What would be the effect of the speech utterance length on speaker recognition. i.e
if T, UBM, LDA, PLDA-----> are trained on short utterance i.e. from 3 to 15 seconds, but
enrollment of speaker (modeled speaker) are trained on long utterance such as 30 to 60 seconds uttarnce? Would it effect the performance of the system????
These models treat observations independently across time, so there should be no problem with train and testing on utterances of different length.
There are few concerns that you should take into account:
1) It is better to make sure you have enough observations (per speaker) for training. If you have several short utterances per speaker, this should be fine
2) UBM training can be severely affected by silences. When you have long utterances in test, they likely contain a lot of silences. A common practice is to use at least energy-based voice activity detector and to score using only voiced frames.
You may find useful the SRE10 Kaldi recipe at least for having some general ideas about data pre-processing.
https://github.com/kaldi-asr/kaldi/tree/master/egs/sre10/v2
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