Comments (2)
Enrollment stage is exactly similar to development stage similar to this code but with different speakers.
So basically, using the background model created in the development stage, the new speakers' models will be generated in enrollment phase.
So in enrollment stage, the data pipeline is exactly similar to development phase with different identities who will be used in enrollment and evaluation phases.
Thanks,
Sina
from 3d-convolutional-speaker-recognition.
@astorfi Hi Sina,
May I way the dimension of utterance_enrollment is (108,80,40,1) while utterance_train is (12,80,40,20)?
What does the last dimension denote?
Thanks!
from 3d-convolutional-speaker-recognition.
Related Issues (20)
- Convolution expects input with rank 4, got 5 HOT 9
- Extracting VAD for our own dataset HOT 1
- How to generate data HOT 13
- Run time error in the demo HOT 6
- No such file or directory: 'results/SCORES/score_vector.npy HOT 1
- Where does input_feature.py store it's results? HOT 1
- How to make Speaker Verification (1:1 recognition) model in keras? HOT 1
- What is the exact meaning of "utterances"? HOT 4
- ValueError: axes don't match array
- What does low-level and high-level features extraction mean? HOT 1
- .wav inputs specifics HOT 6
- where is score_vector.npy HOT 2
- Demo video recording link is broken
- Please update the vedio link of the demo.
- Pre trained model HOT 1
- Does anyone know the EER of this repo? HOT 1
- How to deal with .hdfs5 files ? HOT 2
- version problem HOT 1
- Speakers for Enrollment and Development
- γAll Dependency of This Project HOT 1
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from 3d-convolutional-speaker-recognition.