If we train our PLDA with microphone data only, and test with Phone data, will it effects the system performance?
and If we train with large amount of data of microphone and with less data of phone, how much the accuracy be effected?
Or there should be a balance between them?
1. recognition always work on correlation of data or you can say correlation of features in the data.
2. more number of samples will always help you to increase accuracy
3.accuracy is your case will depend on what type of features you use
4. if you want to enhance accuracy use both time and frequency domain features , it may slow down your algorithm but accuracy will improve.more the feature you include more will be the accuracy.
5.my advice work with very simple logic you need to increase correlation.it can be done by increasing samples if you cant increase samples you have to increase features for recolonization .
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