Spaces:
Running
Running
| 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() | |