Speech/music discrimination for radio broadcasts using a hybrid HMM-Bayesian Network architecture

Author

Pikrakis, Aggelos ; Giannakopoulos, Theodoros ; Theodoridis, Sergios

Author_Institution

Dept. of Inf. & Telecommun., Univ. of Athens, Athens, Greece

fYear

2006

fDate

4-8 Sept. 2006

Firstpage

1

Lastpage

5

Abstract

This paper presents a speech/music discrimination scheme for radio recordings using a hybrid architecture based on a combination of a Variable Duration Hidden Markov Model (VDHMM) and a Bayesian Network (BN). The proposed scheme models speech and music as states in a VDHMM. A modified Viterbi algorithm for the computation of the observations´ probabilities at each state is proposed. This is achieved by embedding a BN, that outputs to the HMM the required probability values. The proposed system has been tested on audio recordings from a variety of radio stations and has exhibited an overall performance close to 95%.

Keywords

Bayes methods; Viterbi detection; audio recording; hidden Markov models; music; radio broadcasting; radio stations; speech processing; VDHMM; audio recording; hybrid HMM-Bayesian network architecture; modified Viterbi algorithm; music model; observation probability computation; radio broadcasts; radio recordings; radio station; speech model; speech-music discrimination scheme; variable duration hidden Markov model; Abstracts; Complexity theory; Hidden Markov models; Markov processes; Speech; Vectors;

fLanguage

English

Publisher

ieee

Conference_Titel

Signal Processing Conference, 2006 14th European

Conference_Location

Florence

ISSN

2219-5491

Type

conf

Filename

7071435