Abstract: A device includes a memory configured to store a collection of sets of weights, each of the sets of weights representing a respective media segment. The device also includes one or more processors configured to generate data representing the detected first input speech segment and to pass the data representing the detected first input speech segment into a collection of memory units. Each memory unit of the collection of memory units includes a set of weights from the collection of sets of weights. The one or more processors are also configured to generate a first estimate of an associated media segment that represents the detected first input speech segment. The associated media segment corresponds to a first memory unit in the collection of memory units.

Abstract: Systems and techniques are described herein for encoding and/or decoding audio information. For example, a process can process an input audio segment to generate a representation of the input audio segment, and can compare the representation of the input audio segment to representations stored in a memory. The representations represent a plurality of audio segments. The process can determine, based on the comparison, target representation(s) of target audio segment(s) from the representations stored in the memory. The process can determine one or more indices associated with the target audio segment(s). The process can then packetize the one or more indices and transmit the one or more packetized indices (e.g., to a decoder configured to decode the packetized indices).

Abstract: A device includes one or more processors configured to input one or more segments of an input media stream into a feature extractor. The one or more processors are further configured to pass an output of the feature extractor into an utterance classifier to produce at least one representation of at least one utterance class of a plurality of utterance classes. The one or more processors are further configured to pass the output of the feature extractor and the at least one representation into a segment matcher to produce a media output segment identifier.

Abstract: Methods, systems, and devices for encoding are described. A device, which may be otherwise known as user equipment (UE), may support standards-compatible audio encoding (e.g., speech encoding) using a pre-encoded database. The device may receive a digital representation of an audio signal and identify, based on receiving the digital representation of the audio signal, a database that is pre-encoded according to a coding standard and that includes a quantity of digital representations of other audio signals. The device may encode the digital representation of the audio signal using a machine learning scheme and information from the database pre-encoded according to the coding standard. The device may generate a bitstream of the digital representation that is compatible with the coding standard based on encoding the digital representation of the audio signal, and output a representation of the bitstream.

Abstract: Techniques are described for coding audio signals. For example, using a neural network, a residual signal is generated for a sample of an audio signal based on inputs to the neural network. The residual signal is configured to excite a long-term prediction filter and/or a short-term prediction filter. Using the long-term prediction filter and/or the short-term prediction filter, a sample of a reconstructed audio signal is determined. The sample of the reconstructed audio signal is determined based on the residual signal generated using the neural network for the sample of the audio signal.

Abstract: A device includes an encoder configured to determine, during a first period, that a first audio signal is a leading signal and that a second audio signal is a lagging signal. The encoder is also configured to generate a first frame of at least one encoded signal based on a first modified version of the second audio signal that is generated by adjusting the second audio signal based on a first mismatch value. The encoder is configured to determine, during a second period, that the first audio signal is the leading signal and that the second audio signal is the lagging signal. The encoder is configured to generate a second frame of the at least one encoded signal based on a second modified version of the second audio signal that is generated by adjusting the second audio signal based on the first mismatch value and a second mismatch value.

Abstract: Methods, systems, and devices for encoding are described. A device, which may be otherwise known as user equipment (UE), may support standards-compatible audio encoding (e.g., speech encoding) using a pre-encoded database. The device may receive a digital representation of an audio signal and identify, based on receiving the digital representation of the audio signal, a database that is pre-encoded according to a coding standard and that includes a quantity of digital representations of other audio signals. The device may encode the digital representation of the audio signal using a machine learning scheme and information from the database pre-encoded according to the coding standard. The device may generate a bitstream of the digital representation that is compatible with the coding standard based on encoding the digital representation of the audio signal, and output a representation of the bitstream.

Abstract: Techniques are described for coding audio signals. For example, using a neural network, a residual signal is generated for a sample of an audio signal based on inputs to the neural network. The residual signal is configured to excite a long-term prediction filter and/or a short-term prediction filter. Using the long-term prediction filter and/or the short-term prediction filter, a sample of a reconstructed audio signal is determined. The sample of the reconstructed audio signal is determined based on the residual signal generated using the neural network for the sample of the audio signal.

Abstract: A method includes decoding a low-band portion of an encoded mid channel to generate a decoded low-band mid channel. The method also includes filtering the decoded low-band mid channel according to one or more filter coefficients to generate a low-band filtered mid channel. The method also includes generating an inter-channel predicted signal based on the low-band filtered mid channel and the inter-channel prediction gain. The method further includes generating a low-band left channel and a low-band right channel based on an up-mix factor, the decoded low-band mid channel, and the inter-channel predicted signal.

Abstract: A method includes receiving, at an audio encoder, multiple streams of audio data. The method includes assigning a priority to each stream of the multiple streams and determining, based on the priority of each stream of the multiple streams, a permutation sequence for encoding of the multiple streams. The method also includes encoding at least a portion of each stream of the multiple streams according to the permutation sequence.

Abstract: A method of capturing video includes instructing a microphone to initiate an audio scan of different areas of interest to detect audio activity. The method also includes receiving a feedback signal from the microphone in response to initiating the audio scan. The feedback signal indicates audio activity in a particular area of interest. The method further includes adjusting targeting characteristics of a device based on the feedback signal to focus the device on the particular area of interest.

Abstract: A method and an apparatus for estimating speech signal in split-domain is disclosed. The method includes performing LP analysis on a noisy speech signal to generate a first plurality of LPC and a first residual signal. The method also includes estimating speech LPC spectrum to generate cleaned LPC. The method further includes estimating speech residual spectrum to generate cleaned residual signal. The method also includes synthesizing output signals based on the cleaned LPC and the cleaned residual signal.

Abstract: Certain aspects of the present disclosure provide an apparatus for wireless communication. The apparatus generally includes an interface configured to obtain at least one voice packet from an access point (AP), wherein the at least one voice packet is obtained during one or more service periods (SPs) of a target wake time (TWT) protocol, and a processing system configured to process the at least one voice packet obtained during the one or more SPs.

Abstract: A device includes an encoder configured to determine, during a first period, that a first audio signal is a leading signal and that a second audio signal is a lagging signal. The encoder is also configured to generate a first frame of at least one encoded signal based on a first modified version of the second audio signal that is generated by adjusting the second audio signal based on a first mismatch value. The encoder is configured to determine, during a second period, that the first audio signal is the leading signal and that the second audio signal is the lagging signal. The encoder is configured to generate a second frame of the at least one encoded signal based on a second modified version of the second audio signal that is generated by adjusting the second audio signal based on the first mismatch value and a second mismatch value.

Abstract: A device includes an encoder configured to determine, during a first period, that a first audio signal is a leading signal and that a second audio signal is a lagging signal. The encoder is also configured to generate a first frame of at least one encoded signal based on a first modified version of the second audio signal that is generated by adjusting the second audio signal based on a first mismatch value. The encoder is configured to determine, during a second period, that the first audio signal is the leading signal and that the second audio signal is the lagging signal. The encoder is configured to generate a second frame of the at least one encoded signal based on a second modified version of the second audio signal that is generated by adjusting the second audio signal based on the first mismatch value and a second mismatch value.

Abstract: A method includes decoding a low-band portion of an encoded mid channel to generate a decoded low-band mid channel. The method also includes filtering the decoded low-band mid channel according to one or more filter coefficients to generate a low-band filtered mid channel. The method also includes generating an inter-channel predicted signal based on the low-band filtered mid channel and the inter-channel prediction gain. The method further includes generating a low-band left channel and a low-band right channel based on an up-mix factor, the decoded low-band mid channel, and the inter-channel predicted signal.

Abstract: A method includes decoding a low-band portion of an encoded mid channel to generate a decoded low-band mid channel. The method also includes filtering the decoded low-band mid channel according to one or more filter coefficients to generate a low-band filtered mid channel. The method also includes generating an inter-channel predicted signal based on the low-band filtered mid channel and the inter-channel prediction gain. The method further includes generating a low-band left channel and a low-band right channel based on an up-mix factor, the decoded low-band mid channel, and the inter-channel predicted signal.

Abstract: A method and an apparatus for estimating speech signal in split-domain is disclosed. The method includes performing LP analysis on a noisy speech signal to generate a first plurality of LPC and a first residual signal. The method also includes estimating speech LPC spectrum to generate cleaned LPC. The method further includes estimating speech residual spectrum to generate cleaned residual signal. The method also includes synthesizing output signals based on the cleaned LPC and the cleaned residual signal.

Abstract: A method of capturing video includes instructing a microphone to initiate an audio scan of different areas of interest to detect audio activity. The method also includes receiving a feedback signal from the microphone in response to initiating the audio scan. The feedback signal indicates audio activity in a particular area of interest. The method further includes adjusting targeting characteristics of a device based on the feedback signal to focus the device on the particular area of interest.

Abstract: A method of capturing audio includes initiating capture, at a laser microphone, of first audio of an area of interest. The first audio is captured while the laser microphone is focused on a first target surface associated with the area of interest. The method also includes generating adjustment parameters based on a feedback signal to adjust targeting characteristics of the laser microphone. The method further includes adjusting the targeting characteristics of the laser microphone based on the adjustment parameters to focus the laser microphone on a second target surface associated with the area of interest. The method also includes initiating capture, at the laser microphone, of second audio of the area of interest in response to adjusting the targeting characteristics. The second audio has an audio quality that is greater than the first audio.