Methods, systems, and computer program products for synchronizing audio signals captured by multiple independent devices during an audio event are described. Multiple recording devices, e.g. several smartphones, record the audio event. A computer system receives audio signals from the devices. The system determines a first delay between two audio signals based on cross-correlation of waveforms of the two audio signals. Subsequently, the system detects attacks that are present in each audio signal by computing the derivative of a respective envelope for each audio signal. The system determines a second delay between the two audio signals based on cross-correlation of attacks of the two audio signals. The system synchronizes the audio signals using the second delay upon determining that using the second delay improves sound quality over using the first delay.

Methods, systems, and computer program products for synchronizing audio signals captured by multiple independent devices during an audio event are described. Multiple recording devices, e.g. several smartphones, record the audio event. A computer system receives audio signals from the devices. The system determines a first delay between two audio signals based on cross-correlation of waveforms of the two audio signals. Subsequently, the system detects attacks that are present in each audio signal by computing the derivative of a respective envelope for each audio signal. The system determines a second delay between the two audio signals based on cross-correlation of attacks of the two audio signals. The system synchronizes the audio signals using the second delay upon determining that using the second delay improves sound quality over using the first delay.

Communication terminal includes a first microphone system, a second microphone system, and a noise reduction processing unit (NRPU). The NRPU receives a primary signal from the first microphone system and a secondary signal from the second microphone system. The NRPU dynamically identify an optimal transfer function of a correction filter which can be applied to the secondary signal provided by the second microphone system to obtain a correction signal. The correction signal is subtracted from the primary signal to obtain a remainder signal which approximates a signal of interest contained within the primary signal.

Communication terminal includes a first microphone system, a second microphone system, and a noise reduction processing unit (NRPU). The NRPU receives a primary signal from the first microphone system and a secondary signal from the second microphone system. The NRPU dynamically identify an optimal transfer function of a correction filter which can be applied to the secondary signal provided by the second microphone system to obtain a correction signal. The correction signal is subtracted from the primary signal to obtain a remainder signal which approximates a signal of interest contained within the primary signal.

Communication terminal includes a first microphone system, a second microphone system, and a noise reduction processing unit (NRPU). The NRPU receives a primary signal from the first microphone system and a secondary signal from the second microphone system. The NRPU dynamically identify an optimal transfer function of a correction filter which can be applied to the secondary signal provided by the second microphone system to obtain a correction signal. The correction signal is subtracted from the primary signal to obtain a remainder signal which approximates a signal of interest contained within the primary signal.

Communication terminal includes a first microphone system, a second microphone system, and a noise reduction processing unit (NRPU). The NRPU receives a primary signal from the first microphone system and a secondary signal from the second microphone system. The NRPU dynamically identify an optimal transfer function of a correction filter which can be applied to the secondary signal provided by the second microphone system to obtain a correction signal. The correction signal is subtracted from the primary signal to obtain a remainder signal which approximates a signal of interest contained within the primary signal.

A method for improving speech signal intelligibility is performed at a device. A speech signal is obtained. A correspondence between the speech signal and a respective user group among different user groups having distinct voice characteristics is identified. Pre-encoding signal augmentation is performed on the speech signal with a respective pre-augmentation filtering coefficient that corresponds to the respective user group to obtain a group-specific pre-augmented speech signal. The device encodes the pre-augmented speech signal for subsequent transmission through the voice communication channel. An encoded version of the pre-augmented speech signal has reduced loss of signal quality as compared to an encoded version of the speech signal that is obtained without the pre-encoding signal augmentation.

The present application discloses and describes neurostimulation systems and methods that include, among other features, (i) neural stimulation through audio with dynamic modulation characteristics, (ii) audio content serving and creation based on modulation characteristics, (iii) extending audio tracks while avoiding audio discontinuities, and (iv) non-auditory neurostimulation and methods, including non-auditory neurostimulation for anesthesia recovery.

The present application discloses and describes neurostimulation systems and methods that include, among other features, (i) neural stimulation through audio with dynamic modulation characteristics, (ii) audio content serving and creation based on modulation characteristics, (iii) extending audio tracks while avoiding audio discontinuities, and (iv) non-auditory neurostimulation and methods, including non-auditory neurostimulation for anesthesia recovery.

Techniques are disclosed relating to implementing audio techniques for real-time audio generation. For example, a music generator system may generate new music content from playback music content based on different parameter representations of an audio signal. In some cases, an audio signal can be represented by both a graph of the signal (e.g., an audio signal graph) relative to time and a graph of the signal relative to beats (e.g., a signal graph). The signal graph is invariant to tempo, which allows for tempo invariant modification of audio parameters of the music content in addition to tempo variant modifications based on the audio signal graph.