MULTI-TASK LEARNING FOR PERSONALIZED KEYWORD SPOTTING: abstract simplified (18153932)

Systems and techniques are described for processing audio data using personalized keyword spotting through multi-task learning (PK-MTL). This involves obtaining an audio sample and generating representations of both a keyword and a speaker based on the sample. These representations are then used to determine a similarity score against a reference representation. Based on this score and a threshold, a keyword spotting output is generated, indicating whether the audio sample includes a target keyword or not.