Abstract: Techniques for improving sound source localization (SSL) are provided. A method for probabilistic SSL using a deep neural network (DNN) may include receiving audio data including a representation of audio such as a wakeword from a microphone array. The audio data may be processed by a DNN to output a plurality of values where each value indicates a probability that the audio originated from a direction corresponding to that value. A sensor may provide computer vision or other data which may be used to inform the plurality of values based on detecting presence of a human or obstacle. A probability that the audio originated from one of the directions of the plurality of directions may be determined based at least in part on the DNN output and the computer vision or other data.

Abstract: A device capable of autonomous motion may move in response to a user speaking an utterance, such as a command. Before moving, the device processes audio data received from a microphone array to identify different audio signals arriving at the device from different directions. Based on properties of the audio signals, the device determines which of the audio signals are merely reflections of other audio.

Abstract: A voice-controlled device includes a beamformer for determining audio data corresponding to one or more directions and a beam selector for selecting in which direction a source of target audio lies. The device determines magnitude spectrums for each beam and for each frequency bin in each beam for each frame of audio data. The device determines frame-by-frame changes in the magnitude and filters the changes to smooth them. The device selects the beam having the greatest smoothed change in magnitude as corresponding to speech.