SPEECH DETECTION ON BROADCAST AUDIO

Date

2010-08-27

Author

Zubari, Unal
Ozan, Ezgi Can
Acar, Banu Oskay
Çiloğlu, Tolga
Esen, Ersin
Ates, Tugrul K.
Onur, Duygu Oskay

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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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).

Subject Keywords

Classificitation, Music

URI

https://hdl.handle.net/11511/53077

Conference Name

18th European Signal Processing Conference (EUSIPCO)

Collections

Department of Electrical and Electronics Engineering, Conference / Seminar

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Citation Formats

U. Zubari et al., “SPEECH DETECTION ON BROADCAST AUDIO,” presented at the 18th European Signal Processing Conference (EUSIPCO), Aalborg, DENMARK, 2010, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/53077.