Sound source localization confidence estimation using machine learning

A method of using machine learning to perform sound source localization confidence estimation using at least one of (a) one or more processors, (b) hardware logic, or (c) electrical circuitry, the method comprising:

• performing a sound source localization (SSL) operation with regard to a sound to determine an SSL direction estimate, which indicates an estimated direction from which the sound is received, and an SSL-based confidence associated with the SSL direction estimate based at least in part on a multi-channel representation of the sound,
• the SSL-based confidence indicating an estimated probability that the sound is received from the estimated direction,
• the multi-channel representation including a plurality of representations of the sound that are detected by a plurality of respective sensors;
• automatically determining one or more additional characteristics of the sound;
• and
• performing a machine learning (ML) operation based at least in part on the SSL direction estimate, the SSL-based confidence, and the one or more additional characteristics to determine an ML-based confidence associated with the SSL direction estimate and to generate a feature set of a machine learning model that is usable in a subsequent machine learning operation to determine an ML-based confidence inference based at least in part on a second SSL direction estimate that indicates a second estimated direction from which a second sound is received, a second SSL-based confidence that indicates an estimated probability that the second sound is received from the second estimated direction, and one or more additional characteristics of the second sound.

A system to use machine learning to perform sound source localization confidence estimation, the system comprising:

• memory;
• and
• one or more processors coupled to the memory and configured to:
• perform a sound source localization (SSL) operation with regard to a sound to determine an SSL direction estimate, which indicates an estimated direction from which the sound is received, and an SSL-based confidence associated with the SSL direction estimate based at least in part on a multi-channel representation of the sound,
• the SSL-based confidence indicating an estimated probability that the sound is received from the estimated direction,
• the multi-channel representation including a plurality of representations of the sound that are detected by a plurality of respective sensors;
• automatically determine one or more additional characteristics of the sound;
• perform a machine learning (ML) operation based at least in part on the SSL direction estimate, the SSL-based confidence, and the one or more additional characteristics to determine an ML-based confidence associated with the SSL direction estimate;
• and
• determine an angle in which to point a video camera in accordance with a dynamic video zoom operation based at least in part on the ML-based confidence.