Update tts.py

tts.py

@@ -0,0 +1,58 @@
+import os
+import torch
+import torchaudio
+from TTS.tts.configs.xtts_config import XttsConfig
+from TTS.tts.models.xtts import Xtts
+from huggingface_hub import snapshot_download, hf_hub_download
+from vinorm import TTSnorm
+
+def generate_speech(text, language="vi", speaker_wav=None):
+    # Tải mô hình nếu chưa được tải
+    checkpoint_dir = "model/"
+    repo_id = "capleaf/viXTTS"
+    use_deepspeed = False
+
+    os.makedirs(checkpoint_dir, exist_ok=True)
+
+    required_files = ["model.pth", "config.json", "vocab.json", "speakers_xtts.pth"]
+    files_in_dir = os.listdir(checkpoint_dir)
+    if not all(file in files_in_dir for file in required_files):
+        snapshot_download(
+            repo_id=repo_id,
+            repo_type="model",
+            local_dir=checkpoint_dir,
+        )
+        hf_hub_download(
+            repo_id="coqui/XTTS-v2",
+            filename="speakers_xtts.pth",
+            local_dir=checkpoint_dir,
+        )
+
+    # Cấu hình và tải mô hình
+    xtts_config = os.path.join(checkpoint_dir, "config.json")
+    config = XttsConfig()
+    config.load_json(xtts_config)
+    MODEL = Xtts.init_from_config(config)
+    MODEL.load_checkpoint(config, checkpoint_dir=checkpoint_dir, use_deepspeed=use_deepspeed)
+
+    if torch.cuda.is_available():
+        MODEL.cuda()
+
+    # Chuẩn hóa văn bản
+    normalized_text = TTSnorm(text)
+
+    # Tạo giọng nói
+    with torch.no_grad():
+        gpt_cond_latent, speaker_embedding = MODEL.get_conditioning_latents(audio_path=speaker_wav)
+        out = MODEL.inference(
+            normalized_text,
+            language,
+            gpt_cond_latent,
+            speaker_embedding,
+            temperature=0.7,
+        )
+
+    # Lưu file âm thanh
+    output_file = "output.wav"
+    torchaudio.save(output_file, torch.tensor(out["wav"]).unsqueeze(0), 22050)
+    return output_file