Implicit Acoustic Echo Cancellation for Keyword Spotting and Device-Directed Speech Detection

In these are increasingly realistic or include celebrity-derived custom instances, the performance of tasks such as keyword-spotting voices. This can lead to the device "self waking" and continuously (KWS) and device-directed speech detection (DDD) can degrade interrupting itself as the model, alone, cannot implicitly significantly. To address this problem, we propose an distinguish between user and device speech and ignore this implicit acoustic echo cancellation (iAEC) framework where latter. Such problem also affects automatic speech recognition a neural network is trained to exploit the additional information (ASR) or keyword-less initiated interactions, such as from a reference microphone channel to learn to ignore device-directed detection (DDD) [7-10]. One trivial way to the interfering signal and improve detection performance. We mitigate this issue would be disabling the KWS functionality study this framework for the tasks of KWS and DDD on, while the device is in playback. Yet, doing so prevents the respectively, an augmented version of Google Speech Commands user to "barge in", making the interaction significantly less v2 and a real-world Alexa device dataset.