3. The method of claim 2 , further comprising: receiving one or more test speech samples; generating a set of test data by extracting one or more acoustic features from every frame of the one or more test speech samples; and transforming the set of test data into transformed data using the PLDA model to capture emotion and/or speaking style in the transformed data; and using the transformed data for clustering and/or classification to discover speech with emotion or speaking styles similar to that captured in the transformed data.
3. The method of claim 2 , further comprising: receiving one or more test speech samples; generating a set of test data by extracting one or more acoustic features from every frame of the one or more test speech samples; and transforming the set of test data into transformed data using the PLDA model to capture emotion and/or speaking style in the transformed data; and using the transformed data for clustering and/or classification to discover speech with emotion or speaking styles similar to that captured in the transformed data. 4. The method of claim 3 , wherein the one or more test speeches includes one or more speakers and one or more emotions or speaking styles different from the one or more sample speeches.