Create app.py

app.py

@@ -0,0 +1,62 @@
+import gradio as gr
+from transformers import pipeline
+import os
+import azure.cognitiveservices.speech as speechsdk
+
+dialects = {"Palestinian/Jordanian": "P", "Syrian": "S", "Lebanese": "L", "Egyptian": "E"}
+
+translator = pipeline(task="translation", model="guymorlan/English2Dialect")
+transliterator = pipeline(task="translation", model="guymorlan/DialectTransliterator")
+
+speech_config = speechsdk.SpeechConfig(subscription=os.environ.get('SPEECH_KEY'), region=os.environ.get('SPEECH_REGION'))
+
+def translate_text(input_text):
+    inputs = [f"{val} {input_text}" for val in dialects.values()]
+    result = translator (inputs)
+    
+    audio_files = []
+
+        
+    return result[0]["translation_text"], result[1]["translation_text"], result[2]["translation_text"], result[3]["translation_text"]
+
+
+def get_audio(input_text):
+    audio_config = speechsdk.audio.AudioOutputConfig(filename=f"{input_text}.wav")
+    speech_config.speech_synthesis_voice_name='ar-SY-AmanyNeural'
+    speech_synthesizer = speechsdk.SpeechSynthesizer(speech_config=speech_config, audio_config=audio_config)
+    speech_synthesis_result = speech_synthesizer.speak_text_async(input_text).get()
+    return f"{input_text}.wav"
+
+def get_transliteration(input_text):
+    result = transliterator([input_text])
+    return result[0]["translation_text"]
+
+
+css = """
+#liter textarea, #trans textarea { font-size: 25px;}
+#trans textarea { direction: rtl; };
+"""
+
+with gr.Blocks(title = "English to Levantine Arabic", css=css) as demo:
+    with gr.Row():
+        with gr.Column():
+            input_text = gr.inputs.Textbox(label="Input", placeholder="Enter English text", lines=1)
+            gr.Examples(["I wanted to go to the store yesterday, but it rained", "How are you feeling today?", "Let's go to your place"], input_text)
+            btn = gr.Button("Translate", label="Translate")
+            gr.Markdown("Built by [Guy Mor-Lan](mailto:guy.mor@mail.huji.ac.il). Pronunciation model is specifically tailored to urban Palestinian Arabic. Text-to-speech uses Microsoft Azure's API and may provide different result from the transliterated pronunciation.")
+
+        with gr.Column():
+            pal = gr.Textbox(lines=1, label="Palestinian", elem_id="trans")
+            pal_translit = gr.Textbox(lines=1, label="Palestinian Pronunciation", elem_id="liter")
+            sy = gr.Textbox(lines=1, label="Syrian", elem_id="trans")
+            lb = gr.Textbox(lines=1, label="Lebanese", elem_id="trans")
+            eg = gr.Textbox(lines=1, label="Egyptian", elem_id="trans")
+            with gr.Row():
+                audio = gr.Audio(label="Audio - Palestinian", interactive=False)
+                audio_button = gr.Button("Get Audio", label="Get Audio")
+                audio_button.click(get_audio, inputs=[pal], outputs=[audio])
+    btn.click(translate_text, inputs=input_text, outputs=[pal, sy, lb, eg])
+    input_text.submit(translate_text, inputs=input_text, outputs=[pal, sy, lb, eg])
+    pal.change(get_transliteration, inputs=[pal], outputs=[pal_translit])
+
+demo.launch()