How ITS Uses Machine Learning to Measure and Improve Speech Quality

When public safety professionals use telecommunications systems to communicate with one another, it’s easy for them to tell when there’s an issue with the signals—they hear distorted sound, static or interruptions, to name a few examples.

Fixing these issues is much tougher. As the amount of spectrum used to transmit speech decreases, so do speech quality and intelligibility. A reliable system for measuring speech quality and intelligibility is required to optimize the two quantities—adjusting bandwidth use to efficiently deliver acceptable quality and intelligibility.

Unfortunately, measurements using human listeners are time-consuming and expensive. Existing automated measurements are fast, but require systems to be taken offline to be tested. Improving these kinds of measurements would lead to more reliable and efficient telecommunications systems. This is especially critical for systems used by first responders, when clear voice communications can save lives.

Read more…