Sch. of Math., Stat. Comput. Sci., Central Univ. of Bihar, Patna, India;
Gaussian processes; emotion recognition; mixture models; speech recognition; Berlin emotional database; GMM; Gaussian mixture models; IIT Kharagpur simulated emotion speech corpus; LP residual; inverse filtering; linear prediction residual; segmental level; speech signal based emotion recognition; sub-segmental level; supra-segmental level; Databases; Emotion recognition; Feature extraction; Gaussian mixture model; Speech; Speech recognition; Feature vector; Gaussian Mixture Model; Linear prediction analysis; Linear pr;
机译:基于超分割特征的单词水平连续语音自动分割
机译:基于不同语音段水平的情绪识别
机译:基于多级残余卷积神经网络的语音情感识别
机译:在子系统,分段和超节段形水平下使用LP残差的情感识别
机译:基于属性的语音情感识别的新颖框架使用时间连续迹线和句子级注释
机译:语音反馈的超分段变化是频谱反馈退化的结果:与伦巴第语音的比较
机译:使用Supra-segment级激励信息的扬声器识别