Disclosed are a method for recognizing an unmanned aerial vehicle (UAV) sound based on a hidden Markov model (HMM) using a mel-frequency cepstral coefficients (MFCC) technique in an environment having much real noise and a system thereof. A method for recognizing sound of a UAV comprises the following steps of: extracting a feature vector related to a sound signal of a UAV based on an MFCC technique in an environment where noise exists; training an HMM model based on a training data set generated based on the extracted feature vector; and recognizing a sound signal corresponding to the UAV based on the trained HMM model with respect to an input sound signal.

    실질 잡음이 많은 환경에서 MFCC 기법을 이용한 HMM 기반 무인 항공기 음향 인식 방법 및 시스템이 개시된다. 무인 항공기(Unmanned Aerial Vehicle)의 음향을 인식하는 방법에 있어서, 잡음(noise)이 존재하는 환경에서 MFCC(Mel Frequency Cepstral Coefficients) 기법에 기초하여 무인 항공기(UAV)의 음향 신호관련 특징 벡터를 추출하는 단계, 추출된 특징 벡터를 기반으로 생성된 학습 데이터 세트에 기초하여 HMM(hidden Markov Model) 모델을 학습시키는 단계, 및 입력된 음향 신호를 대상으로, 학습된 HMM 모델에 기초하여 무인 항공기(UAV)에 해당하는 음향 신호를 인식하는 단계를 포함할 수 있다.


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    Title :

    MFCC HMM SYSTEM AND METHOD FOR HIDDEN MARKOV MODEL BASED UAV SOUND RECOGNITION USING MFCC TECHNIQUE IN PRACTICAL NOISY ENVIRONMENTS


    Additional title:

    실질 잡음 환경에서 MFCC 기법을 이용한 HMM 기반 무인 항공기 음향 인식 방법 및 시스템


    Contributors:
    KYUNGHI CHANG (author) / SHI LIN (author) / HE YUJING (author)

    Publication date :

    2019-07-24


    Type of media :

    Patent


    Type of material :

    Electronic Resource


    Language :

    Korean


    Classification :

    IPC:    G10L Analyse oder Synthese von Sprache , SPEECH ANALYSIS OR SYNTHESIS / B64C AEROPLANES , Flugzeuge / G05D SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES , Systeme zum Steuern oder Regeln nichtelektrischer veränderlicher Größen



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