Update app.py

app.py

@@ -1,23 +1,28 @@
 import gradio as gr
 import librosa
 from asr import transcribe, ASR_EXAMPLES, ASR_NOTE
-from lid import identify  # Import language identification model
+from lid import identify  # Import Language Identification model
 
-# Function to detect language and transcribe automatically
-def auto_detect_and_transcribe(audio):
-    detected_lang = identify(audio)  # Identify language from audio
-    if detected_lang in ["swh", "eng"]:  # Ensure it's either Swahili or English
-        return f"[Detected Language: {detected_lang.upper()}]\n\n" + transcribe(audio)
-    return "Error: Unsupported language detected."
+# Function to detect language and transcribe speech
+def auto_transcribe(audio):
+    # Detect language (returns language code like "eng" or "swh")
+    detected_lang = identify(audio)
+
+    # Ensure the detected language is Swahili or English
+    if detected_lang not in ["eng", "swh"]:
+        return "Error: Only English and Swahili are supported."
+
+    # Transcribe using detected language
+    return transcribe(audio, lang=detected_lang)
 
 # Speech-to-Text Interface with Auto Language Detection
 mms_transcribe = gr.Interface(
-    fn=auto_detect_and_transcribe,
+    fn=auto_transcribe,
     inputs=gr.Audio(),
     outputs="text",
     examples=ASR_EXAMPLES,
-    title="Speech-to-Text (Automatic Language Detection)",
-    description="Upload or record audio, and the model will detect if it is Swahili or English before transcribing.",
+    title="Speech-to-Text (Auto Language Detection)",
+    description="Automatically detects whether speech is in Swahili or English and transcribes it.",
     article=ASR_NOTE,
     allow_flagging="never",
 )
@@ -25,11 +30,10 @@ mms_transcribe = gr.Interface(
 # Main Gradio App
 with gr.Blocks() as demo:
     gr.Markdown("<p align='center' style='font-size: 20px;'>MMS Speech-to-Text</p>")
-    gr.HTML("<center>Convert speech to text while automatically detecting Swahili or English.</center>")
+    gr.HTML("<center>Automatically detects and transcribes Swahili or English speech.</center>")
 
     mms_transcribe.render()
 
 if __name__ == "__main__":
     demo.queue()
     demo.launch()
-