.

app.py

@@ -1,17 +1,12 @@
 import gradio as gr
 from transformers import pipeline
-import torch
 
 MODEL_NAME = "openai/whisper-large-v3"
 BATCH_SIZE = 8
 
-device = 0 if torch.cuda.is_available() else "cpu"
-
 asr = pipeline(
     task="automatic-speech-recognition",
     model=MODEL_NAME,
-    chunk_length_s=30,
-    device=device,
 )
 
 def transcribe(filepath):

speech-gen.py

@@ -0,0 +1,9 @@
+from transformers import pipeline
+
+synthesizer = pipeline("text-to-speech", "suno/bark")
+
+
+def generate_speech(text):
+    result = synthesizer(text)
+    print(synthesizer(text))
+    return synthesizer(text)