Zubari U., Ozan E. C., Acar B. O., ÇİLOĞLU T., Esen E., Ates T. K., ...More

18th European Signal Processing Conference (EUSIPCO), Aalborg, Denmark, 23 - 27 August 2010, pp.85-89 identifier

  • Publication Type: Conference Paper / Full Text
  • City: Aalborg
  • Country: Denmark
  • Page Numbers: pp.85-89
  • Middle East Technical University Affiliated: Yes


Speech boundary detection contributes to performance of speech based applications such as speech recognition and speaker recognition. Speech boundary detector implemented in this study works on broadcast audio as a pre-processor module of a keyword spotter. Speech boundary detection is handled in 3 steps. At first step, audio data is segmented into homogeneous regions in an unsupervised manner. After an ACTIVITY/NON-ACTIVITY decision is made for each region, ACTIVITY regions are classified as Speech/Non-speech via Gaussian Mixture Model (GMM) based classification. GMM's are trained using a novel feature, Spectral Flow Direction (SFD), and an improved multi-band harmonicity feature in addition to widely used Mel Frequency Cepstral Coefficients (MFCC's).