deploy app

app.py

@@ -14,21 +14,6 @@ def generate_audio(text):
     if len(text) > MAX_TXT_LEN:
         text = text[:MAX_TXT_LEN]
         print(f"Input text was cutoff since it went over the {MAX_TXT_LEN} character limit.")
-    # model_path, config_path, model_item = manager.download_model(model_name)
-    # vocoder_name: Optional[str] = model_item["default_vocoder"]
-    # vocoder_path = None
-    # vocoder_config_path = None
-    # if vocoder_name is not None:
-    #     vocoder_path, vocoder_config_path, _ = manager.download_model(vocoder_name)
-    # synthesizer = Synthesizer(
-    #     model_path, config_path, None, None, vocoder_path, vocoder_config_path,
-    # )
-    # if synthesizer is None:
-    #     raise NameError("model not found")
-    #tts_engine= TextToSpeech()
-    # text1 = subprocess.check_output("pwd", shell=True)+ subprocess.check_output("ls Kinyarwanda_YourTTS", shell=True)
-    # text2 = text1.decode("utf-8")
-    # return text2
     synthesizer = Synthesizer("./Kinyarwanda_YourTTS/model.pth",
             "Kinyarwanda_YourTTS/config.json",
             tts_speakers_file="Kinyarwanda_YourTTS/speakers.pth",
@@ -45,13 +30,13 @@ iface = gr.Interface(
     inputs=[
         gr.inputs.Textbox(
             label="Input Text",
-            default="This sentence has been generated by a speech synthesis system.",
+            default="Muraho neza! nizere ko umunsi uri kugenda neza.",
         ),
     ],
     outputs=gr.outputs.Audio(type="filepath",label="Output"),
     #outputs=gr.outputs.Textbox(label="Recognized speech from speechbrain model"),
     title="Kinyarwanda tts Demo",
-    description="Kinyarwanda tts build with ",
+    description="Kinyarwanda tts build By Digital Umuganda, using the Bible dataset, and trained on YourTTS model.",
     allow_flagging=False,
     flagging_options=['error', 'bad-quality', 'wrong-pronounciation'],
     layout="vertical",