upload files

preprocess.py

@@ -1,5 +1,4 @@
 import os
-MIN_VOICE_NUM = 10
 if __name__ == "__main__":
     # load sampled_audio4ft
     with open("sampled_audio4ft.txt", 'r', encoding='utf-8') as f:
@@ -8,16 +7,27 @@ if __name__ == "__main__":
     # load user text
     with open("./user_voice/user_voice.txt.cleaned", 'r', encoding='utf-8') as f:
         user_annos = f.readlines()
+
     # check how many voices are recorded
     wavfiles = [file for file in list(os.walk("./user_voice"))[0][2] if file.endswith(".wav")]
     num_user_voices = len(wavfiles)
-    if num_user_voices < MIN_VOICE_NUM:
-        raise Exception(f"You need to record at least {MIN_VOICE_NUM} voices for fine-tuning!")
     # user voices need to occupy 1/4 of the total dataset
-    duplicate = num_old_voices // num_user_voices // 3
+    if num_user_voices:
+        user_duplicate = num_old_voices // num_user_voices // 3
+    else:
+        user_duplicate = 0
+
     # find corresponding existing annotation lines
     actual_user_annos = ["./user_voice/" + line for line in user_annos if line.split("|")[0] in wavfiles]
-    final_annos = old_annos + actual_user_annos * duplicate
+    final_annos = old_annos + actual_user_annos * user_duplicate
+
+    # load custom characters
+    with open("custom_character_anno.txt", 'r', encoding='utf-8') as f:
+        custom_character_anno = f.readlines()
+    # custom character voices need to be at least equal to number of sample_audio4ft
+    num_character_voices = len(custom_character_anno)
+    cc_duplicate = num_old_voices // num_character_voices
+    final_annos = final_annos + custom_character_anno * cc_duplicate
     # save annotation file
     with open("final_annotation_train.txt", 'w', encoding='utf-8') as f:
         for line in final_annos:
@@ -26,3 +36,5 @@ if __name__ == "__main__":
     with open("final_annotation_val.txt", 'w', encoding='utf-8') as f:
         for line in actual_user_annos:
             f.write(line)
+        for line in custom_character_anno:
+            f.write(line)