trust while protecting consumer interests
• Industry value and awareness with best practices designed for multiple verticals as well as horizontal applications.
• Advocacy for relevant legislation and policy development

Membership to the network includes a commitment of resources dedicated to the cause and support of its research. Members must also participate in symposia and workshops as well. It offers an open governance model that values and accepts input from all members as well as community-wide input in hopes of rapid development.

Such capabilities with respect to development will impact many industries, including automobile and transportation, smartphones, and smart homes. Development and research will depend on natural language processing, automatic speech recognition, and machine learning methods.