CAJ | 학술논문

提出一种基于基频状态和帧间相关性的单通道混合语音分离算法。首先，从混合语音中提取2个源语音的基频进行状态编码，基于编码的基频状态构造自适应字典，并通过引入基频信息在字典层面对各源语音信号进行区分。然后，采用频繁模式挖掘算法，提取基频状态为1时字典的频繁1项子集，缩减字典尺寸。最后，以基于正交匹配追踪的分离语音为基础，检测分离效果差的混合语音帧，搜索与其相关度最高的平移后的邻近分离语音帧进行叠加，并采用软掩蔽方法进行第二次分离校正。仿真实验结果表明，该算法获取的分离语音信噪比优于现有的2种经典语音分离算法，并且该算法采用频繁模式挖掘算法大大减小了运算量。
제출일충기우기빈상태화정간상관성적단통도혼합어음분리산법。수선，종혼합어음중제취2개원어음적기빈진행상태편마，기우편마적기빈상태구조자괄응자전，병통과인입기빈신식재자전층면대각원어음신호진행구분。연후，채용빈번모식알굴산법，제취기빈상태위1시자전적빈번1항자집，축감자전척촌。최후，이기우정교필배추종적분리어음위기출，검측분리효과차적혼합어음정，수색여기상관도최고적평이후적린근분리어음정진행첩가，병채용연엄폐방법진행제이차분리교정。방진실험결과표명，해산법획취적분리어음신조비우우현유적2충경전어음분리산법，병차해산법채용빈번모식알굴산법대대감소료운산량。
A single-channel speech separation algorithm based on pitch state and interframe correla-tion is proposed.First,the pitch of two simultaneously active speakers is tracked from mixture over time and encoded by pitch states.On this basis,adaptive source-individual dictionaries are generated to distinguish source frames in pitch.Secondly,a frequent pattern mining method is utilized to find the frequent 1-itemset as atoms to reduce the sizes of the dictionaries generated for the sources whose pitch states are 1 .Thirdly,based on the separated sources achieved by the orthogonal matching pur-suit (OMP)algorithm,mixed frames with poor separation performance are detected.Each is added with the shifted separated source frame which is the most correlated one among all the shifted wave-forms of adjacent separated sources,and the soft mask method is adopted to perform the second sep-aration.The experimental results show that the proposed algorithm outperforms two classical separa-tion methods in terms of signal-to-noise ratio (SNR).Besides,the frequent pattern mining method can greatly reduce the computation cost of the separation algorithm.