A communications enhancement computing system for connecting multiple users while balancing audio noise comprises a memory, a network interface device and a processor configured for applying signal processing techniques to a dataset of environmental sounds to extract sound characteristics of said sounds, executing a first deep neural network algorithm to train a first machine learning classification model for classifying sounds by label, executing a second deep neural network algorithm to train a second machine learning classification model for classifying sounds by environment, receiving, via the communications network, input sounds from a user and executing the first and second classification models to classify the input sounds by label and by environment, defining a sound softening technique configured to apply to audio from the user, wherein said sound softening technique is based on the environment and label, and executing the sound softening techniques to a continuous audio feed from the user.

Noise abatement within a signal stream containing unwanted signal referred to as noise is performed by acquiring a digitized noise signal and using a digital processor circuit to subdivide the acquired noise signal into different frequency band segments and thereby generate a plurality of segmented noise signals. Then individually for each segmented noise signal, the processor shifts in time the segmented noise signal by an amount dependent on a selected frequency of the segmented noise signal to produce a plurality of shifted segmented noise signals. The precise time shift applied to each noise segment considers the frequency content of the segment and the system processing time. Individually for each segmented noise signal, amplitude scaling is applied. The shifted and amplitude-scaled segmented noise signals are then combined to form a composite anti-noise signal which is output into the signal stream to abate the noise through destructive interference.

A sensor is configured to infer a rotational speed of a tire of a vehicle. A frequency generator is configured to synthesize frequencies of a tire cavity resonance according to the rotational speed of the tire to generate a sense signal. An active noise control filter is configured to generate an antinoise signal from the sense signal. A loudspeaker configured to convert the antinoise signal into antinoise and to radiate the antinoise to a listening position. The antinoise signal is configured so that the antinoise reduces sound of the tire cavity resonance at the listening position.

A noise cancellation technique is presented with improved frequency resolution. The method includes: acquiring a digitized noise signal from an environment in which the audio signal stream is present; receiving a data sample from the digitized noise signal; appending one or more additional samples to the data sample to form a series of samples, where magnitude for each of the one or more additional samples is substantially zero; computing a frequency domain representation of the series of samples in the frequency domain; shifting the frequency domain representation of the series of samples in time using the digital processor circuit, thereby producing a shifted frequency domain representation of the series of samples; converting the shifted frequency domain representation of the series of samples to time domain to form a portion of an anti-noise signal; and outputting the anti-noise signal into the audio signal stream to abate the noise through destructive interference.

An embodiment for creating a virtual ambient workstation is provided. The embodiment may include receiving a request to reserve an ambient space for a determined time period. The embodiment may also include identifying one or more workstations that are occupied by one or more other individuals. The embodiment may further include identifying combined vocal-fold sound patterns provided to a cognitive system based on the identified one or more workstations occupied by the one or more other individuals. The embodiment may also include evaluating data obtained from the one or more workstations and the combined vocal-fold sound patterns. The embodiment may further include generating an ambient noise remediation sound using an acoustic beam system. The embodiment may also include training the cognitive system. The embodiment may further include determining whether a level of ambient sound is sufficient and providing feedback to the cognitive system through machine learning.

Embodiments include a method of reducing echo in an audio system comprising a microphone, an acoustic echo canceller (AEC), and at least one processor, the method comprising receiving, by the at least one processor, an audio signal detected by the microphone; deploying, by the at least one processor, a microphone lobe towards a first location associated with the detected audio signal; obtaining, by the at least one processor, one or more AEC parameters for the first location, the one or more AEC parameters being stored in a memory in communication with the at least one processor; initializing, by the at least one processor, the AEC using the one or more AEC parameters; and generating, by the at least one processor, an echo-cancelled output signal using the initialized AEC and based on the detected audio signal and a reference signal provided to the AEC.

Systems and methods are provided for generating destructive interference signals for use in active noise cancellation in an interior setting of an urban environment. The system employs a combination of conventional ANC and predictive state estimation to generate destruction interference sound waves using a window pane to counteract urban noises.

In at least one embodiment, a system for performing active noise cancelation in a vehicle is provided. The system includes an adaptive filter and an adjustment controller. The adaptive filter is configured to control a loudspeaker to generate anti-noise to cancel undesired noise in the vehicle. The adjustment controller is programmed to receive a reference signal from one or more accelerometers. Each reference signal includes a frequency that is indicative of a force acting on a portion of the vehicle. The adjustment controller is programmed to compare the frequency to a predetermined frequency threshold and to control a first filter to filter to the frequency based on the comparison of the frequency to the predetermined frequency threshold. The adjustment controller is programmed to transmit a filtered reference signal to the adaptive filter to generate the anti-noise without influence of the frequency of the reference signal.

Methods, systems, computer-readable media, and apparatuses for audio signal processing are presented. Some configurations include determining that first audio activity in at least one microphone signal is voice activity; determining whether the voice activity is voice activity of a participant in an application session active on a device; based at least on a result of the determining whether the voice activity is voice activity of a participant in the application session, generating an antinoise signal to cancel the first audio activity; and by a loudspeaker, producing an acoustic signal that is based on the antinoise signal. Applications relating to shared virtual spaces are described.

In some implementations, an output of a first channel of an echo cancellation variable filter having an output of a first microphone output from a second speaker as an input is added to an output of a second microphone. An echo cancellation coefficient updating unit updates the filter coefficient of the first channel so that the error that is the output of a second adder is minimized. Using the output of the second channel that uses the output of a sound source device output from the first speaker as an input and shares the filter coefficient with the first channel as a reference signal, and the output of the second microphone as an error, the noise cancellation coefficient updating unit updates the filter coefficient of the noise cancellation variable filter that generates a noise-canceling sound to be output from the output of the sound source device to the second speaker.