شماره ركورد كنفرانس :
1730
عنوان مقاله :
Best Features for Emotional Speech Classification in the Presence of Babble Noise
عنوان به زبان ديگر :
Best Features for Emotional Speech Classification in the Presence of Babble Noise
پديدآورندگان :
Karimi Salman نويسنده , Sedaaghi Mohammad Hossein نويسنده
كليدواژه :
babble noise , Noise , Artificial neural networks , Support vector machines , Robustness , Classification , Emotional Speech Recognition , Feature selection
عنوان كنفرانس :
بيستمين كنفرانس مهندسي برق ايران
چكيده لاتين :
Hitherto, different efforts have been held for the recognition of emotional state of speakers. Most of these works are performed in clean environments. But, in the real world,there are different noise parameters such as cross-talk, car noise, awgn (especially in the transmission of sounds) and etc., whichdecrease the performance of classifiers. In this paper we look for features which have the best performance in the presence ofbabble noise. We carry out our evaluation on three emotional speech datasets
شماره مدرك كنفرانس :
4460809