Keyword Transformer: A Self-Attention Model For Keyword Spotting


The Transformer architecture has been successful across many domains, including natural language processing, computer vision and speech recognition. In keyword spotting, self-attention has primarily been used on top of convolutional or recurrent encoders. We investigate a range of ways to adapt the Transformer architecture to keyword spotting and introduce the Keyword Transformer (KWT), a fully... » read more

Speech Applications Will Enable A New Category Of Edge AI Chips


Speech recognition has become an increasingly important feature in a wide range of devices. Wakewords such as Alexa or OK Google or Siri have now become a standard feature of wearables, smart-speakers, mobile phones, and even laptops. These devices have already shipped in millions of units and consumers are getting better at utilizing this feature. The wakeword recognition feature is slowly evo... » read more

Babblelabs: Deep Learning Speech Processing


Pronounced “babble labs,” a startup that is the brainchild of serial entrepreneur [getperson id="11244" comment="Chris Rowen"] is setting out to transform speech processing and will leverage deep learning to do so. Rowen, CEO of Babblelabs, has spoken for some time about move of processing to more general purpose hardware, with applications layered on top, so it’s not so surprising his... » read more