Muting Specific Talkers Using a Beamforming Microphone Array
This disclosure describes an invention that that mutes specific talkers using at least one beamforming microphone array 102 that is configured to generate N audio signals 108 where each audio signal is associated with a spatial pickup pattern 130 , the microphone array(s) 102 are located in a room 200 ; a processor 104 and memory 105 operably coupled to the microphone array 102 , the processor 104 configured to execute the following steps: (a) selectively mute or unmute an individual talker the room with a mute function 106 that controls whether to mute or unmute the individual talker T1-T7 that is picked up by one or more of the individual audio signals, the mute function 106 includes speech learning that learns to identify different talkers in real time to allow the mute function 106 to identify transitions from one talker to another talker in the room 200 , (b) output an audio signal 110 based on the selective muting of the talkers T1-T7 in the room 200.
1 . An apparatus that mutes specific talkers using beamforming microphone arrays, comprising:
at least one microphone array configured for beamforming where an individual microphone array includes a plurality of microphones where each individual microphone is configured to sense audio signals and the microphone array is configured to generate N audio signals where each audio signal is associated with a spatial pickup pattern, the microphone array(s) are located in a room;
a processor and memory operably coupled to the microphone array, the processor configured to execute the following steps:
selectively mute or unmute an individual talker the room with a mute function that controls whether to mute or unmute the individual talker that is picked up by one or more of the individual audio signals, the mute function includes speech learning that learns to identify different talkers in real time to allow the mute function to identify transitions from one talker to another talker in the room;
output an audio signal based on the selective muting of the talkers in the room.
2 . The claim according to claim 1 where the mute function uses one or more of the following techniques to assist in identifying individual talkers: artificial intelligence, machine learning, or deep learning.
3 . The claim according to claim 1 that further includes at least one video camera that uses facial recognition and/or mouth-movement detection to assist in the learning and identifying the individual talkers.
4 . The claim according to claim 1 that further includes a user interface so that a user can selectively mute a sound source and/or one or more individual talkers.
5 . The claim according to claim 1 that further includes a diarization function configured to assist in identifying the individual talkers.
6 . The claim according to claim 1 that further includes a speaker separation function configured assist in separating the individual talkers in an audio signal.
7 . A method to make an apparatus that mutes specific talkers using beamforming microphone arrays, comprising:
providing at least one microphone array configured for beamforming where an individual microphone array includes a plurality of microphones where each individual microphone is configured to sense audio signals and the microphone array is configured to generate N audio signals where each audio signal is associated with a spatial pickup pattern, the microphone array(s) are located in a room,
operably coupling a processor and memory to the microphone array, the processor configured to execute the following steps:
selectively mute or unmute an individual talker the room with a mute function that controls whether to mute or unmute the individual talker that is picked up by one or more of the individual audio signals, the mute function includes speech learning that learns to identify different talkers in real time to allow the mute function to identify transitions from one talker to another talker in the room,
output an audio signal based on the selective muting of the talkers in the room.
8 . The claim according to claim 7 where the mute function uses one or more of the following techniques to assist in identifying individual talkers: artificial intelligence, machine learning, or deep learning.
9 . The claim according to claim 7 that further includes at least one video camera that uses facial recognition and/or mouth-movement detection to assist in the learning and identifying the individual talkers.
10 . The claim according to claim 7 that further includes a user interface so that a user can selectively mute a sound source and/or one or more individual talkers.
11 . The claim according to claim 7 that further includes a diarization function configured to assist in identifying the individual talkers.
12 . The claim according to claim 7 that further includes a speaker separation function configured assist in separating the individual talkers in an audio signal.
13 . A method to use an apparatus that mutes specific talkers using beamforming microphone arrays, comprising:
beamforming with at least one microphone array where an individual microphone array includes a plurality of microphones where each individual microphone is configured to sense audio signals and the microphone array is configured to generate N audio signals where each audio signal is associated with a spatial pickup pattern, the microphone array(s) are located in a room;
processing with a processor and memory operably coupled to the microphone array, the processor configured to execute the following steps:
selectively mute or unmute an individual talker the room with a mute function that controls whether to mute or unmute the individual talker that is picked up by one or more of the individual audio signals, the mute function includes speech learning that learns to identify different talkers in real time to allow the mute function to identify transitions from one talker to another talker in the room;
output an audio signal based on the selective muting of the talkers in the room.
14 . The claim according to claim 13 where the mute function uses one or more of the following techniques to assist in identifying individual talkers: artificial intelligence, machine learning, or deep learning.
15 . The claim according to claim 13 that further includes at least one video camera that uses facial recognition and/or mouth-movement detection to assist in the learning and identifying the individual talkers.
16 . The claim according to claim 13 that further includes a user interface so that a user can selectively mute a sound source and/or one or more individual talkers.
17 . The claim according to claim 13 that further includes a diarization function configured to assist in identifying the individual talkers.
18 . The claim according to claim 13 that further includes a speaker separation function configured assist in separating the individual talkers in an audio signal.
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