NovoSpeech, a specialist in developing speech recognition solutions, has announced that it has recently been acknowledged that its “virtual microphone array” application has been approved by the USPTO. The company won this new patent for its advancement in building an exclusive algorithm that generates a number of independent channels, while making an array effect from a single speech signal and a microphone.
NovoSpeech’s virtual microphone array drastically improves signal in a noisy environment and augments the speech signal against background noise, all without de-noising the speech signal and keeping the important data intact.
Tina Ornstein, CEO of NovoSpeech said, “This is great news for us. Additionally, our quantum search patent application claims were deemed innovative, inventive, and industrially applicable by the international PCT examiner, which puts us on an accelerated track for our national applications. We recently applied on an accelerated track for a U.S. patent and expect to have it granted in 3 to 4 months.”
The NovoSpeech technology promises to offer reliable and superior user experience in real-life environments that will allow speech recognition to enter the mass markets.
Ornstein said that the new patent relates to their ability to carry out very large vocabulary recognition in the small, constrained environments of mobile devices. Also, NovoSpeech solution can accurately identify words regardless of gender, accent, or speaking style.
Steve Rhodes, Chairman and CEO of Trendlines, adds: “This is an incredible milestone for NovoSpeech and validates their cutting-edge technology. The ability to significantly enhance automatic speech recognition allows NovoSpeech a larger stake in a relatively untapped market. We look forward to the Company’s next developments.”
NovoSpeech is an Israel-based company devoted to develop leading-edge speech recognition engine that claims to provides highly robust, large vocabulary speech recognition entirely on-device — without the need to connect to the cloud, as required by current leading speech recognition solutions for mobile devices.
Edited by Cassandra Tucker