Information processing, in terms of archiving, indexing, delivering, accessing and other processing, require in-depth knowledge of content to optimize the performance.
Choose one among a set of candidate models M i , i =1,2,..., m and corresponding model parameters to represent a given data set D = ( D 1 , D 2 , …, D N ).
Model Posterior Probability
Bayesian information criterion
Maximized log data likelihood for the given model with model complexity penalty
Bayesian information criterion of model M i
where d i is the number of independent
parameters in the mode parameter set
17.
Unsupervised Segmentation Using Bayesian Information Criterion
First model
Second model
Bayesian information criterion
18.
Disadvantages of Conventional Unsupervised Speaker Change Detection
Disadvantage:
For metric based methods, it’s not easy to decide a suitable threshold
For BIC, it’s not easy to detect speaker segment less than 2 seconds
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