Speech classification apparatus, speech classification method, and speech classification program

A speech classification apparatus that classifies speech signals into clusters based on vocal similarity, comprising:

• a speech classification probability calculation means that calculates a probability that a latest input one of the speech signals sequentially input belongs to each of the clusters, based on a probability model for probabilistically determining to which cluster a certain speech signal belongs;
• and
• a parameter updating means that successively estimates values of parameters that define the probability model using each probability calculated by the speech classification probability calculation means;
• the speech classification probability calculation means calculating each probability based on the probability model defined by latest values of the parameters successively estimated by the parameter updating means.

A speech classification method that classifies speech signals into clusters based on vocal similarity, comprising:

• calculating a probability that a latest input one of the speech signals sequentially input belongs to each cluster, based on a probability model for probabilistically determining to which cluster a certain speech signal belongs;
• successively estimating parameters that define the probability model using the probability;
• and
• calculating a probability that at least next input speech signal belongs to each cluster, based on the probability model defined by the successively estimated parameters.

A speech classification program that classifies speech signals into clusters based on vocal similarity, the program causing a computer to execute:

• a probability calculation processing that calculates a probability that a latest input one of the speech signals sequentially input belongs to each cluster, based on a probability model for probabilistically determining to which cluster a certain speech signal belongs;
• and
• a parameter update processing that successively estimates parameters that define the probability model using each probability calculated by the speech classification probability calculation processing;
• the probability calculation processing calculating each probability based on the probability model defined by latest values of the successively estimated parameters.

A speech clustering system that performs a clustering process which generates a cluster in response to each of sequentially input speech data on-line, the system comprising:

• a speech classification probability calculation means that derives a probability that a latest one of the sequentially input speech data belongs to each cluster, using a generation model which is defined by parameter values stored in parameter storage means, assuming a speech data distribution, and storing the probability in speech classification probability storage means;
• an update target speech selection means that determines whether or not recalculation of the probability that each of the speech data belongs to each cluster is needed according to a magnitude relation between a predetermined threshold value and an indicator, the indicator being obtained by reversing a sign of an entropy of the probability that each of the speech data belongs to each cluster;
• a speech classification probability updating means that derives a probability that speech data, the probability of which is determined to be needed by the update target speech selection means, out of predetermined items of the sequentially input speech data except the latest speech data belongs to each cluster and that updates the speech classification probability storage means;
• and
• a parameter updating means that calculates sufficient statistics necessary for calculating the generation model on each of the numbers of clusters to estimate parameter values of the generation model, assuming a current number of clusters and some numbers of clusters in the vicinity of the current number of clusters, based on results of calculations by the speech classification probability calculation means and the speech classification probability updating means, and that successively updates the parameter values in the parameter storage means with the estimated parameter values.