Abstract: A method of encoding an audio signal and an encoder and a method of decoding an audio signal and a decoder are provided. The method of encoding an audio signal includes outputting a decoded signal by using a bitstream that encodes an audio signal, separating the decoded signal into a low-band signal and a high-band signal by using a sound source separator, upsampling the low-band signal, upsampling the high-band signal, and restoring the audio signal by synthesizing the upsampled low-band signal with the upsampled high-band signal, wherein the bitstream is generated by encoding a superimposed signal in which a signal in a high frequency band of the audio signal is superimposed on a low frequency band of the audio signal.

Abstract: Provided is an encoding apparatus for integrally encoding and decoding a speech signal and a audio signal, and may include: an input signal analyzer to analyze a characteristic of an input signal; a stereo encoder to down mix the input signal to a mono signal when the input signal is a stereo signal, and to extract stereo sound image information; a frequency band expander to expand a frequency band of the input signal; a sampling rate converter to convert a sampling rate; a speech signal encoder to encode the input signal using a speech encoding module when the input signal is a speech characteristics signal; a audio signal encoder to encode the input signal using a audio encoding module when the input signal is a audio characteristic signal; and a bitstream generator to generate a bitstream.

Abstract: A method and apparatus for rendering an object-based audio signal considering an obstacle are disclosed. A method for rendering an object-based audio signal according to an example embodiment, the method includes identifying an object-based input signal and metadata for the input signal, generating a binaural filter based on the metadata using a binaural room impulse response (BRIR), determining, based on the metadata, whether an obstacle is present between a listener and an object, modifying the generated binaural filter when it is determined that the obstacle is present, and generating a rendered output signal by convolving the modified binaural filter and the input signal.

Abstract: A method and apparatus for processing acoustic spatial information are provided. The method of processing acoustic spatial information includes identifying at least one mesh disposed in an acoustic space, setting a minimum cuboid surrounding the mesh as a bounding box, and generating acoustic spatial information including information about the bounding box.

Abstract: Provided are a method of training a neural network model, a method of recognizing an acoustic event and an acoustic direction, and an electronic device for performing the methods. A method of training a neural network model according to an example embodiment includes generating a heatmap indicating an acoustic event and an acoustic direction in which the acoustic event occurs by using training data, outputting a result of recognizing the acoustic event and the acoustic direction by inputting a feature extracted using the training data into a neural network model for recognizing the acoustic event and the acoustic direction of the training data, and training the neural network model by using the result and the heatmap.

Abstract: Provided is a method and apparatus for generating an impulse response using ray tracing. The method of generating an impulse response may include calculating a number of rays reaching a receiver from a transmitter based on acoustic geometry information including a position of the transmitter and a position of the receiver disposed in a sound space, a maximum ray length or a sound space volume, and a radius of the receiver, tracing the rays using a path of the calculated rays, and generating an impulse response based on the traced rays.

Abstract: Provided are a method of recognizing sound, a method of training a sound recognition model, and an electronic device performing the same methods. A method of training a sound recognition model according to an example embodiment may include converting training data labeled with a sound class into a feature vector, storing the feature vector in a feature queue, transferring the feature vector stored in the feature queue to a block queue according to an operation of a feature vector transfer timer, inputting the feature vector of the block queue into a sound recognition model trained to predict the sound class and storing an output result in a result queue, transferring the feature vector stored in the feature queue corresponding to timing at which the result is output to the block queue by the feature vector transfer timer when the result is output.

Abstract: An audio signal encoding and decoding method using a learning model, a training method of the learning model, and an encoder and decoder that perform the method, are disclosed. The audio signal decoding method may include extracting a first residual signal and a first linear prediction coefficient by decoding a bitstream received from an encoder, generating a first audio signal from the first residual signal using the first linear prediction coefficient, generating a second linear prediction coefficients and a second residual signal from the first audio signal, obtaining a third linear prediction coefficient by inputting the second linear prediction coefficient into a trained learning model, and generating a second audio signal from the second residual signal using the third linear prediction coefficient.

Abstract: There is provided a method for transmitting data. The method for transmitting data comprises arranging a plurality of RIS based on INFO message of an AP; grouping a plurality of terminals disposed within a predetermined distance from the RIS for each RIS based on distance information from the RIS; and when data is received in the RIS from at least one or more of the grouped terminals, transmitting the received data to the AP.

Abstract: Disclosed is a binaural rendering method and apparatus for decoding a multichannel audio signal. The binaural rendering method may include: extracting an early reflection component and a late reverberation component from a binaural filter; generating a stereo audio signal by performing binaural rendering of a multichannel audio signal base on the early reflection component; and applying the late reverberation component to the generated stereo audio signal.

Abstract: The present invention relates to: an electrolyte for a rechargeable lithium battery, the electrolyte including a non-aqueous organic solvent, a lithium salt, and an electrolyte additive for a rechargeable lithium battery, the electrolyte additive including a compound represented by Chemical Formula 1; and a rechargeable lithium battery comprising the electrolyte for a rechargeable lithium battery. Chemical Formula 1 is as defined in the specification.

Abstract: Disclosed are methods of training a deep learning model and predicting a class and an electronic device for performing the methods. A method of training a deep learning model may include identifying training data labeled for each class, determining whether to augment the training data based on overall recognition performance indicating prediction accuracy of the deep learning model calculated in a previous epoch, augmenting the training data based on class-specific recognition performance indicating class-specific prediction accuracy of the deep learning model calculated in the previous epoch, predicting a class by inputting the training data or the training data that is augmented to the deep learning model according to a determination of whether to augment the training data, and training the deep learning model based on a labeled class and the predicted class.

Abstract: An audio metadata providing apparatus and method and a multichannel audio data playback apparatus and method to support a dynamic format conversion are provided. Dynamic format conversion information may include information about a plurality of format conversion schemes that are used to convert a first format set by a writer of multichannel audio data into a second format that is based on a playback environment of the multichannel audio data and that are set for each of playback periods of the multichannel audio data. The audio metadata providing apparatus may provide audio metadata including the dynamic format conversion information. The multichannel audio data playback apparatus may identify the dynamic format conversion information from the audio metadata, may convert the first format of the multichannel audio data into the second format based on the identified dynamic format conversion information, and may play back the multichannel audio data with the second format.

Abstract: There is provided a data collection system. The data collection system comprises a wake-up radio (WuR) terminal that operates in sleep mode when a wake-up signal is not received and transmits data in active mode when the wake-up signal is received; an Access Point (AP) terminal that stores information on a total number of WuR terminals in a network and sensing data collected by the WuR terminal, sets a slot through which the data is to be transmitted by the WuR terminal, and receives the data from the WuR terminal in the set slot; and a reconfigurable intelligent surface (RIS) that controls passive elements in groups, modulates the groups into different signals at the same time, and transmits the signals to a plurality of WuR terminals in a beamforming manner.

Abstract: Provided are an additive represented by Chemical Formula 1, an electrolyte for a lithium secondary battery including same, and a lithium secondary battery. The details of Chemical Formula 1 are as described in the specification.

Abstract: Methods of encoding and decoding a speech signal using a neural network model that recognizes sound sources, and encoding and decoding apparatuses for performing the methods are provided. A method of encoding a speech signal includes identifying an input signal for a plurality of sound sources; generating a latent signal by encoding the input signal; obtaining a plurality of sound source signals by separating the latent signal for each of the plurality of sound sources; determining a number of bits used for quantization of each of the plurality of sound source signals according to a type of each of the plurality of sound sources; quantizing each of the plurality of sound source signals based on the determined number of bits; and generating a bitstream by combining the plurality of quantized sound source signals.

Abstract: Disclosed herein are a method, apparatus, system, and computer-readable recording medium for image compression. An encoding apparatus performs preprocessing of feature map information, frame packing, frame classification, and encoding. A decoding apparatus performs decoding, frame depacking, and postprocessing in order to reconstruct feature map information. By encoding the feature map information, inter-prediction and intra-block prediction for a frame are performed. The encoding apparatus provides the decoding apparatus with a feature map information bitstream for reconstructing the feature map information along with an image information bitstream.

Abstract: The present invention relates to technology capable of labeling a certain site of an antibody with a certain number of chemical functional groups or cargo moieties. The present invention may provide an antibody product having high uniformity. The present invention may provide an antibody product whose antibody functions are not degraded. That is, the present invention may provide an antibody product whose antibody binding affinity and half-life are not degraded. The present invention is of great significance as being the first technology allowing site-specific labeling of an antibody without any complicated processes.

Abstract: Disclosed are methods of encoding and decoding an audio signal, and an encoder and a decoder for performing the methods. The method of encoding an audio signal includes identifying an input signal corresponding to a low frequency band of the audio signal, windowing the input signal, generating a first latent vector by inputting the windowed input signal to a first encoding model, transforming the windowed input signal into a frequency domain, generating a second latent vector by inputting the transformed input signal to a second encoding model, generating a final latent vector by combining the first latent vector and the second latent vector, and generating a bitstream corresponding to the final latent vector.

Abstract: Provided are wake-up radio systems and methods based on backscatter wake-up radio. The wake-up radio method based on backscatter wake-up radio includes setting an arbitrary receiving window period in a window setting period by receiving a beacon signal from a data collection apparatus, transmitting a backscatter response message to the data collection apparatus based on a reception time of a contention signal received from the data collection apparatus in the set receiving window period, in the window setting period, and receiving a wake-up signal from the data collection apparatus in the data transmission period to set as a wake-up period and transmitting data to the data collection apparatus based on a scheduling time according to a backscatter response message.