Update app.py

app.py

@@ -23,7 +23,7 @@ def get_timestamp(seconds):
     seconds = int(seconds % 60)
     return f"{str(minutes).zfill(2)}:{str(seconds).zfill(2)}"
 
-def divide_into_30s_segments(audio_fpath, seconds_max):
+def create_segments(audio_fpath, seconds_max):
     """
     Divides the audio file into 30s segments and returns the paths to the segments and the start times of the segments.
     :param audio_fpath: Path to the audio file.
@@ -82,7 +82,7 @@ def transcribe(audio, url, seconds_max):
     """
     if url:
         fpath = download_from_youtube(url)
-        segment_paths, segment_start_times = divide_into_30s_segments(fpath, seconds_max)
+        segment_paths, segment_start_times = create_segments(fpath, seconds_max)
 
         audio_dataset = Dataset.from_dict({"audio": segment_paths}).cast_column("audio", Audio(sampling_rate=16000))
         pred = pipe(audio_dataset["audio"])
@@ -106,8 +106,8 @@ iface = gr.Interface(
         gr.Slider(minimum=30, maximum=300, value=30, step=30, label="Number of seconds to transcribe from YouTube URL")
     ], 
     outputs="text",
-    title="Whisper Small Swedish",
-    description="Realtime demo for Swedish speech recognition using a fine-tuned Whisper small model.",
+    title="Whisper: transcribe Swedish language audio to text",
+    description="Swedish Text Transcription using Transformers.",
 )
 
 iface.launch()