Abstract:
In general, techniques are described for performing an interpolation with respect to decomposed versions of a sound field. A device comprising one or more processors may be configured to perform the techniques. The processors may be configured to obtain decomposed interpolated spherical harmonic coefficients for a time segment by, at least in part, performing an interpolation with respect to a first decomposition of a first plurality of spherical harmonic coefficients and a second decomposition of a second plurality of spherical harmonic coefficients.
Abstract:
In general, techniques are described for coding of vectors decomposed from higher order ambisonic coefficients. A device comprising a processor and a memory may perform the techniques. The processor may be configured to obtain from a bitstream data indicative of a plurality of weight values that represent a vector that is included in a decomposed version of the plurality of HOA coefficients. Each of the weight values may correspond to a respective one of a plurality of weights in a weighted sum of code vectors that represents the vector and that includes a set of code vectors. The processor may further be configured to reconstruct the vector based on the weight values and the code vectors. The memory may be configured to store the reconstructed vector.
Abstract:
A device for processing audio data obtains data representing quantized versions of a set of one or more spatial vectors. Each respective spatial vector of the set of spatial vectors corresponds to a respective audio signal of the set of audio signals. Each of the spatial vectors is in a Higher-Order Ambisonics (HOA) domain and is computed based on a set of loudspeaker locations. The device inverse quantizes the quantized versions of the spatial vectors.
Abstract:
In general, techniques are described for coding of vectors decomposed from higher-order ambisonic coefficients. A device comprising a memory and a processor may perform the techniques. The memory may be configured to store audio data. The processor may be configured to determine whether to perform vector dequantization or scalar dequantization with respect to a decomposed version of the plurality of HOA coefficients.
Abstract:
In general, techniques are described for obtaining audio rendering information in a bitstream. A device configured to render higher order ambisonic coefficients comprising a processor and a memory may perform the techniques. The processor may be configured to obtain sparseness information indicative of a sparseness of a matrix used to render the higher order ambisonic coefficients to a plurality of speaker feeds. The memory may be configured to store the sparseness information.
Abstract:
In general, techniques are described for grouping audio objects into clusters. In some examples, a device for audio signal processing comprises a cluster analysis module configured to, based on a plurality of audio objects, produce a first grouping of the plurality of audio objects into L clusters, wherein the first grouping is based on spatial information from at least N among the plurality of audio objects and L is less than N. The device also includes an error calculator configured to calculate an error of the first grouping relative to the plurality of audio objects, wherein the error calculator is further configured to, based on the calculated error, produce a plurality L of audio streams according to a second grouping of the plurality of audio objects into L clusters that is different from the first grouping.
Abstract:
In general, techniques are described for obtaining an indication of whether spherical harmonic coefficients are representative of a synthetic audio object. In accordance with the techniques, a device comprising one or more processors may be configured to obtain an indication of whether spherical harmonic coefficients representative of a sound field are generated from a synthetic audio object.
Abstract:
In general, techniques are described for compensating for loudspeaker positions using hierarchical three-dimensional (3D) audio coding. An apparatus comprising or more processors may perform the techniques. The processors may be configured to perform a first transform that is based on a spherical wave model on a first set of audio channel information for a first geometry of speakers to generate a first hierarchical set of elements that describes a sound field. The processors may further be configured to perform a second transform in a frequency domain on the first hierarchical set of elements to generate a second set of audio channel information for a second geometry of speakers.
Abstract:
In general, techniques are described for coding of spherical harmonic coefficients representative of a three dimensional soundfield. A device comprising a memory and one or more processors may be configured to perform the techniques. The memory may be configured to store a plurality of spherical harmonic coefficients. The one or more processors may be configured to perform an energy analysis with respect to the plurality of spherical harmonic coefficients to determine a reduced version of the plurality of spherical harmonic coefficients.