Apparatus for processing an audio signal including an audio processing device configured to process, evaluate and modify an audio signal.

Apparatus for processing an audio signal including an audio processing device configured to process, evaluate and modify an audio signal.

A first device obtains, from the array, several audio signals and processes the audio signals to produce a speech signal and one or more ambient signals. The first device processes the ambient signals to produce a sound-object sonic descriptor that has metadata describing a sound object within an acoustic environment. The first device transmits, over a communication data link, the speech signal and the descriptor to a second electronic device that is configured to spatially reproduce the sound object using the descriptor mixed with the speech signal, to produce several mixed signals to drive several speakers.

A first device obtains, from the array, several audio signals and processes the audio signals to produce a speech signal and one or more ambient signals. The first device processes the ambient signals to produce a sound-object sonic descriptor that has metadata describing a sound object within an acoustic environment. The first device transmits, over a communication data link, the speech signal and the descriptor to a second electronic device that is configured to spatially reproduce the sound object using the descriptor mixed with the speech signal, to produce several mixed signals to drive several speakers.

Introduced here are approaches to training and then employing computer-implemented models designed to upsample discrete audio signals to higher sampling rates. Assume, for example, that a media production platform obtains a first discrete signal at a relatively low sampling rate. The relatively low sampling frequency may make the first discrete audio signal unsuitable for inclusion in media compilations, so the media production platform may attempt to improve its quality through upsampling. To accomplish this, the media production platform can apply a transform to the first discrete signal to produce a first magnitude spectrogram. Then, the media production platform can apply a computer-implemented model to the first magnitude spectrogram to produce a second magnitude spectrogram. Thereafter, the media production platform can apply an inverse transform to the second magnitude spectrogram to create a second discrete signal that has a higher sampling rate than the first discrete audio signal.

Introduced here are approaches to training and then employing computer-implemented models designed to upsample discrete audio signals to higher sampling rates. Assume, for example, that a media production platform obtains a first discrete signal at a relatively low sampling rate. The relatively low sampling frequency may make the first discrete audio signal unsuitable for inclusion in media compilations, so the media production platform may attempt to improve its quality through upsampling. To accomplish this, the media production platform can apply a transform to the first discrete signal to produce a first magnitude spectrogram. Then, the media production platform can apply a computer-implemented model to the first magnitude spectrogram to produce a second magnitude spectrogram. Thereafter, the media production platform can apply an inverse transform to the second magnitude spectrogram to create a second discrete signal that has a higher sampling rate than the first discrete audio signal.

An apparatus for generating a decoded two-channel signal includes: an audio processor for decoding an encoded two-channel signal to obtain a first set of first spectral portions; a parametric decoder for providing parametric data for a second set of second spectral portions and a two-channel identification identifying either a first or a second different two-channel representation for the second spectral portions; and a frequency regenerator for regenerating a second spectral portion depending on a first spectral portion of the first set of first spectral portions, the parametric data for the second portion and the two-channel identification for the second portion.

An apparatus for generating a decoded two-channel signal includes: an audio processor for decoding an encoded two-channel signal to obtain a first set of first spectral portions; a parametric decoder for providing parametric data for a second set of second spectral portions and a two-channel identification identifying either a first or a second different two-channel representation for the second spectral portions; and a frequency regenerator for regenerating a second spectral portion depending on a first spectral portion of the first set of first spectral portions, the parametric data for the second portion and the two-channel identification for the second portion.

There is provided methods and apparatuses for decoding and encoding of audio signals. In particular, a method for decoding includes receiving a waveform-coded signal having a spectral content corresponding to a subset of the frequency range above a cross-over frequency. The waveform-coded signal is interleaved with a parametric high frequency reconstruction of the audio signal above the cross-over frequency. In this way an improved reconstruction of the high frequency bands of the audio signal is achieved.

There is provided methods and apparatuses for decoding and encoding of audio signals. In particular, a method for decoding includes receiving a waveform-coded signal having a spectral content corresponding to a subset of the frequency range above a cross-over frequency. The waveform-coded signal is interleaved with a parametric high frequency reconstruction of the audio signal above the cross-over frequency. In this way an improved reconstruction of the high frequency bands of the audio signal is achieved.