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公开(公告)号：US20240420712A1
公开(公告)日：2024-12-19
申请号：US18732758
申请日：2024-06-04
Inventor： Byeongho CHO , Seung Kwon BEACK , Jung Won KANG , Soo Young PARK , Jongmo SUNG , Tae Jin LEE , Woo-taek LIM , Inseon JANG
IPC: G10L19/028 , G10L19/02 , G10L19/035 , G10L19/06
Abstract: A method of encoding/decoding an audio signal and a device for performing the same are provided. The method of encoding an audio signal includes generating, based on the audio signal, a linear prediction coding (LPC) bitstream and a frequency-domain signal of the audio signal, generating, based on the LPC bitstream and the frequency-domain signal, a first residual signal including information on a frequency envelope of the frequency-domain signal, and outputting a second residual signal by processing a first residual signal through one of a plurality of signal processing paths.
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公开(公告)号：US20240357306A1
公开(公告)日：2024-10-24
申请号：US18426984
申请日：2024-01-30
Inventor： Young Ho JEONG , Kyeongok KANG , Soo Young PARK , Jae-hyoun YOO , Yong Ju LEE , Tae Jin LEE , Dae Young JANG
IPC: H04S7/00
CPC classification number: H04S7/303 , H04S2400/11
Abstract: A bitstream reconstruction method and apparatus are provided. The method includes constructing an initial bitstream by rendering sound source information and geometry information within a reference radius from an initial location of a user accessing a virtual space into spatial audio, collecting location information according to a movement of the user within the virtual space, and reconstructing, based on a relationship between the reference radius and a movement radius identified according to the collected location information, the initial bitstream constructed by corresponding to the initial location of the user.
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13.发明公开公开(公告)号：US20240136993A1
公开(公告)日：2024-04-25
申请号：US18480259
申请日：2023-10-02
Inventor： Yong Ju LEE , Jae-hyoun YOO , Dae Young JANG , Soo Young PARK , Young Ho JEONG , Kyeongok KANG , Tae Jin LEE
IPC: H03G7/00
CPC classification number: H03G7/007
Abstract: A rendering method of an object-based audio signal and an apparatus for performing the same are provided. The rendering method of an object-based audio signal includes obtaining a rendered audio signal, performing clipping prevention on the rendered audio signal using a first limiter, mixing a signal output by the first limiter using a mixer, and performing clipping prevention on the mixed signal using a second limiter.
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Patent Agency Ranking
公开(公告)号：US20240129682A1
公开(公告)日：2024-04-18
申请号：US18484117
申请日：2023-10-10
Inventor： Yong Ju LEE , Jae-hyoun YOO , Dae Young JANG , Soo Young PARK , Young Ho JEONG , Kyeongok KANG , Tae Jin LEE
IPC: H04S7/00
CPC classification number: H04S7/30 , H04S2400/11
Abstract: A method of rendering object-based audio and an electronic device performing the method are provided. The method includes identifying a bitstream, determining a reference distance of an object sound source based on the bitstream, determining a minimum distance for applying distance-dependent attenuation, based on the reference distance, and determining a gain of object-based audio included in the bitstream based on the reference distance and the minimum distance.
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15.发明公开公开(公告)号：US20230177331A1
公开(公告)日：2023-06-08
申请号：US18060405
申请日：2022-11-30
Inventor： Young Ho JEONG , Soo Young PARK , Tae Jin LEE
IPC: G06N3/08
CPC classification number: G06N3/08
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.
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公开(公告)号：US20250104724A1
公开(公告)日：2025-03-27
申请号：US18886296
申请日：2024-09-16
Applicant: Electronics and Telecommunications Research Institute , The Trustees of Indiana University
Inventor： Inseon JANG , Soo Young PARK , Seung Kwon BEACK , Jongmo SUNG , Woo-taek LIM , Byeongho CHO , Jung Won KANG , Tae Jin LEE , Minje KIM , Haici YANG
IPC: G10L19/16
Abstract: A method and apparatus for encoding/decoding a neural network-based personalized speech are provided. The method includes outputting a first bit stream in which an input speech signal is encrypted, based on the input speech signal, and outputting a second bit stream in which speaker information of the input speech signal is encrypted, based on the input speech signal.
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17.发明申请公开(公告)号：US20250104722A1
公开(公告)日：2025-03-27
申请号：US18886765
申请日：2024-09-16
Applicant: Electronics and Telecommunications Research Institute , The Trustees of Indiana University
Inventor： Inseon JANG , Woo-taek LIM , Soo Young PARK , Seung Kwon BEACK , Jongmo SUNG , Byeongho CHO , Jung Won KANG , Tae Jin LEE , Minje KIM , Haici YANG
IPC: G10L19/038 , G10L21/0208 , G10L25/30
Abstract: A method and device for encoding/decoding an audio signal based on dequantization through potential diffusion are provided. The method of decoding an audio signal includes obtaining a discrete latent vector in which a speech signal is quantized and based on the discrete latent vector, outputting a continuous latent vector in which the discrete latent vector is dequantized.
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18.发明公开公开(公告)号：US20230154485A1
公开(公告)日：2023-05-18
申请号：US17987364
申请日：2022-11-15
Inventor： Young Ho JEONG , Soo Young PARK , Minhan KIM , Seungjae BAEK , Seung-Hyeon SHIN , Seokjin LEE
Abstract: Disclosed are methods of training an acoustic scene classification model and classifying an acoustic scene and an electronic device for performing the methods. The training method of an acoustic scene classification model includes inputting training data labeled as an acoustic scene to the acoustic scene classification model that is repeatedly trained by using the training data and outputting a first result predicting the acoustic scene, updating the weight of the auxiliary model configured to induce training of the acoustic scene classification model, based on a weight of the acoustic scene classification model and a weight of an auxiliary model in a previous epoch, inputting the training data to the auxiliary model and outputting a second result, calculating a cost function, based on the first result, the second result, and labeling of acoustic data, and updating the weight of the acoustic scene classification model, based on the cost function.
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