The company says the improvements boost the performance of its TrulyHandsfree technology by more than 65%. In addition, improved deep-neural network training enables improved near- and far-field speech recognition performance in all room conditions.
"In ideal conditions, an always-listening wake word recognizer should only wake the voice UI when it hears the wake word, and never false fire," says Todd Mozer, CEO of Sensory. "This is how we designed TrulyHandsfree to operate, and with the upgraded AI technologies in version 6.0, it works exactly as it should even in far less than ideal conditions."
"TrulyHandsfree has long been the performance benchmark that other voice UI solutions strive to match," says Mozer. "With our sixth generation, the bar for efficiency, security, wake word accuracy, and near- and far-field performance has been set much higher, making it the ideal wake word solution for any kind of voice-enabled product design."
Version 6.0 improves performance and word recognition accuracy relative to the last two generations of TrulyHandsfree by reducing wake word false positives by more than 65%, the company says. In addition, the new high-resolution speech feature also enables TrulyHandsfree to support multiple wake words, like "Okay Google" "Alexa," "Hey Cortana," "Hey Siri," and "Xiaodu, Xiaodu" in a single implementation.
The technology's improved neural network training allows the algorithms to anticipate a variety of factors associated with wake word performance, including understanding how one person - or a population of people - may pronounce a wake word. It also takes into consideration acoustic challenges like various room configurations, device placement, room size, reverb and echo, the company says.
Other improvements include enhanced security and improved barge-in and far-field performance.
The TrulyHandsfree SDK is available for Android, iOS, Linux, QNX, and Windows, and developer support is available for cloud service interfaces on Linux, Android, iOS and Windows as well as for dozens of proprietary DSPs, microcontrollers, smart microphones, and other low-power embedded devices. In addition,