A voice input apparatus includes first to third microphones and a controller. The first microphone collects a voice at a first position outside an ear canal of a speaker, and outputs a first input voice signal. The second microphone collects a voice at a second position outside the ear canal of the speaker and closer to a mouth of the speaker than the first position, and outputs a second input voice signal. The third microphone collects a voice inside the ear canal of the speaker, and outputs a third input voice signal. The controller detects a sound pressure of the first input voice signal, sets reflection degrees of the second and third input voice signals according to the detected sound pressure, and generates an output voice signal including at least one of the second and third input voice signals based on the reflection degrees.

Apparatuses, systems, and techniques are presented to upsample audio. In at least one embodiment, one or more neural networks are used to determine one or more second frequencies of one or more audio signals based, at least in part, on only one or more first frequencies of the one or more audio signals

Apparatuses, systems, and techniques are presented to upsample audio. In at least one embodiment, one or more neural networks are used to determine one or more second frequencies of one or more audio signals based, at least in part, on only one or more first frequencies of the one or more audio signals

Background noise estimators and methods are disclosed for estimating background noise in an audio signal. Some methods include obtaining at least one parameter associated with an audio signal segment, such as a frame or part of a frame, based on a first linear prediction gain, calculated as a quotient between a residual signal from a 0th-order linear prediction and a residual signal from a 2nd-order linear prediction for the audio signal segment. A second linear prediction gain is calculated as a quotient between a residual signal from a 2nd-order linear prediction and a residual signal from a 16th-order linear prediction for the audio signal segment. Whether the audio signal segment comprises a pause is determined based at least on the obtained at least one parameter; and a background noise estimate is updated based on the audio signal segment when the audio signal segment comprises a pause.

Background noise estimators and methods are disclosed for estimating background noise in an audio signal. Some methods include obtaining at least one parameter associated with an audio signal segment, such as a frame or part of a frame, based on a first linear prediction gain, calculated as a quotient between a residual signal from a 0th-order linear prediction and a residual signal from a 2nd-order linear prediction for the audio signal segment. A second linear prediction gain is calculated as a quotient between a residual signal from a 2nd-order linear prediction and a residual signal from a 16th-order linear prediction for the audio signal segment. Whether the audio signal segment comprises a pause is determined based at least on the obtained at least one parameter; and a background noise estimate is updated based on the audio signal segment when the audio signal segment comprises a pause.

A method for speech equalization, comprising the steps of receiving an input audio signal, processing said input audio signal in dependence on frequency and to providing an equalized electric audio signal according to an equalization function, wherein said equalization function comprises at least an actuator part configured to dynamically applying a compensation filter to the received input signal and dynamically applying a transparent filter to the received input signal, and further transmitting an output signal perceivable by a user as sound representative of said electric acoustic input signal or a processed version thereof.

An apparatus for processing an audio signal includes an audio signal analyzer and a filter. The audio signal analyzer is configured to analyze an audio signal to determine a plurality of noise suppression filter values for a plurality of bands of the audio signal, wherein the analyzer is configured to determine a noise suppression filter value so that a noise suppression filter value is greater than or equal to a minimum noise suppression filter value and so that the minimum noise suppression value depends on a characteristic of the audio signal. The filter is configured for filtering the audio signal, wherein the filter is adjusted based on the noise suppression filter values.

An apparatus for processing an audio signal includes an audio signal analyzer and a filter. The audio signal analyzer is configured to analyze an audio signal to determine a plurality of noise suppression filter values for a plurality of bands of the audio signal, wherein the analyzer is configured to determine a noise suppression filter value so that a noise suppression filter value is greater than or equal to a minimum noise suppression filter value and so that the minimum noise suppression value depends on a characteristic of the audio signal. The filter is configured for filtering the audio signal, wherein the filter is adjusted based on the noise suppression filter values.

In an audio encoder, for audio content received in a source audio format, default gains are generated based on a default dynamic range compression (DRC) curve, and non-default gains are generated for a non-default gain profile. Based on the default gains and non-default gains, differential gains are generated. An audio signal comprising the audio content, the default DRC curve, and differential gains is generated. In an audio decoder, the default DRC curve and the differential gains are identified from the audio signal. Default gains are re-generated based on the default DRC curve. Based on the combination of the re-generated default gains and the differential gains, operations are performed on the audio content extracted from the audio signal.

In an audio encoder, for audio content received in a source audio format, default gains are generated based on a default dynamic range compression (DRC) curve, and non-default gains are generated for a non-default gain profile. Based on the default gains and non-default gains, differential gains are generated. An audio signal comprising the audio content, the default DRC curve, and differential gains is generated. In an audio decoder, the default DRC curve and the differential gains are identified from the audio signal. Default gains are re-generated based on the default DRC curve. Based on the combination of the re-generated default gains and the differential gains, operations are performed on the audio content extracted from the audio signal.