Create app.py

app.py

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+import gradio as gr
+
+def main():
+    title = """<h1 align="center">🎤 Multilingual ASR 💬</h1>"""
+    description = """
+    💻 This demo showcases a general-purpose speech recognition model called Whisper. It is trained on a large dataset of diverse audio and supports multilingual speech recognition, speech translation, and language identification tasks.<br><br>
+    <br>
+    ⚙️ Components of the tool:<br>
+    <br>
+    &nbsp;&nbsp;&nbsp;&nbsp; - Real-time multilingual speech recognition<br>
+    &nbsp;&nbsp;&nbsp;&nbsp; - Language identification<br>
+    &nbsp;&nbsp;&nbsp;&nbsp; - Sentiment analysis of the transcriptions<br>
+    <br>
+    🎯 The sentiment analysis results are provided as a dictionary with different emotions and their corresponding scores.<br>
+    <br>
+    😃 The sentiment analysis results are displayed with emojis representing the corresponding sentiment.<br>
+    <br>
+    ✅ The higher the score for a specific emotion, the stronger the presence of that emotion in the transcribed text.<br>
+    <br>
+    ❓ Use the microphone for real-time speech recognition.<br>
+    <br>
+    ⚡️ The model will transcribe the audio and perform sentiment analysis on the transcribed text.<br>
+    """
+
+    custom_css = """
+    #banner-image {
+        display: block;
+        margin-left: auto;
+        margin-right: auto;
+    }
+    #chat-message {
+        font-size: 14px;
+        min-height: 300px;
+    }
+    """
+
+    block = gr.Blocks(css=custom_css)
+
+    with block:
+        gr.HTML(title)
+
+        with gr.Row():
+            with gr.Column():
+                gr.HTML(description)
+
+        with gr.Group():
+            with gr.Box():
+                audio = gr.Audio(
+                    label="Input Audio",
+                    show_label=False,
+                    source="microphone",
+                    type="filepath"
+                )
+
+                sentiment_option = gr.Radio(
+                    choices=["Sentiment Only", "Sentiment + Score"],
+                    label="Select an option",
+                    default="Sentiment Only"
+                )
+
+                btn = gr.Button("Transcribe")
+
+            lang_str = gr.Textbox(label="Language")
+
+            text = gr.Textbox(label="Transcription")
+
+            sentiment_output = gr.Textbox(label="Sentiment Analysis Results", output=True)
+
+            prediction = gr.Textbox(label="Prediction")
+            
+            language_translation = gr.Textbox(label="Language Translation")
+            
+
+            btn.click(inference, inputs=[audio, sentiment_option], outputs=[lang_str, text, sentiment_output, prediction,language_translation])
+
+            # gr.HTML('''
+            # <div class="footer">
+            #     <p>Model by <a href="https://github.com/openai/whisper" style="text-decoration: underline;" target="_blank">OpenAI</a>
+            #     </p>
+            # </div>
+            # ''') 
+
+    block.launch()