Comments (4)
Hi,
this repository is mainly intended for speech recognition. You are probably talking about the other repository where we used sincnet for speaker id (https://github.com/mravanelli/SincNet). To address another task you have to change datasets and labels. To assign to each sentence to the right label, you have modify the dictionary "TIMIT_labels.npy" as you pointed out. When you change task, it could be very important to properly tune the hyperparameters of the model (e.g., cw_len, cnn_N_filt, cnn_len_filt, fc_lay,lr) to make them more suitable for the new task.
Please, let me know if you are able to make it!
Thank you!
from pytorch-kaldi.
Hi,
Thank you for you reply. The repo instruction is very informative. I will get back to you when i am able to run my fusion models.
Again, thank you for your time.
tsly
from pytorch-kaldi.
Hi,
I am apologize about this but after struggling with Kaldi ASR (i'm new to kaldi), I realize that my EmotiW dataset which contains *.avi files only, can't be done as instructed for TIMIT tutorial which needs others must be done
files (as stated in Kaldi for Dummies, such as text
, lexicon
, or spk2utt
, etc.
Is there another way to construct the data preparation and alignment by myself, like preparing the pre-extracting features and labels to compatible with the pytorch-kaldi?
I've tried to run the Librispeech s5 and other free datasets with Kaldi to get how the structure of prepared data but always got some errors. I've also looked at the Kaldi-io-for-python repo and thought that the features can be converted to ark file using it but for the label and alignment i don't know how to do it.
Thank you for your time.
tsly
from pytorch-kaldi.
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Related Issues (20)
- How to setup parameters in "cfg/TIMIT_baselines/TIMIT_liGRU_fmllr.cfg"? HOT 1
- Do bidirectional layers share the input-to-hidden weights? HOT 2
- Can we resume training from the epoch we got interruption HOT 4
- input shape of nns HOT 3
- Question about the Dimension of wx.0.weight in my mlp model HOT 1
- The loss curve of train and dev is reasonable but why the Test Error keeps 53% or so? HOT 8
- Support for torch.nn.Transformer Class? HOT 1
- KaldiFatalError during decoding phase
- No WER stdout when decoding
- Does pytorch-kaldi support chain model training? HOT 1
- Word transcription of TIMIT dataset HOT 1
- No Decoding Output HOT 20
- How to train/decode on reverberant speech? HOT 1
- x-vector DNN model
- Unable to run forwarding step on test set
- Before switch to SpeechBrain, how to use trained model in pytorch
- Use final_architecture1.pkl for live test HOT 4
- err_te is 1
- using different features instead of FMLLR
- res.res
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