Abstract:
A method for controlling a voice tracking apparatus according to an embodiment of the present invention includes the steps of: tracking a sound source of a voice signal generated from the outside; turning an image capturing unit of the voice tracking apparatus toward the location of the tracked sound source; and beamforming the voice signal of the sound source through a voice input unit mounted on the image capturing unit.
Abstract:
The present invention relates to a method and apparatus for processing a voice signal, and the voice signal encoding method according to the present invention comprises the steps of: generating transform coefficients of sine wave components forming an input voice signal by transforming the sine wave components; determining transform coefficients to be encoded from the generated transform coefficients; and transmitting indication information indicating the determined transform coefficients, wherein the indication information may include position information, magnitude information, and sign information of the transform coefficients.
Abstract:
Disclosed are a robot cleaner, and a method for controlling the same.Firstly, a sound source direction and a sound source position may be detected by one or more microphones, e,g., three microphones, and a specific event sound may be recognized. Then, the recognized specific event sound may be output to a cleaner body in the form of a message, or may be provided via a communication network. This can allow the circumstances to be easily monitored.Secondly, a sound recognition function may be updated using an ambient sound, for sound recognition from background noise and environmental noise, in a robust and precise manner. This can enhance a sound recognition rate, and improve stability and efficiency.Thirdly, the robot cleaner may be moved to a detected direction or position of a sound source with respect to an event sound. Then, image information may be detected, or whether an abnormal situation has occurred or not may be determined. Such information may be provided via a communication network.
Abstract:
The present invention relates to a method and apparatus for processing a voice signal, and the voice signal encoding method according to the present invention comprises the steps of: generating transform coefficients of sine wave components forming an input voice signal by transforming the sine wave components; determining transform coefficients to be encoded from the generated transform coefficients; and transmitting indication information indicating the determined transform coefficients, wherein the indication information may include position information, magnitude information, and sign information of the transform coefficients.
Abstract:
According to an embodiment of the present disclosure, a refrigerator may include a storage compartment, an outer door, one or more cameras provided in the outer door, a global DB configured to store a plurality of default food identification items and a plurality of default product names respectively corresponding to the plurality of default food identification items, and a local DB configured to store edited product names and a food identification item corresponding to the edited product names, and a processor configured to photograph an internal image of the storage compartment through the one or more cameras, obtain a food identification item from the photographed internal image, determine whether the obtained food identification item is stored in the local DB, and when the food identification item is not stored in the local DB, determine whether the obtained food identification item is stored in the global DB.
Abstract:
Provided is an artificial intelligence air conditioner for calibrating sensor data. The artificial intelligence air conditioner includes a sensor unit configured to acquire sensor data; a communication unit configured to receive at least one of external sensor data or environment information from at least one of an external air conditioner or an internet of things (IoT) device; and a processor. The processor is configured to generate estimated sensor data corresponding to the sensor unit using a sensor data estimation model, the received external sensor data and the received environment information, determine whether the acquired sensor data is abnormal using the generated estimated sensor data, perform an air conditioning function using the acquired sensor data if the acquired sensor data is determined as normal, and perform the air conditioning function using the generated estimated sensor data if the acquired sensor data is determined as abnormal.
Abstract:
An artificial intelligence apparatus for generating training data includes a memory configured to store a target artificial intelligence model, and a processor configured to receive sensor data, determine whether the received sensor data is irrelevant to a learning of the target artificial intelligence model, determine whether the received sensor data is useful for the learning if the received sensor data is determined to be relevant to the learning, extract a label from the received sensor data by using a label extractor if the received sensor data is determined to be useful for the learning, determine a confidence level of the extracted label, and generate training data including the received sensor data and the extracted label if the determined confidence level exceeds a first reference value.
Abstract:
According to an embodiment of the present disclosure, a refrigerator may include a storage compartment, a door, one or more cameras provided in the door, a global DB configured to store a plurality of default food identification items and a plurality of default product names respectively corresponding to the plurality of default food identification items, and a local DB configured to store edited product names and a food identification item corresponding to the edited product names, and a processor configured to photograph an internal image of the storage compartment, obtain one or more food identification items from the photographed internal image, and if the obtained one or more food identification items are stored in the local DB, recognize one or more product names of the obtained one or more food identification items as product names of the food identification items stored in the local DB.
Abstract:
Disclosed is a laundry scheduling apparatus. The apparatus includes a communication unit, an output unit, and a processor configured to pair with at least one washing machine via the communication unit, obtain laundry preference parameters of a user generated by learning based on at least one of a deep learning algorithm or a machine learning algorithm, using at least one of a laundry log of the user or laundry satisfaction information of the user as input data, generate laundry scheduling information by using washing machine information about the paired at least one washing machine, the laundry preference parameters, and laundry item information obtained via at least one of a user input unit, an interface unit, or a sensor, and cause the output unit to output the laundry scheduling information.
Abstract:
The present invention relates to a frame loss recovering method, an audio decoding method, and an apparatus using the method. A method of recovering a frame loss of an audio signal according to the present invention includes: grouping transform coefficients of at least one frame into a predetermined number of bands among previous frames of a current frame; deriving an attenuation constant according to a tonality of the bands; and recovering transform coefficients of the current frame by applying the attenuation constant to the previous frame of the current frame.