  Voice assistants like Siri, Google Assistant, Alexa etc. are used widely
across the globe for home automation, these require the use of special phrases
also known as hotwords to wake it up and perform an action like "Hey Alexa!",
"Ok Google!" and "Hey Siri!" etc. These hotwords are detected with lightweight
real-time engines whose purpose is to detect the hotwords uttered by the user.
This paper presents the design and implementation of a hotword detection engine
based on one-shot learning which detects the hotword uttered by the user in
real-time with just one or few training samples of the hotword. This approach
is efficient when compared to existing implementations because the process of
adding a new hotword in the existing systems requires enormous amounts of
positive and negative training samples and the model needs to retrain for every
hotword. This makes the existing implementations inefficient in terms of
computation and cost. The architecture proposed in this paper has achieved an
accuracy of 94.51%.
