Update app.py

app.py

@@ -188,22 +188,21 @@ def infer_batch(ref_audio, ref_text, gen_text_batches, exp_name, remove_silence,
     generated_waves = []
     spectrograms = []
 
-
-
+    if len(ref_text[-1].encode("utf-8")) == 1:
+        ref_text = ref_text + " "
     for i, gen_text in enumerate(progress.tqdm(gen_text_batches)):
         # Prepare the text
-        if len(ref_text[-1].encode('utf-8')) == 1:
-            ref_text = ref_text + " "
         text_list = [ref_text + gen_text]
         final_text_list = convert_char_to_pinyin(text_list)
 
-        # Calculate duration
         ref_audio_len = audio.shape[-1] // hop_length
-        zh_pause_punc = r"。，、；：？！"
-        ref_text_len = len(ref_text.encode('utf-8')) + 3 * len(re.findall(zh_pause_punc, ref_text))
-        gen_text_len = len(gen_text.encode('utf-8')) + 3 * len(re.findall(zh_pause_punc, gen_text))
-        duration = ref_audio_len + int(ref_audio_len / ref_text_len * gen_text_len / speed)
-
+        if fix_duration is not None:
+            duration = int(fix_duration * target_sample_rate / hop_length)
+        else:
+            # Calculate duration
+            ref_text_len = len(ref_text.encode("utf-8"))
+            gen_text_len = len(gen_text.encode("utf-8"))
+            duration = ref_audio_len + int(ref_audio_len / ref_text_len * gen_text_len / speed)
     # Print the calculated duration
         print(f"Duration: {duration} seconds")
         # inference