Papers with in-browser implementation

2 papers
CNNs for NLP in the Browser: Client-Side Deployment and Visualization Opportunities (N18-5)

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Challenge: a JavaScript implementation of a convolutional neural network performs feedforward inference completely in the browser.
Approach: They propose a JavaScript implementation that performs feedforward inference completely in the browser.
Outcome: The proposed model performs feedforward inference completely in the browser without server requests . the proposed model is useful for applications with stringent latency requirements or low connectivity .
Honkling: In-Browser Personalization for Ubiquitous Keyword Spotting (D19-3)

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Challenge: keyword spotting systems are used for simple commands recognition on devices . however, voice-enabled web applications are few and far between . a prominent drawback is that most of these systems perform speech recognition in the cloud .
Approach: Honkling is a JavaScript-based keyword spotting system that can be deployed on user devices.
Outcome: Honkling is a JavaScript-based keyword spotting system that can be deployed on user devices.

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