update

examples/dfnet2/run.sh

@@ -10,6 +10,10 @@ sh run.sh --stage 2 --stop_stage 2 --system_version centos --file_folder_name fi
 --noise_dir "/data/tianxing/HuggingDatasets/nx_noise/data/noise" \
 --speech_dir "/data/tianxing/HuggingDatasets/nx_noise/data/speech/dns3-speech"
 
+sh run.sh --stage 1 --stop_stage 2 --system_version centos --file_folder_name file_dir --final_model_name dfnet2-nx-devoice \
+--noise_dir "/data/tianxing/HuggingDatasets/nx_noise/data/speech/nx-speech" \
+--speech_dir "/data/tianxing/HuggingDatasets/nx_noise/data/noise/nx-noise"
+
 
 END
 

examples/dtln/run.sh

@@ -13,6 +13,12 @@ sh run.sh --stage 1 --stop_stage 2 --system_version centos --file_folder_name fi
 --speech_dir "/data/tianxing/HuggingDatasets/nx_noise/data/speech/dns3-speech"
 
 
+sh run.sh --stage 1 --stop_stage 2 --system_version centos --file_folder_name file_dir-1024 --final_model_name dtln-1024-nx \
+--config_file "yaml/config-1024.yaml" \
+--noise_dir "/data/tianxing/HuggingDatasets/nx_noise/data/noise/nx-noise" \
+--speech_dir "/data/tianxing/HuggingDatasets/nx_noise/data/speech/nx-speech"
+
+
 END
 
 

examples/dtln/yaml/config-1024.yaml

@@ -0,0 +1,29 @@
+model_name: "DTLN"
+
+# spec
+sample_rate: 8000
+fft_size: 512
+hop_size: 128
+win_type: hann
+
+# data
+max_snr_db: 20
+min_snr_db: -10
+
+# model
+encoder_size: 1024
+
+# train
+lr: 0.001
+lr_scheduler: "CosineAnnealingLR"
+lr_scheduler_kwargs:
+  T_max: 250000
+  eta_min: 0.0001
+
+max_epochs: 100
+clip_grad_norm: 10.0
+seed: 1234
+
+num_workers: 4
+batch_size: 64
+eval_steps: 15000

examples/frcrn/run.sh

@@ -9,6 +9,11 @@ sh run.sh --stage 1 --stop_stage 2 --system_version centos --file_folder_name fi
 --speech_dir "/data/tianxing/HuggingDatasets/nx_noise/data/speech"
 
 
+sh run.sh --stage 1 --stop_stage 2 --system_version centos --file_folder_name file_dir --final_model_name frcrn-10-nx-devoice \
+--config_file "yaml/config-10.yaml" \
+--noise_dir "/data/tianxing/HuggingDatasets/nx_noise/data/speech/nx-speech" \
+--speech_dir "/data/tianxing/HuggingDatasets/nx_noise/data/noise/nx-noise"
+
 END
 
 

examples/frcrn/yaml/config-10.yaml

@@ -16,7 +16,7 @@ max_snr_db: 20
 
 num_workers: 8
 batch_size: 32
-eval_steps: 10000
+eval_steps: 20000
 
 lr: 0.001
 lr_scheduler: "CosineAnnealingLR"

main.py

@@ -102,16 +102,28 @@ denoise_engines = {
             "pretrained_model_path_or_zip_file": (project_path / "trained_models/dfnet2-nx-dns3.zip").as_posix()
         }
     },
-    "frcrn-dns3": {
+    "frcrn-10-dns3": {
         "infer_cls": InferenceFRCRN,
         "kwargs": {
-            "pretrained_model_path_or_zip_file": (project_path / "trained_models/frcrn-dns3.zip").as_posix()
+            "pretrained_model_path_or_zip_file": (project_path / "trained_models/frcrn-10-dns3.zip").as_posix()
         }
     },
-    "mpnet-nx-speech": {
+    "mpnet-nx": {
         "infer_cls": InferenceMPNet,
         "kwargs": {
-            "pretrained_model_path_or_zip_file": (project_path / "trained_models/mpnet-nx-speech.zip").as_posix()
+            "pretrained_model_path_or_zip_file": (project_path / "trained_models/mpnet-nx.zip").as_posix()
+        }
+    },
+    "dfnet2-nx-devoice": {
+        "infer_cls": InferenceDfNet2,
+        "kwargs": {
+            "pretrained_model_path_or_zip_file": (project_path / "trained_models/dfnet2-nx-devoice.zip").as_posix()
+        }
+    },
+    "frcrn-10-nx-devoice": {
+        "infer_cls": InferenceFRCRN,
+        "kwargs": {
+            "pretrained_model_path_or_zip_file": (project_path / "trained_models/frcrn-10-nx-devoice.zip").as_posix()
         }
     },
 }
@@ -277,8 +289,8 @@ def main():
     # http://127.0.0.1:7865/
     # http://10.75.27.247:7865/
     blocks.queue().launch(
-        # share=True,
-        share=False if platform.system() == "Windows" else False,
+        share=True,
+        # share=False if platform.system() == "Windows" else False,
         server_name="127.0.0.1" if platform.system() == "Windows" else "0.0.0.0",
         server_port=args.server_port
     )