add app.py and requirements.txt

app.py

@@ -0,0 +1,89 @@
+# Module Imports
+from pytube import YouTube
+import whisper
+import gradio as gr
+
+model = whisper.load_model("base.en")
+
+# Functions
+def transcribe(file):
+    options = dict(task="transcribe", best_of=5)
+    text = model.transcribe(file, **options)["text"]
+    return text.strip()
+
+def translate(file):
+    options = dict(task="translate", best_of=5)
+    text = model.transcribe(file, **options)["text"]
+    return text.strip()
+
+def get_filename(file_obj):
+    return file_obj.orig_name
+
+def inference(link):
+  yt = YouTube(link)
+  path = yt.streams.filter(only_audio=True)[0].download(filename="audio.mp4")
+  options = whisper.DecodingOptions(without_timestamps=True)
+  results = model.transcribe(path)
+  return results['text']
+
+def populate_metadata(link):
+  yt = YouTube(link)
+  return yt.thumbnail_url, yt.title
+
+def transcribe_file(file):
+    options = dict(task="transcribe", best_of=5)
+    file = get_filename(file)
+    text = model.transcribe(file, **options)["text"]
+    return text.strip()
+
+# Gradio Blocks
+demo = gr.Blocks()
+with demo:
+    gr.Markdown(""" <p style="text-align: center;"> Speech To Text Grammar Checker </p>""")
+    with gr.Tabs():
+        with gr.TabItem("Voice Record"):
+            with gr.Row():
+                audio = gr.Audio(show_label=False,source="microphone",type="filepath")
+                text_output1 = gr.Textbox(label="Transcription", placeholder="Text Output")
+            transcribe_button1 = gr.Button("Transcribe")
+            CG_button1 = gr.Button("Check Grammar (Work In Progress)")
+        with gr.TabItem("Upload File"):
+            with gr.Row():
+                file_upload = gr.File()
+                text_output2 = gr.Textbox(label="Transcription", placeholder="Text Output")
+            transcribe_button2 = gr.Button("Transcribe")
+            CG_button3 = gr.Button("Check Grammar (Work In Progress)")
+        with gr.TabItem("Youtube Link"):
+            with gr.Box():
+                link = gr.Textbox(label="YouTube Link")
+                with gr.Row().style(mobile_collapse=False, equal_height=True):
+                  title = gr.Label(label="Video Title", placeholder="Title")
+                  img = gr.Image(label="Thumbnail")
+                text_link_output = gr.Textbox(label="Transcription", placeholder="Text Output",lines=5)
+                with gr.Row().style(mobile_collapse=False, equal_height=True): 
+                  transcribe_button3 = gr.Button("Transcribe")
+                  CG_button3 = gr.Button("Check Grammar (Work In Progress)")
+        with gr.TabItem("About"):
+          with gr.Row():
+            gr.Markdown("""
+            <p style="text-align: center;"> Thesis System presented by  <br/> <br/>
+            • <b>Jomari A. Buenaobra</b> <br/>
+            • <b>Christian G. Eslit</b> <br/>
+            • <b>Daniel L. Espinola</b> <br/>
+            • <b>Jhon Vincent A. Gupo</b> <br/>
+            • <b>Ryan M. Ibay</b> <br/> <br/>
+            In partial fulfillment of the requirements for the degree <br/>   
+            Bachelor of Science in Computer Science Specialized in Intelligent Systems <br/>
+            Laguna State Polytechnic University - Los Baños Campus . <br/>  <br/> 
+            We would also like to thank our fellow adviser and subject specialist for their guidance in making this idea a reality. <br/>
+            • <b>Crisanto F. Gulay</b> - Adviser <br/>
+            • <b>Jonardo R. Asor</b> - Subject Specialist <br/>
+            </p>
+            """)
+
+            link.change(populate_metadata, inputs=[link], outputs=[img, title])
+            transcribe_button1.click(transcribe, inputs=audio, outputs=text_output1)
+            transcribe_button2.click(transcribe_file, inputs=file_upload, outputs=text_output2)
+            transcribe_button3.click(inference, inputs=link, outputs=text_link_output)
+            
+demo.launch()

requirements.txt.txt

@@ -0,0 +1,3 @@
+git+https://github.com/openai/whisper.git
+gradio
+pytube