In general, disclosed is a device that includes one or more processors, coupled to the memory, configured to perform an energy analysis with respect to one or more audio objects, in the ambisonics domain, in the first time segment. The one or more processors are also configured to perform a similarity measure between the one or more audio objects, in the ambisonics domain, in the first time segment, and the one or more audio objects, in the ambisonics domain, in the second time segment. In addition, the one or more processors are configured to perform a reorder of the one or more audio objects, in the ambisonics domain, in the first time segment with the one or more audio objects, in the ambisonics domain, in the second time segment, to generate one or more reordered audio objects in the first time segment.

Quantizing speech model parameters includes, for each of multiple vectors of quantized excitation strength parameters, determining first and second errors between first and second elements of a vector of excitation strength parameters and, respectively, first and second elements of the vector of quantized excitation strength parameters, and determining a first energy and a second energy associated with, respectively, the first and second errors. First and second weights for, respectively, the first error and the second error, are determined and are used to produce first and second weighted errors, which are combined to produce a total error. The total errors of each of the multiple vectors of quantized excitation strength parameters are compared and the vector of quantized excitation strength parameters that produces the smallest total error is selected to represent the vector of excitation strength parameters.

It is inter alia disclosed an apparatus comprising: a table comprising a plurality of sub vectors, wherein each entry of the table is a subvector and each subvector have vector components which are the same as vector components of one or more basis code vectors; and a further table wherein an entry of the further table comprises a first pointer pointing to a sub vector in the table and a second pointer pointing to a subvector in the table, wherein the first pointer and the second pointer are arranged in the further table such that when vector components of the sub vector pointed to by the first pointer are combined with vector components of the sub vector pointed to by the second pointer a basis code vector is formed.

It is inter alia disclosed to determine a first quantized representation of an input vector, and to determine a second quantized representation of the input vector based on a codebook depending on the first quantized representation.

An X-ray diagnosis apparatus according to an embodiment includes a calculating unit and a control unit. The calculating unit that calculates an angle between a specified position specified in an ultrasonic image generated through transmission and reception of ultrasonic waves by an ultrasound probe and a predetermined position in a radiographic space where a subject is radiographed based on information on a relative position between the radiographic space and a scanning space where the subject is scanned by the ultrasound probe. The control unit that controls an arm to move so that the subject is radiographed at the angle calculated by the calculating unit.

A method comprising: receiving lattice vector quantised parameter data, the parameter data representing at least one audio signal; determining within the data at least one bit error; and controlling the decoding of the data to generate an audio signal based on the determining of the bit error.

In general, disclosed is a device that includes one or more processors, coupled to the memory, configured to perform an energy analysis with respect to one or more audio objects, in the ambisonics domain, in the first time segment. The one or more processors are also configured to perform a similarity measure between the one or more audio objects, in the ambisonics domain, in the first time segment, and the one or more audio objects, in the ambisonics domain, in the second time segment. In addition, the one or more processors are configured to perform a reorder of the one or more audio objects, in the ambisonics domain, in the first time segment with the one or more audio objects, in the ambisonics domain, in the second time segment, to generate one or more reordered audio objects in the first time segment.

Methods, systems and apparatus, including computer programs encoded on computer storage media. One of the methods includes receiving an audio waveform that includes a respective audio sample for each of a plurality of time steps, processing the audio waveform using an encoder neural network to generate a plurality of feature vectors representing the audio waveform, generating a respective coded representation of each of the plurality of feature vectors using a plurality of vector quantizers that are each associated with a respective codebook of code vectors, wherein the respective coded representation of each feature vector identifies a plurality of code vectors, including a respective code vector from the codebook of each vector quantizer, that define a quantized representation of the feature vector, and generating a compressed representation of the audio waveform by compressing the respective coded representation of each of the plurality of feature vectors.

A device for injecting fuel into the combustion chamber of an internal combustion engine comprising at least one injector. The injector includes an injector body, a high-pressure accumulator integrated into the injector body, an injection nozzle, a high-pressure bore, and a feed bore. The injection nozzle defines a nozzle chamber and has a nozzle needle configured to be guided in an axially movable manner and that is surrounded by the nozzle chamber. The high-pressure bore is connected to the high-pressure accumulator and the nozzle chamber. The feed bore is configured to feed high-pressure fuel to the high-pressure accumulator. Additionally, the feed bore has a lance connection positioned laterally on the injector body, is formed as a bore separate from the high-pressure bore, and connects the lance connection directly to the high-pressure accumulator.

Methods, systems and apparatus, including computer programs encoded on computer storage media. According to one aspect, there is provided a method comprising: receiving a new input; processing the new input using an encoder neural network to generate a feature vector representing the new input; and generating a coded representation of the feature vector using a sequence of vector quantizers that are each associated with a respective codebook of code vectors, wherein the coded representation of the feature vector identifies a plurality of code vectors, including a respective code vector from the codebook of each vector quantizer, that define a quantized representation of the feature vector.