A mask estimation apparatus for estimating mask information for specifying a mask used to extract a signal of a specific sound source from an input audio signal includes a converter which converts the input audio signal into embedded vectors of a predetermined dimension using a trained neural network model and a mask calculator which calculates the mask information by fitting the embedded vectors to a mixed Gaussian model.

A wearable badge for an employee that records and transmits audio from client interactions with the professional, comprising two microphones and two microphone channels that focus one microphone on the speech of the employee and the other microphone on the speech of the customer, making diarizing easier. The wearable badge also comprises a module to determine whether or not the employee is maintaining an appropriate social distance with customers.

A wearable badge for an employee that records and transmits audio from client interactions with the professional, comprising two microphones and two microphone channels that focus one microphone on the speech of the employee and the other microphone on the speech of the customer, making diarizing easier. The wearable badge also comprises a module to determine whether or not the employee is maintaining an appropriate social distance with customers.

Assigning spatial information to audio segments is disclosed. A method includes receiving a first audio segment that is non-spatialized and is associated with first video frames; identifying visual objects in the first video frames; identifying auditory events in the first audio segment; identifying a match between a visual object of the visual objects and an auditory event of the auditory events; and assigning a spatial location to the auditory event based on a location of the visual object.

An acoustic analysis device and the like that can separate acoustic signals of a target sound source at a higher speed are provided. The acoustic analysis device includes: an acquiring unit configured to acquire acoustic signals; a first generating unit configured to generate acoustic signals of diffuse noise using a first model which includes a spatial correlation matrix related to frequency, a first parameter related to the frequency, and a second parameter related to the frequency and time; a second generating unit configured to generate acoustic signals emitted from a target sound source using a second model which includes a steering vector related to the frequency, and a third parameter related to the frequency and the time; and a determining unit configured to determine the first parameter, the second parameter and the third parameter so that the likelihood of the first parameter, the second parameter and the third parameter is maximized. The determining unit decomposes an inverse matrix of the matrix related to the frequency and the time into an inverse matrix of the matrix related to the frequency, and determines the first parameter, the second parameter and the third parameter so that the likelihood is maximized.

An acoustic analysis device and the like that can separate acoustic signals of a target sound source at a higher speed are provided. The acoustic analysis device includes: an acquiring unit configured to acquire acoustic signals; a first generating unit configured to generate acoustic signals of diffuse noise using a first model which includes a spatial correlation matrix related to frequency, a first parameter related to the frequency, and a second parameter related to the frequency and time; a second generating unit configured to generate acoustic signals emitted from a target sound source using a second model which includes a steering vector related to the frequency, and a third parameter related to the frequency and the time; and a determining unit configured to determine the first parameter, the second parameter and the third parameter so that the likelihood of the first parameter, the second parameter and the third parameter is maximized. The determining unit decomposes an inverse matrix of the matrix related to the frequency and the time into an inverse matrix of the matrix related to the frequency, and determines the first parameter, the second parameter and the third parameter so that the likelihood is maximized.

A processing apparatus includes one or more processors and one or more memories operatively coupled to the one or more processors. The one or more processors are configured to acquire a spectrogram of a sound signal. The one or more processors are also configured to perform a first convolution on the spectrogram at every predetermined width on one of a frequency axis or a time axis. The one or more processors are also configured to combine results of the first convolution to obtain one-dimensional first feature data. The one or more processors are also configured to perform at least one second convolution on the one-dimensional first feature data to obtain one-dimensional second feature data indicating a feature of the spectrogram.

Methods to reduce agent effort and improve customer experience quality through artificial intelligence. The Agent Assist tool provides contact centers with an innovative tool designed to reduce agent effort, improve quality and reduce costs by minimizing search and data entry tasks The Agent Assist tool is natively built and fully unified within the agent interface while keeping all data internally protected from third-party sharing.

Methods to reduce agent effort and improve customer experience quality through artificial intelligence. The Agent Assist tool provides contact centers with an innovative tool designed to reduce agent effort, improve quality and reduce costs by minimizing search and data entry tasks The Agent Assist tool is natively built and fully unified within the agent interface while keeping all data internally protected from third-party sharing.

Aspects disclosed herein generally related to a method and system for efficient blind source separation using a topological approach. The method and system comprise locating and separating the audio streams by constructing and simplifying contour tree in a built time-frequency smooth weighted histogram in the subsystems included. Thus, in one example, the audio streams can be separated and reproduced in a faster, more reliability, higher quality and more robust way.