hyperion-ml · jesus-villalba · Aug 15, 2022 · Aug 26, 2022 · Oct 21, 2022 · Oct 21, 2022
diff --git a/README.md b/README.md
@@ -23,6 +23,19 @@ The full API is described in the documentation page [https://hyperion-ml.readthe
 
 ## Installation Instructions
 
+### If you use the CLSP grid, simply run below in the root of your cloned repo (as of Aug 15 2022):
+```
+./prepare_egs_paths.sh
+# Then, type /home/janto/usr/local/anaconda3 when "Introduce path to your conda base installation (e.g.:/usr/local/anaconda3):" is prompted
+# type /home/jcho/.conda/envs/hyp_persephone_jj when "Introduce name/prefix_path for your conda environment (e.g.:hyperion)" is prompted
+
+# You may see the two lines below but it seems okay to ignore:
+# Hyperion is not installed in env
+# Adding hyperion directory to the PYTHONPATH variable in the recipes.
+
+# Also, with this, you can skip "Prerequistes to run the recipes" below
+```
+
 ### Prerequisites
 
     We use anaconda or miniconda, though you should be able to make it work in other python distributions

diff --git a/egs/voxceleb/dinossl.v1/README.md b/egs/voxceleb/dinossl.v1/README.md
@@ -0,0 +1,205 @@
+# VoxCeleb V1.1
+
+Recipe for the VoxCeleb Speaker Verification Task
+
+## Differences w.r.t VoxCeleb V1 recipe
+
+In recipe version V1: 
+   - We compute speech augmentations and acoustic features offline and dump them to disk. 
+   - Augmentation is performed using Kaldi scripts and wav-reverbate tool
+   - Babble noise is created on-the-fly when computing features by mixing 3-7 single speaker files.
+
+In this recipe:
+   - We compute speech augmentations and acoustic features are computed always on-the-fly,
+     we don't dump any features to disk. 
+   - Augmentation is performed using Hyperin SpeechAugment class.
+   - The behavior of this class is controlled 
+     by the the configuration file `conf/reverb_noise_aug.yml`, 
+     which mimics the proportions of noise and RIR types, and SNRs used in the V1 or the recipe.
+   - Babble noise is created offline by mixing 3-10 single speaker files.
+
+
+## Citing
+
+## Training Data
+
+   - x-Vector network is trained on Voxceleb2 dev + test with augmentations
+     - MUSAN noise
+     - RIR reverberation
+
+## Test data
+
+   - Test data is VoxCeleb 1
+   - We evaluate 6 conditions:
+      - VoxCeleb-O (Original): Original Voxceleb test set with 40 speakers
+      - Voxceleb-O-cleaned: VoxCeleb-O cleaned-up of some errors
+      - VoxCeleb-E (Entire): List using all utterances of VoxCeleb1
+      - Voxceleb-E-cleaned: VoxCeleb-E cleaned-up of some errors
+      - VoxCeleb-H (Hard): List of hard trials between all utterances of VoxCeleb1, same gender and nationality trials.
+      - Voxceleb-H-cleaned: VoxCeleb-H cleaned-up of some errors
+
+## Usage
+
+   - Run the run_0*.sh scripts in sequence
+   - By default it will use Light ResNet (16 base channels)
+   - For better performance use full ResNet (64 base channels) using `config_fbank80_stmn_resnet34_arcs30m0.3_adam_lr0.05_amp.v1.sh` file as
+```bash
+run_011_train_xvector.sh --config-file config_fbank80_stmn_resnet34_arcs30m0.3_adam_lr0.05_amp.v1.sh
+run_030_extract_xvectors.sh --config-file config_fbank80_stmn_resnet34_arcs30m0.3_adam_lr0.05_amp.v1.sh --use-gpu true
+run_040_eval_be.sh --config-file config_fbank80_stmn_resnet34_arcs30m0.3_adam_lr0.05_amp.v1.sh
+```
+
+   - To train with mixed precision training use config file `config_fbank80_stmn_lresnet34_arcs30m0.3_adam_lr0.05_amp.v1.sh`
+
+## Recipe Steps:
+
+   - `run_001_prepare_data.sh`
+      - Data preparation script to generate Kaldi style data directories for 
+          - VoxCeleb2 train+test
+          - VoxCeleb1 O/E/H eval sets
+
+   - `run_002_compute_evad.sh`
+      - Computes Energy VAD for all datasets
+
+   - `run_003_prepare_noises_rirs.sh`
+      - Prepares MUSAN noises, music to be used by SpeechAugment class.
+      - Creates Babble noise from MUSAN speech to be used by SpeechAugment class.
+      - Prepares RIRs by compacting then into HDF5 files, to be used by SpeechAugment class.
+
+   - `run_010_prepare_xvec_train_data.sh`
+      - Transforms all the audios that we are going to use to train the x-vector into a common format, e.g., .flac.
+      - Removes silence from the audios
+      - Removes utterances shorter than 4secs and speakers with less than 8 utterances.
+      - Creates training and validation lists for x-vector training
+
+   - `run_011_train_xvector.sh`
+      - Trains the x-vector network
+
+   - `run_030_extract_xvectors.sh`
+      - Extracts x-vectors for VoxCeleb2 or VoxCeleb2+augmentation for PLDA training
+      - Exctracts x-vectors for VoxCeleb1 test sets
+
+   - `run_040_eval_be.sh`
+      - Trains PLDA and evals PLDA and cosine scoring back-ends
+
+
+## Results
+
+### VoxCeleb 1 Original-Clean trial list
+
+| Config | Model Type | Model Details | Back-end | EER(%) | MinDCF(p=0.05) | MinDCF(p=0.01) |
+| ------ | ---------- | ------------- | -------- | :----: | :------------: | :------------: |
+| config_fbank80_stmn_lresnet34_arcs30m0.3_adam_lr0.05_amp.v1.sh | LResNet34 | ArcFace s=30/m=0.3 | PLDA | 2.00 | 0.129 | 0.216 |
+| | | | Cosine | 2.04 | 0.138 | 0.210 |
+| config_fbank80_stmn_resnet34_arcs30m0.3_adam_lr0.05_amp.v1.sh | ResNet34 | ArcFace s=30/m=0.3 | PLDA |  1.35 | 0.091 | 0.159 |
+| | | | Cosine |  1.22 | 0.082 | 0.129 |
+| config_fbank80_stmn_resnet34_arcs30m0.3_adam_lr0.05_amp_swa.v1.sh | ResNet34 | + SWA | Cosine | 1.19 | 0.074 | 0.124 |
+| config_fbank80_stmn_resnet50_arcs30m0.3_adam_lr0.05_amp.v1.sh | ResNet50 | ArcFace s=30/m=0.3 | PLDA |  1.30 | 0.090 | 0.160 |
+| | | | Cosine |  1.44 | 0.100 | 0.173 |
+| config_fbank80_stmn_tseresnet34_arcs30m0.3_adam_lr0.05_amp.v1.sh | Time-SE-ResNet34 | ArcFace s=30/m=0.3 | PLDA | 1.23 | 0.091 | 0.143 |
+| | | | Cosine |  1.17 | 0.081 | 0.110 |
+| config_fbank80_stmn_effnetb4_v2_arcs30m0.3_adam_lr0.01_amp.v1.sh | EfficientNet-b4 v2 | EfficientNet-b4 with strides=1122121 <br> ArcFace s=30/m=0.3 | 1.37 | 0.104 | 0.179 |
+| | | | Cosine | 1.31 | 0.080 | 0.139 |
+| config_fbank80_stmn_effnetb7_v2_eina_hln_arcs30m0.3_adam_lr0.01_amp.v1.sh | EfficientNet-b7 v2 | EfficientNet-b7 with strides=1122121 <br> Instance-Norm with affine transform in Encoder <br> Layer-Norm in head <br> ArcFace s=30/m=0.3 | 1.29 | 0.088 | 0.129 |
+| | | | Cosine | 1.23 | 0.083 | 0.136 |
+| config_fbank80_stmn_res2net34w16s4_arcs30m0.3_adam_lr0.05_amp.v1.sh | Res2Net34 width=16x4 | ArcFace s=30/m=0.3 | PLDA |  1.20 | 0.095 | 0.156 |
+| | | | Cosine | 1.29 | 0.089 | 0.146 |
+| config_fbank80_stmn_res2net34w26s4_arcs30m0.3_adam_lr0.05_amp.v1.sh | Res2Net34 width=26x4 | ArcFace s=30/m=0.3 | PLDA |  1.20 | 0.084 | 0.136 |
+| | | | Cosine | 1.18 | 0.078 | 0.115 |
+| config_fbank80_stmn_res2net50w26s4_arcs30m0.3_adam_lr0.05_amp.v1.sh | Res2Net50 width=26x4 | ArcFace s=30/m=0.3 | PLDA |  1.11 | 0.084 | 0.145 |
+| | | | Cosine | 1.12 | 0.073 | 0.131 |
+| config_fbank80_stmn_seres2net50w26s4_arcs30m0.3_adam_lr0.05_amp.v1.sh | SE-Res2Net50 | se-r=16 <br> ArcFace s=30/m=0.3 | PLDA |  1.53 | 0.104 | 0.189 |
+| | | | Cosine | 1.31 | 0.084 | 0.132 |
+| config_fbank80_stmn_tseres2net50w26s4_arcs30m0.3_adam_lr0.05_amp.v1.sh | Time-SE-Res2Net50 | se-r=256 <br> ArcFace s=30/m=0.3 | PLDA |  0.98 | 0.066 | 0.116 |
+| | | | Cosine | 1.12 | 0.071 | 0.103 |
+| config_fbank80_stmn_res2net50w13s8_arcs30m0.3_adam_lr0.05_amp.v1.sh | Res2Net50 width=13x8 | ArcFace s=30/m=0.3 | PLDA |  1.05 | 0.077 | 0.123 |
+| | | | Cosine | 0.96 | 0.065 | 0.110 |
+| config_fbank80_stmn_res2net50w26s8_arcs30m0.3_adam_lr0.05_amp.v1.sh | Res2Net50 width=26x8 | ArcFace s=30/m=0.3 | PLDA |  1.04 | 0.071 | 0.118 |
+| | | | Cosine | 0.93 | 0.067 | 0.108 |
+| config_fbank80_stmn_res2net50w26s8_arcs30m0.3_adam_lr0.05_amp.v1_swa.sh | Res2Net50 width=26x8 | + SWA | PLDA |  0.90 | 0.067 | 0.118 |
+| | | | Cosine | 0.85 | 0.060 | 0.094 |
+| config_fbank80_stmn_spinenet49s_arcs30m0.3_adam_lr0.05_amp.v1.sh | SpineNet49S | ArcFace s=30/m=0.3 | PLDA | 1.44 | 0.102 | 0.169 |
+| | | | Cosine | 1.29 | 0.084 | 0.140 |
+| config_fbank80_stmn_spinenet49_arcs30m0.3_adam_lr0.05_amp.v1.sh | SpineNet49 | ArcFace s=30/m=0.3 | Cosine | 1.12 | 0.071 | 0.116 |
+| config_fbank80_stmn_spine2net49_arcs30m0.3_adam_lr0.05_amp.v1.sh | Spine2Net49 | ArcFace s=30/m=0.3 | Cosine | 1.05 | 0.074 | 0.116 |
+| config_fbank80_stmn_tsespine2net49_arcs30m0.3_adam_lr0.05_amp.v1.sh | Spine2Net49 | ArcFace s=30/m=0.3 | Cosine | 1.09 | 0.081 | 0.150 |
+
+
+### VoxCeleb 1 Entire-Clean trial list
+
+| Config | Model Type | Model Details | Back-end | EER(%) | MinDCF(p=0.05) | MinDCF(p=0.01) |
+| ------ | ---------- | ------------- | -------- | :----: | :------------: | :------------: |
+| config_fbank80_stmn_lresnet34_arcs30m0.3_adam_lr0.05_amp.v1.sh | LResNet34 | ArcFace s=30/m=0.3 | PLDA | 1.86 | 0.124 | 0.210 |
+| | | | Cosine | 1.93 | 0.122 | 0.201 |
+| config_fbank80_stmn_resnet34_arcs30m0.3_adam_lr0.05_amp.v1.sh | ResNet34 | ArcFace s=30/m=0.3 | PLDA | 1.43 | 0.091 | 0.159 |
+| | | | Cosine | 1.24 | 0.080 | 0.136 |
+| config_fbank80_stmn_resnet34_arcs30m0.3_adam_lr0.05_amp_swa.v1.sh | ResNet34 | + SWA | Cosine | 1.19 | 0.077 | 0.132 |
+| config_fbank80_stmn_resnet50_arcs30m0.3_adam_lr0.05_amp.v1.sh | ResNet50 | ArcFace s=30/m=0.3 | PLDA | 1.27 | 0.084 | 0.150 |
+| | | | Cosine | 1.30 | 0.082 | 0.150 |
+| config_fbank80_stmn_tseresnet34_arcs30m0.3_adam_lr0.05_amp.v1.sh | Time-SE-ResNet34 | ArcFace s=30/m=0.3 | PLDA | 1.30 | 0.083 | 0.146 |
+| | | | Cosine | 1.09 | 0.071 | 0.124 |
+| config_fbank80_stmn_effnetb4_v2_arcs30m0.3_adam_lr0.01_amp.v1.sh | EfficientNet-b4 v2 | EfficientNet-b4 with strides=1122121 <br> ArcFace s=30/m=0.3 | 1.45 | 0.097 | 0.165 |
+| | | | Cosine | 1.15 | 0.076 | 0.132 |
+| config_fbank80_stmn_effnetb7_v2_eina_hln_arcs30m0.3_adam_lr0.01_amp.v1.sh | EfficientNet-b7 v2 | EfficientNet-b7 with strides=1122121 <br> Instance-Norm with affine transform in Encoder <br> Layer-Norm in head <br> ArcFace s=30/m=0.3 | 1.47 | 0.094 | 0.165 |
+| | | | Cosine | 1.27 | 0.082 | 0.148 |
+| config_fbank80_stmn_res2net34w16s4_arcs30m0.3_adam_lr0.05_amp.v1.sh | Res2Net34 width=16x4 | ArcFace s=30/m=0.3 | PLDA |  1.31 | 0.086 | 0.149 |
+| | | | Cosine | 1.22 | 0.079 | 0.134 |
+| config_fbank80_stmn_res2net34w26s4_arcs30m0.3_adam_lr0.05_amp.v1.sh | Res2Net34 width=26x4 | ArcFace s=30/m=0.3 | PLDA |  1.27 | 0.082 | 0.145 |
+| | | | Cosine | 1.16 | 0.074 | 0.130 |
+| config_fbank80_stmn_res2net50w26s4_arcs30m0.3_adam_lr0.05_amp.v1.sh | Res2Net50 width=26x4 | ArcFace s=30/m=0.3 | PLDA |  1.23 | 0.077 | 0.136 |
+| | | | Cosine | 1.11 | 0.071 | 0.125 |
+| config_fbank80_stmn_seres2net50w26s4_arcs30m0.3_adam_lr0.05_amp.v1.sh | SE-Res2Net50 | se-r=16 <br> ArcFace s=30/m=0.3 | PLDA |  1.46 | 0.097 | 0.173 |
+| | | | Cosine | 1.24 | 0.080 | 0.140 |
+| config_fbank80_stmn_tseres2net50w26s4_arcs30m0.3_adam_lr0.05_amp.v1.sh | Time-SE-Res2Net50 | se-r=256 <br> ArcFace s=30/m=0.3 | PLDA |  1.11 | 0.071 | 0.127 |
+| | | | Cosine | 1.05 | 0.067 | 0.117 |
+| config_fbank80_stmn_res2net50w13s8_arcs30m0.3_adam_lr0.05_amp.v1.sh | Res2Net50 width=13x8 | ArcFace s=30/m=0.3 | PLDA |  1.23 | 0.078 | 0.134 |
+| | | | Cosine | 1.05 | 0.069 | 0.121 |
+| config_fbank80_stmn_res2net50w26s8_arcs30m0.3_adam_lr0.05_amp.v1.sh | Res2Net50 width=26x8 | ArcFace s=30/m=0.3 | PLDA |  1.18 | 0.075 | 0.131 |
+| | | | Cosine | 0.98 | 0.063 | 0.110 |
+| config_fbank80_stmn_res2net50w26s8_arcs30m0.3_adam_lr0.05_amp_swa.v1.sh | Res2Net50 width=26x8 | + SWA | PLDA |  1.17 | 0.072 | 0.123 |
+| | | | Cosine | 0.94 | 0.061 | 0.107 |
+| config_fbank80_stmn_spinenet49s_arcs30m0.3_adam_lr0.05_amp.v1.sh | SpineNet49S | ArcFace s=30/m=0.3 | PLDA | 1.56 | 0.095 | 0.166 |
+| | | | Cosine | 1.27 | 0.079 | 0.142 |
+| config_fbank80_stmn_spinenet49_arcs30m0.3_adam_lr0.05_amp.v1.sh | SpineNet49 | ArcFace s=30/m=0.3 | Cosine | 1.19 | 0.077 | 0.137 |
+| config_fbank80_stmn_spine2net49_arcs30m0.3_adam_lr0.05_amp.v1.sh | Spine2Net49 | ArcFace s=30/m=0.3 | Cosine | 1.12 | 0.073 | 0.129 |
+| config_fbank80_stmn_tsespine2net49_arcs30m0.3_adam_lr0.05_amp.v1.sh | TSE-Spine2Net49 | ArcFace s=30/m=0.3 | Cosine | 1.05 | 0.068 | 0.120 |
+
+
+### VoxCeleb 1 Hard-Clean trial list
+
+| Config | Model Type | Model Details | Back-end | EER(%) | MinDCF(p=0.05) | MinDCF(p=0.01) |
+| ------ | ---------- | ------------- | -------- | :----: | :------------: | :------------: |
+| config_fbank80_stmn_lresnet34_arcs30m0.3_adam_lr0.05_amp.v1.sh | LResNet34 | ArcFace s=30/m=0.3 | PLDA | 3.29 | 0.195 | 0.318 |
+| | | | Cosine | 3.27 | 0.188 | 0.303 |
+| config_fbank80_stmn_resnet34_arcs30m0.3_adam_lr0.05_amp.v1.sh | ResNet34 | ArcFace s=30/m=0.3 | PLDA | 2.66 | 0.160 | 0.258 |
+| | | | Cosine | 2.32 | 0.139 | 0.232 |
+| config_fbank80_stmn_resnet34_arcs30m0.3_adam_lr0.05_amp_swa.v1.sh | ResNet34 | + SWA | Cosine | 2.19 | 0.133 | 0.215 |
+| config_fbank80_stmn_resnet50_arcs30m0.3_adam_lr0.05_amp.v1.sh | ResNet50 | ArcFace s=30/m=0.3 | PLDA | 2.33 | 0.139 | 0.227 |
+| | | | Cosine | 2.33 | 0.142 | 0.235 |
+| config_fbank80_stmn_tseresnet34_arcs30m0.3_adam_lr0.05_amp.v1.sh | Time-SE-ResNet34 | ArcFace s=30/m=0.3 | PLDA | 2.46 | 0.142 | 0.237 |
+| | | | Cosine | 2.14 | 0.126 | 0.203 |
+| config_fbank80_stmn_effnetb4_v2_arcs30m0.3_adam_lr0.01_amp.v1.sh | EfficientNet-b4 v2 | EfficientNet-b4 with strides=1122121 <br> ArcFace s=30/m=0.3 | 2.57 | 0.153 | 0.255 |
+| | | | Cosine | 2.11 | 0.127 | 0.205 |
+| config_fbank80_stmn_effnetb7_v2_eina_hln_arcs30m0.3_adam_lr0.01_amp.v1.sh | EfficientNet-b7 v2 | EfficientNet-b7 with strides=1122121 <br> Instance-Norm with affine transform in Encoder <br> Layer-Norm in head <br> ArcFace s=30/m=0.3 | 2.64 | 0.157 | 0.244 |
+| | | | Cosine | 2.33 | 0.141 | 0.232 |
+| config_fbank80_stmn_res2net34w16s4_arcs30m0.3_adam_lr0.05_amp.v1.sh | Res2Net34 width=16x4 | ArcFace s=30/m=0.3 | PLDA |  2.42 | 0.144 | 0.245 |
+| | | | Cosine | 2.26 | 0.133 | 0.224
+| config_fbank80_stmn_res2net34w26s4_arcs30m0.3_adam_lr0.05_amp.v1.sh | Res2Net34 width=26x4 | ArcFace s=30/m=0.3 | PLDA |  2.39 | 0.141 | 0.235 |
+| | | | Cosine | 2.17 | 0.128 | 0.215
+| config_fbank80_stmn_res2net50w26s4_arcs30m0.3_adam_lr0.05_amp.v1.sh | Res2Net50 width=26x4 | ArcFace s=30/m=0.3 | PLDA |  2.28 | 0.131 | 0.225 |
+| | | | Cosine | 2.11 | 0.124 | 0.204 |
+| config_fbank80_stmn_seres2net50w26s4_arcs30m0.3_adam_lr0.05_amp.v1.sh | SE-Res2Net50 | se-r=16 <br> ArcFace s=30/m=0.3 | PLDA |  2.77 | 0.172 | 0.271 |
+| | | | Cosine | 2.45 | 0.141 | 0.225 |
+| config_fbank80_stmn_tseres2net50w26s4_arcs30m0.3_adam_lr0.05_amp.v1.sh | Time-SE-Res2Net50 | se-r=256 <br> ArcFace s=30/m=0.3 | PLDA |  2.07 | 0.124 | 0.201 |
+| | | | Cosine | 1.95 | 0.113 | 0.181 |
+| config_fbank80_stmn_res2net50w13s8_arcs30m0.3_adam_lr0.05_amp.v1.sh | Res2Net50 width=13x8 | ArcFace s=30/m=0.3 | PLDA |  2.34 | 0.136 | 0.230 |
+| | | | Cosine | 1.99 | 0.119 | 0.196 |
+| config_fbank80_stmn_res2net50w26s8_arcs30m0.3_adam_lr0.05_amp.v1.sh | Res2Net50 width=26x8 | ArcFace s=30/m=0.3 | PLDA |  2.18 | 0.127 | 0.211 |
+| | | | Cosine | 1.89 | 0.112 | 0.184 |
+| config_fbank80_stmn_res2net50w26s8_arcs30m0.3_adam_lr0.05_amp.v1_swa.sh | Res2Net50 width=26x8 | + SWA | PLDA |  2.14 | 0.125 | 0.209 |
+| | | | Cosine | 1.84 | 0.110 | 0.186 |
+| config_fbank80_stmn_spinenet49s_arcs30m0.3_adam_lr0.05_amp.v1.sh | SpineNet49S | ArcFace s=30/m=0.3 | PLDA | 2.78 | 0.156 | 0.252 |
+| | | | Cosine | 2.26 | 0.134 | 0.214 |
+| config_fbank80_stmn_spinenet49_arcs30m0.3_adam_lr0.05_amp.v1.sh | SpineNet49 | ArcFace s=30/m=0.3 | Cosine | 2.24 | 0.134 | 0.221 |
+| config_fbank80_stmn_spine2net49_arcs30m0.3_adam_lr0.05_amp.v1.sh | Spine2Net49 | ArcFace s=30/m=0.3 | Cosine | 2.20 | 0.132 | 0.219 |
+| config_fbank80_stmn_tsespine2net49_arcs30m0.3_adam_lr0.05_amp.v1.sh | Spine2Net49 | ArcFace s=30/m=0.3 | Cosine | 2.02 | 0.123 | 0.203 |
diff --git a/egs/voxceleb/dinossl.v1/cmd.sh b/egs/voxceleb/dinossl.v1/cmd.sh
@@ -0,0 +1,28 @@
+# you can change cmd.sh depending on what type of queue you are using.
+# If you have no queueing system and want to run on a local machine, you
+# can change all instances 'queue.pl' to run.pl (but be careful and run
+# commands one by one: most recipes will exhaust the memory on your
+# machine).  queue.pl works with GridEngine (qsub).  slurm.pl works
+# with slurm.  Different queues are configured differently, with different
+# queue names and different ways of specifying things like memory;
+# to account for these differences you can create and edit the file
+# conf/queue.conf to match your queue's configuration.  Search for
+# conf/queue.conf in http://kaldi-asr.org/doc/queue.html for more information,
+# or search for the string 'default_config' in utils/queue.pl or utils/slurm.pl.
+
+if [ "$(hostname -d)" == "cm.gemini" ];then
+    #export train_cmd="queue.pl --config conf/coe_gpu_short.conf --mem 4G"
+    export train_cmd="queue.pl --config conf/coe_gpu_long.conf --mem 4G"
+    export cuda_cmd="queue.pl --config conf/coe_gpu_long.conf --mem 20G"
+    #export cuda_cmd="queue.pl --config conf/coe_gpu_v100.conf --mem 20G"
+    export cuda_cmd="queue.pl --config conf/coe_gpu_rtx.conf --mem 40G"
+    export cuda_eval_cmd="queue.pl --config conf/coe_gpu_short.conf --mem 4G"
+    # export cuda_eval_cmd="queue.pl --config conf/coe_gpu_long.conf --mem 4G"
+else
+    export train_cmd="queue.pl --mem 4G -l hostname=\"[bc][01]*\" -V" 
+    export cuda_cmd="queue.pl --mem 20G -l hostname=\"c[01]*\" -V"
+    export cuda_eval_cmd="$train_cmd"
+fi
+
+
+
diff --git a/egs/voxceleb/dinossl.v1/conf/clsp.conf b/egs/voxceleb/dinossl.v1/conf/clsp.conf
@@ -0,0 +1,11 @@
+
+# Default configuration
+command qsub -v PATH -cwd -S /bin/bash -j y -l arch=*64* -V
+option mem=* -l mem_free=$0,ram_free=$0
+option mem=0          # Do not add anything to qsub_opts
+option num_threads=* -pe smp $0
+option num_threads=1  # Do not add anything to qsub_opts
+option max_jobs_run=* -tc $0
+default gpu=0
+option gpu=0 -l 'hostname=b[1]*|c0[123456789]*|c1[134679]*|c2[1357]*'
+option gpu=* -l 'hostname=c0[123456789]*|c1[1345679]*|c2[12357]*,gpu=$0'
diff --git a/egs/voxceleb/dinossl.v1/conf/coe_gpu_bigmem.conf b/egs/voxceleb/dinossl.v1/conf/coe_gpu_bigmem.conf
@@ -0,0 +1,11 @@
+
+# Default configuration
+command qsub -v PATH -cwd -S /bin/bash -j y -sync y -l arch=*64* -V 
+option mem=* -l mem_free=$0
+option mem=0          # Do not add anything to qsub_opts
+option num_threads=* -l num_proc=$0
+option num_threads=1  # Do not add anything to qsub_opts
+option max_jobs_run=* -tc $0
+default gpu=0
+option gpu=0 -q all.q -l h_rt=100:00:00 -l hostname=r[2-7]*
+option gpu=* -l gpu=$0,h_rt=500:00:00 -q gpu.q -l hostname=r[237]n[01][0123456789]*
diff --git a/egs/voxceleb/dinossl.v1/conf/coe_gpu_long.conf b/egs/voxceleb/dinossl.v1/conf/coe_gpu_long.conf
@@ -0,0 +1,13 @@
+
+# Default configuration
+command qsub -v PATH -cwd -S /bin/bash -j y -sync y -l arch=*64* -V 
+option mem=* -l mem_free=$0
+option mem=0          # Do not add anything to qsub_opts
+option num_threads=* -l num_proc=$0
+option num_threads=1  # Do not add anything to qsub_opts
+option max_jobs_run=* -tc $0
+default gpu=0
+option gpu=0 -q all.q -l h_rt=100:00:00 -l hostname=r[1-9]*
+option gpu=* -l gpu=$0,h_rt=500:00:00 -q gpu.q -l hostname=r[1-9]*
+
+
diff --git a/egs/voxceleb/dinossl.v1/conf/coe_gpu_rtx.conf b/egs/voxceleb/dinossl.v1/conf/coe_gpu_rtx.conf
@@ -0,0 +1,11 @@
+
+# Default configuration
+command qsub -v PATH -cwd -S /bin/bash -j y -sync y -l arch=*64* -V 
+option mem=* -l mem_free=$0
+option mem=0          # Do not add anything to qsub_opts
+option num_threads=* -l num_proc=$0
+option num_threads=1  # Do not add anything to qsub_opts
+option max_jobs_run=* -tc $0
+default gpu=0
+option gpu=0 -q all.q -l h_rt=100:00:00
+option gpu=* -l gpu=$0,h_rt=500:00:00 -q gpu.q@@rtx 
diff --git a/egs/voxceleb/dinossl.v1/conf/coe_gpu_short.conf b/egs/voxceleb/dinossl.v1/conf/coe_gpu_short.conf
@@ -0,0 +1,11 @@
+
+# Default configuration
+command qsub -v PATH -cwd -S /bin/bash -j y -sync y -l arch=*64* -V 
+option mem=* -l mem_free=$0
+option mem=0          # Do not add anything to qsub_opts
+option num_threads=* -l num_proc=$0
+option num_threads=1  # Do not add anything to qsub_opts
+option max_jobs_run=* -tc $0
+default gpu=0
+option gpu=0 -q all.q -l h_rt=100:00:00 -l hostname=r[1-9]*
+option gpu=* -l gpu=$0,h_rt=00:59:00 -q gpu_short.q -l hostname=r[17]*
diff --git a/egs/voxceleb/dinossl.v1/conf/coe_gpu_v100.conf b/egs/voxceleb/dinossl.v1/conf/coe_gpu_v100.conf
@@ -0,0 +1,11 @@
+
+# Default configuration
+command qsub -v PATH -cwd -S /bin/bash -j y -sync y -l arch=*64* -V 
+option mem=* -l mem_free=$0
+option mem=0          # Do not add anything to qsub_opts
+option num_threads=* -l num_proc=$0
+option num_threads=1  # Do not add anything to qsub_opts
+option max_jobs_run=* -tc $0
+default gpu=0
+option gpu=0 -q all.q -l h_rt=100:00:00
+option gpu=* -l gpu=$0,h_rt=500:00:00 -q gpu.q@@v100
diff --git a/egs/voxceleb/dinossl.v1/conf/dinossl_tuning/fbank80_stmn_16k.yaml b/egs/voxceleb/dinossl.v1/conf/dinossl_tuning/fbank80_stmn_16k.yaml
@@ -0,0 +1,12 @@
+audio_feats:
+  audio_feat: logfb
+  sample_frequency: 16000
+  frame_length: 25
+  low_freq: 20 
+  high_freq: 7600
+  num_filters: 80
+  snip_edges: false
+  use_energy: false
+mvn:
+  context: 150
+  norm_var: false