A method and system for real-time customizing and synchronizing media by a client device in communication with a server device. A client device customizes stock media content based on user preferences, and synchronizes the customized content for playback with a server-side playback of the stock media content.

A data processing method according to the present invention comprises the steps of: receiving an input of video contents including a video stream and an audio stream; detecting music data from the audio stream; and filtering the audio stream so that the music data detected from the audio stream is removed.

A data processing method according to the present invention comprises the steps of: receiving an input of video contents including a video stream and an audio stream; detecting music data from the audio stream; and filtering the audio stream so that the music data detected from the audio stream is removed.

An electronic device receives an audio file and divides the audio file into a plurality of segments. The electronic device, automatically, without user input, determines, for each segment, a descriptor from a plurality of descriptors and a value of the descriptor for the segment. The electronic device selects one or more segments of the plurality of segments, based on a comparison of the respective values of respective descriptors for respective segments and genre-specific criteria selected based on a genre of the audio file. The electronic device generates a trailer for the audio file using the selected one or more segments.

One or more embodiments include an emotion analysis system for computing and analyzing emotional state of a user. The emotion analysis system acquires, via at least one sensor, sensor data associated with a user. The emotion analysis system determines, based on the sensor data, an emotional state associated with a user. The emotion analysis system determines a first component of the emotional state that corresponds to media content being accessed by the user. The emotion analysis system applies a first function to the emotional state to remove the first component from the emotional state.

One or more embodiments include an emotion analysis system for computing and analyzing emotional state of a user. The emotion analysis system acquires, via at least one sensor, sensor data associated with a user. The emotion analysis system determines, based on the sensor data, an emotional state associated with a user. The emotion analysis system determines a first component of the emotional state that corresponds to media content being accessed by the user. The emotion analysis system applies a first function to the emotional state to remove the first component from the emotional state.

Various implementations include systems for processing microphone audio signals for a wearable audio device. In particular implementations, a method for processing signals includes: capturing an internal signal with an inner microphone configured to be acoustically coupled to an environment inside an ear canal of a user; extracting a low frequency audio signal from the internal signal; capturing an external signal with an external microphone configured to be acoustically coupled to an environment outside the ear canal of the user; extracting a high frequency audio signal from the external signal; and mixing the high frequency audio signal with the low frequency audio signal.

Various implementations include systems for processing microphone audio signals for a wearable audio device. In particular implementations, a method for processing signals includes: capturing an internal signal with an inner microphone configured to be acoustically coupled to an environment inside an ear canal of a user; extracting a low frequency audio signal from the internal signal; capturing an external signal with an external microphone configured to be acoustically coupled to an environment outside the ear canal of the user; extracting a high frequency audio signal from the external signal; and mixing the high frequency audio signal with the low frequency audio signal.

According to one implementation, an automated audio mapping system includes a computing platform having a hardware processor and a system memory storing an audio mapping software code including an artificial neural network (ANN) trained to identify multiple different audio content types. The hardware processor is configured to execute the audio mapping software code to receive content including multiple audio tracks, and to identify, without using the ANN, a first music track and a second music track of the multiple audio tracks. The hardware processor is further configured to execute the audio mapping software code to identify, using the ANN, the audio content type of each of the multiple audio tracks except the first music track and the second music track, and to output a mapped content file including the multiple audio tracks each assigned to a respective one predetermined audio channel based on its identified audio content type.

According to one implementation, an automated audio mapping system includes a computing platform having a hardware processor and a system memory storing an audio mapping software code including an artificial neural network (ANN) trained to identify multiple different audio content types. The hardware processor is configured to execute the audio mapping software code to receive content including multiple audio tracks, and to identify, without using the ANN, a first music track and a second music track of the multiple audio tracks. The hardware processor is further configured to execute the audio mapping software code to identify, using the ANN, the audio content type of each of the multiple audio tracks except the first music track and the second music track, and to output a mapped content file including the multiple audio tracks each assigned to a respective one predetermined audio channel based on its identified audio content type.