Recurrent Neural Networks are ubiquitous and pervasive in many artificial intelligence
applications such as speech recognition, predictive healthcare, creative art, and so on …

In our Big Data era, data is being generated, collected and analyzed at an unprecedented
scale, and data-driven decision making is sweeping through all aspects of society. Recent …

A method include placing a first processor in a sleep operating mode and running a second
processor that is operative to wake the first processor from the sleep operating mode in …

In this paper, we present an unsupervised learning framework to address the problem of
detecting spoken keywords. Without any transcription information, a Gaussian Mixture Model …

Spoken term detection (STD) provides an efficient means for content based indexing of
speech. However, achieving high detection performance, faster speed, detecting ot-of …

(*) Notice: Subject to any disclaimer, the term of this 2005. O197843 A1* 9, 2005 Faisman et
al. TO4, 276 patent is extended or adjusted under 35 2005/0203738 A1* 9/2005 …

A method include placing a first processor in a sleep operating mode and running a second
processor that is operative to wake the first processor from the sleep operating mode in …

A method include placing a first processor in a sleep operating mode and running a second
processor that is operative to wake the first processor from the sleep operating mode in …

In this paper, we propose an attention-based end-to-end neural approach for small-footprint
keyword spotting (KWS), which aims to simplify the pipelines of building a production-quality …

A method include placing a first processor in a sleep operating mode and running a second
processor that is operative to wake the first processor from the sleep operating mode in …