In some implementations, a user device may receive input that triggers transmission of information via sound. The user device may select an audio clip based on a setting associated with the device, and may modify a digital representation of the selected audio clip using an encoding algorithm and based on data associated with a user of the device. The user device may transmit, to a remote server, an indication of the selected audio clip, an indication of the encoding algorithm, and the data associated with the user. The user device may use a speaker to play audio, based on the modified digital representation, for recording by other devices. Accordingly, the user device may receive, from the remote server and based on the speaker playing the audio, a confirmation that users associated with the other devices have performed an action based on the data associated with the user of the device.

A method, system, and computer readable medium for decomposing an audio signal into different isolated sources. The techniques and mechanisms convert an audio signal into K input spectrogram fragments. The fragments are sent into a deep neural network to isolate for different sources. The isolated fragments are then combined to form full isolated source audio signals.

A method, system, and computer readable medium for decomposing an audio signal into different isolated sources. The techniques and mechanisms convert an audio signal into K input spectrogram fragments. The fragments are sent into a deep neural network to isolate for different sources. The isolated fragments are then combined to form full isolated source audio signals.

Described here are systems and methods for generating sound maps that depict the spatiotemporal distribution of sounds occurring within a subject. To this end, the sound maps may be four-dimensional (“4D”) maps that depict the three-dimensional spatial distribution of acoustic sources within a subject, and also the temporal evolution of sounds measured at those acoustic sources over a duration of time.

In some implementations, a user device may receive input that triggers transmission of information via sound. The user device may select an audio clip based on a setting associated with the device, and may modify a digital representation of the selected audio clip using an encoding algorithm and based on data associated with a user of the device. The user device may transmit, to a remote server, an indication of the selected audio clip, an indication of the encoding algorithm, and the data associated with the user. The user device may use a speaker to play audio, based on the modified digital representation, for recording by other devices. Accordingly, the user device may receive, from the remote server and based on the speaker playing the audio, a confirmation that users associated with the other devices have performed an action based on the data associated with the user of the device.

A method, system, and computer readable medium for decomposing an audio signal into different isolated sources. The techniques and mechanisms convert an audio signal into K input spectrogram fragments. The fragments are sent into a deep neural network to isolate for different sources. The isolated fragments are then combined to form full isolated source audio signals.

Disclosed is a method, an apparatus, and a device for transient noise detection. The method includes: obtaining an audio frame signal having a preset duration; performing wavelet decomposition on a first audio frame signal to obtain a first wavelet decomposition signal corresponding to the first audio frame signal; determining a first reference audio intensity value of a first sub-wavelet decomposition signal according to reference audio intensity values of all samples in the first sub-wavelet decomposition signal; determining energy distribution information of the first wavelet decomposition signal according to first reference audio intensity values of all sub-wavelet decomposition signals in the first wavelet decomposition signal; and determining a probability that the first audio frame signal is transient noise according to the energy distribution information of the first wavelet decomposition signal.

A method, system, and computer readable medium for decomposing an audio signal into different isolated sources. The techniques and mechanisms convert an audio signal into K input spectrogram fragments. The fragments are sent into a deep neural network to isolate for different sources. The isolated fragments are then combined to form full isolated source audio signals.

A method and apparatus for detecting a valid voice signal and a non-transitory computer readable storage medium are provided. A first audio signal including at least one audio frame signal is obtained. Multiple wavelet decomposition signals respectively corresponding to the at least one audio frame signal are obtained. A wavelet signal sequence is obtained by combining the multiple wavelet decomposition signals. A maximum value and a minimum value among audio intensity values of all sample points are obtained, and a first audio intensity threshold is determined according to the maximum value and the minimum value. Sample points each having an audio intensity value greater than the first audio intensity threshold in the wavelet signal sequence are obtained, and a signal of sample points in the first audio signal corresponding to the sample points each having an audio intensity value greater than the first audio intensity threshold is determined as the valid voice signal.

A method, system, and computer readable medium for decomposing an audio signal into different isolated sources. The techniques and mechanisms convert an audio signal into K input spectrogram fragments. The fragments are sent into a deep neural network to isolate for different sources. The isolated fragments are then combined to form full isolated source audio signals.