Update app.py

app.py

@@ -21,7 +21,6 @@ speaker_embeddings = {
 
 def getNews(search_key):
     return requests.get ("https://newsapi.org/v2/everything?q=" +search_key+ "&pagesize=3&apiKey=3bca07c913ec4703a23f6ba03e15b30b").content.decode("utf-8")
-#    return requests.get ("https://newsapi.org/v2/top-headlines?country=us&apiKey=3bca07c913ec4703a23f6ba03e15b30b").content.decode("utf-8" )
 
 def getHeadlines():
     return requests.get ("https://newsapi.org/v2/top-headlines?country=us&apiKey=3bca07c913ec4703a23f6ba03e15b30b").content.decode("utf-8")
@@ -33,16 +32,14 @@ def predict(text, speaker, preset):
 
     # text = getNews ()
     # inputs = processor(text=text, return_tensors="pt")
-    inputs = processor(text=getNews(text), 
-                       return_tensors="pt")
+    inputs = processor(text=getNews(preset), return_tensors="pt")
 
     # limit input length
     input_ids = inputs["input_ids"]
     input_ids = input_ids[..., :model.config.max_text_positions]
 
-    
-    speaker_embedding = np.load(speaker_embeddings[speaker[:3]])
-
+    speaker_embedding = np.load("spkemb/cmu_us_bdl_arctic-wav-arctic_a0009.npy")
+   
     speaker_embedding = torch.tensor(speaker_embedding).unsqueeze(0)
 
     speech = model.generate_speech(input_ids, speaker_embedding, vocoder=vocoder)