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step 3 in inference your own data confusion #19

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amandeepbaberwal opened this issue Mar 7, 2023 · 2 comments
Open

step 3 in inference your own data confusion #19

amandeepbaberwal opened this issue Mar 7, 2023 · 2 comments

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@amandeepbaberwal
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amandeepbaberwal commented Mar 7, 2023

Hello i am following you guide to infer my own data here and i am confused about step 20, where should i run the step 20 python code??
here is my tree from data
raw_kaldi_gop
│   └── librispeech
│   ├── te_feats.csv
│   ├── te_keys_phn.csv
│   ├── te_keys_word.csv
│   ├── te_labels_phn.csv
│   ├── te_labels_word.csv
│   ├── tr_feats.csv
│   ├── tr_keys_phn.csv
│   ├── tr_keys_word.csv
│   ├── tr_labels_phn.csv
│   └── tr_labels_word.csv
├── README.md
├── seq_data_librispeech
│   ├── te_feat.npy
│   ├── te_label_phn.npy
│   ├── te_label_utt.npy
│   ├── te_label_word.npy
│   ├── tr_feat.npy
│   ├── tr_label_phn.npy
│   ├── tr_label_utt.npy
│   └── tr_label_word.npy
├── seq_data_paiia
│   ├── te_feat.npy
│   ├── te_label_phn.npy
│   ├── te_label_utt.npy
│   ├── te_label_word.npy
│   ├── tr_feat.npy
│   ├── tr_label_phn.npy
│   ├── tr_label_utt.npy
│   └── tr_label_word.npy
└── seq_data_paiib
├── te_feat.npy
├── te_label_phn.npy
├── te_label_utt.npy
├── te_label_word.npy
├── tr_feat.npy
├── tr_label_phn.npy
├── tr_label_utt.npy
└── tr_label_word.npy

**My exp folder**
final.py

├── gopt-1e-3-3-1-25-24-gopt-librispeech-br
│   └── result_summary.csv
├── gopt-1e-3-3-1-25-24-gopt-librispeech-br-0
│   ├── models
│   │   └── best_audio_model.pth
│   ├── preds
│   │   ├── phn_pred.npy
│   │   ├── phn_target.npy
│   │   ├── utt_pred.npy
│   │   ├── utt_target.npy
│   │   ├── word_pred.npy
│   │   └── word_target.npy
│   └── result.csv
├── gopt-1e-3-3-1-25-24-gopt-librispeech-br-1
│   ├── models
│   │   └── best_audio_model.pth
│   ├── preds
│   │   ├── phn_pred.npy
│   │   ├── phn_target.npy
│   │   ├── utt_pred.npy
│   │   ├── utt_target.npy
│   │   ├── word_pred.npy
│   │   └── word_target.npy
│   └── result.csv
├── gopt-1e-3-3-1-25-24-gopt-librispeech-br-2
│   ├── models
│   │   └── best_audio_model.pth
│   ├── preds
│   │   ├── phn_pred.npy
│   │   ├── phn_target.npy
│   │   ├── utt_pred.npy
│   │   ├── utt_target.npy
│   │   ├── word_pred.npy
│   │   └── word_target.npy
│   └── result.csv
├── gopt-1e-3-3-1-25-24-gopt-librispeech-br-3
│   ├── models
│   │   └── best_audio_model.pth
│   ├── preds
│   │   ├── phn_pred.npy
│   │   ├── phn_target.npy
│   │   ├── utt_pred.npy
│   │   ├── utt_target.npy
│   │   ├── word_pred.npy
│   │   └── word_target.npy
│   └── result.csv
├── gopt-1e-3-3-1-25-24-gopt-librispeech-br-4
│   ├── models
│   │   └── best_audio_model.pth
│   ├── preds
│   │   ├── phn_pred.npy
│   │   ├── phn_target.npy
│   │   ├── utt_pred.npy
│   │   ├── utt_target.npy
│   │   ├── word_pred.npy
│   │   └── word_target.npy
│   └── result.csv
└── README.md

@YuanGongND
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Please note this is not an official tutorial so you might need to figure it out by yourself, and you need to take care of the bug I pointed out in the readme file.

-Yuan

@YuanGongND
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A general suggestion is to first fully reproduce the original code on so762 and then get to your own data.

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