fix: classify language

add self.lang

bert_vits2/bert_vits2.py

@@ -7,6 +7,7 @@
 from bert_vits2.text import *
 from bert_vits2.text.cleaner import clean_text
 from bert_vits2.utils import process_legacy_versions
+from contants import ModelType
 from utils import classify_language, get_hparams_from_file, lang_dict
 from utils.sentence import sentence_split_and_markup, cut
 
@@ -18,7 +19,7 @@ def __init__(self, model, config, device=torch.device("cpu"), **kwargs):
         self.speakers = [item[0] for item in
                          sorted(list(getattr(self.hps_ms.data, 'spk2id', {'0': 0}).items()), key=lambda x: x[1])]
         self.symbols = symbols
-        
+
         # Compatible with legacy versions
         self.version = process_legacy_versions(self.hps_ms)
 
@@ -32,6 +33,9 @@ def __init__(self, model, config, device=torch.device("cpu"), **kwargs):
         elif self.version in ["1.1", "1.1.0", "1.1.1"]:
             self.hps_ms.model.n_layers_trans_flow = 6
 
+        key = f"{ModelType.BERT_VITS2.value}_v{self.version}" if self.version else ModelType.BERT_VITS2.value
+        self.lang = lang_dict.get(key, ["unknown"])
+
         self._symbol_to_id = {s: i for i, s in enumerate(self.symbols)}
 
         self.net_g = SynthesizerTrn(
@@ -115,7 +119,8 @@ def get_audio(self, voice, auto_break=False):
         max = voice.get("max", 50)
         # sentence_list = sentence_split_and_markup(text, max, "ZH", ["zh"])
         if lang == "auto":
-            lang = classify_language(text, target_languages=lang_dict["bert_vits2"])
+            lang = classify_language(text, target_languages=self.lang)
+
         sentence_list = cut(text, max)
         audios = []
         for sentence in sentence_list:

vits/vits.py

@@ -5,7 +5,7 @@
 from torch import no_grad, LongTensor, inference_mode, FloatTensor
 import utils
 from contants import ModelType
-from utils import get_hparams_from_file
+from utils import get_hparams_from_file, lang_dict
 from utils.sentence import sentence_split_and_markup
 from vits import commons
 from vits.mel_processing import spectrogram_torch
@@ -39,6 +39,9 @@ def __init__(self, model, config, additional_model=None, model_type=None, device
         _ = self.net_g_ms.eval()
         self.device = device
 
+        key = getattr(self.hps_ms.data, "text_cleaners", ["none"])[0]
+        self.lang = lang_dict.get(key, ["unknown"])
+
         # load model
         self.load_model(model, additional_model)