Various embodiments herein provide a method for managing an audio based on a spectrogram. The method includes generating, by a transmitter device, the spectrogram of the audio. The method includes identifying a first spectrogram corresponding to vocals in the audio and a second spectrogram corresponding to music in the audio from the spectrogram of the audio, and extracting a music feature from the second spectrogram. The method includes transmitting a signal comprising the first spectrogram, the second spectrogram, the music feature and the audio to a receiver device. The method includes determining, by the receiver device, whether an audio drop is occurring in the received signal based on a parameter associated with the received signal. The method includes generating the audio using the first spectrogram, the second spectrogram, the music feature, in response to determining that the audio drop is occurring in the received signal.

Introduced here are computer programs and associated computer-implemented techniques for manipulating noisy audio signals to produce clean audio signals that are sufficiently high quality so as to be largely, if not entirely, indistinguishable from “rich” recordings generated by recording studios. When a noisy audio signal is obtained by a media production platform, the noisy audio signal can be manipulated to sound as if recording occurred with sophisticated equipment in a soundproof environment. Manipulation can be performed by a model that, when applied to the noisy audio signal, can manipulate its characteristics so as to emulate the characteristics of clean audio signals that are learned through training.

Introduced here are computer programs and associated computer-implemented techniques for manipulating noisy audio signals to produce clean audio signals that are sufficiently high quality so as to be largely, if not entirely, indistinguishable from “rich” recordings generated by recording studios. When a noisy audio signal is obtained by a media production platform, the noisy audio signal can be manipulated to sound as if recording occurred with sophisticated equipment in a soundproof environment. Manipulation can be performed by a model that, when applied to the noisy audio signal, can manipulate its characteristics so as to emulate the characteristics of clean audio signals that are learned through training.

A method and system for discovering and locating the source of unwanted communication origination in a communications network, the method comprising compiling a communication campaign database storing data of one or more communication campaigns along with automatically identified instances of those campaigns, and simultaneously or sequentially matching those instances against known communication traffic of a set of cooperating telecommunication carriers. The one or more communications campaigns include a grouping of related fingerprints and patterns that identify a sequence of characters, audio or video associated with instances of a same likely campaigns, either legitimate or illegitimate/fraudulent.

A method and system for discovering and locating the source of unwanted communication origination in a communications network, the method comprising compiling a communication campaign database storing data of one or more communication campaigns along with automatically identified instances of those campaigns, and simultaneously or sequentially matching those instances against known communication traffic of a set of cooperating telecommunication carriers. The one or more communications campaigns include a grouping of related fingerprints and patterns that identify a sequence of characters, audio or video associated with instances of a same likely campaigns, either legitimate or illegitimate/fraudulent.

Disclosed is a system for use in a rolling mill having: (a) a roll holder housing a plurality of rollers; (b) a smart module coupled to the roll holder, the smart module comprising: (1) a power source powering the smart module; (2) a microcontroller; (3) a motor, the motor, based on instructions from the microcontroller, controlling a position of the plurality of rollers by moving the roll holder; (4) one or more position sensors, the one or more position sensors detecting the position of the roll holder; and (5) a communication module, the communication module communicating with a central controlling computer to: (i) communicate the position of the roll holder and other sensor data to the central controlling computer, and (ii) receive instructions from the central controlling computer to control the position of the roll holder.

Disclosed is a system for use in a rolling mill having: (a) a roll holder housing a plurality of rollers; (b) a smart module coupled to the roll holder, the smart module comprising: (1) a power source powering the smart module; (2) a microcontroller; (3) a motor, the motor, based on instructions from the microcontroller, controlling a position of the plurality of rollers by moving the roll holder; (4) one or more position sensors, the one or more position sensors detecting the position of the roll holder; and (5) a communication module, the communication module communicating with a central controlling computer to: (i) communicate the position of the roll holder and other sensor data to the central controlling computer, and (ii) receive instructions from the central controlling computer to control the position of the roll holder.

A method for predicting the presence of a malady of the respiratory system in a subject comprising: operating at least one electronic processor to transform one or more sounds of the subject that are associated with the malady into corresponding one or more image representations of said sounds; applying said one or more representations to at least one pattern classifier trained to predict the presence of the malady; and operating said processor to predict the presence of the malady in the subject based on at least one output of the at least one pattern classifier.

A method of generating audio assets, comprising the steps of: receiving a plurality of input audio assets, converting each input audio asset into an input graphical representation, generating an input multi-channel image by stacking each input graphical representation in a separate channel of the image, feeding the input multi-channel image into a generative model to train the generative model and generate one or more output multi-channel images, each output multi-channel image comprising an output graphical representation, extracting the output graphical representations from each output multi-channel image and converting each output graphical representation into an output audio asset.

A method of generating audio assets, comprising the steps of: receiving a plurality of input audio assets, converting each input audio asset into an input graphical representation, generating an input multi-channel image by stacking each input graphical representation in a separate channel of the image, feeding the input multi-channel image into a generative model to train the generative model and generate one or more output multi-channel images, each output multi-channel image comprising an output graphical representation, extracting the output graphical representations from each output multi-channel image and converting each output graphical representation into an output audio asset.