Learn More
Automatic Emotion Recognition (AER) from speech is one of the most interested research domains for the scientific world. AER simply means to make a machine able to recognize the different emotions from speech. We have created and analyzed an elicited database consisting of 700 utterances under four different emotional classes such as neutral happy sad and(More)
This paper deals a novel speech feature extraction technique based on wavelet. We have employed daubechies 4 type of wavelet for feature extraction. Artificial neural network technique (ANN) is used for classification and recognition purpose. We have used five Malayalam (one of the South Indian languages) words for the experiment. One hundred and sixty(More)
As the technology develops, people looks forward more on Speech analysis for Speaker Recognition. A large multichannel corpus, including mobile phone, mobile phone headset, laptop microphone and laptop headset, is collected to evaluate the system performance. Also, a comparative study among wavelet packets and DWT on a gender based Speaker recognition(More)
In this paper we present an effective and robust method for speaker identification based on discrete stationary wavelet transform and principal component analysis techniques. The time invariant characteristic of SWT is particularly used in this paper for Speaker recognition. We have selected PCA as it is a core of modern data analysis. For classification(More)
  • 1