Create app.py

app.py

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+import gradio as gr
+from transformers import MarianMTModel, MarianTokenizer
+import speech_recognition as sr
+from gtts import gTTS
+import pyttsx3
+import tempfile
+import re
+# import os
+
+# os.environ["no_proxy"]="localhost,127.0.0.1,::1"
+
+def clean_text(text):
+    """Clean text to handle punctuations and special characters."""
+    return re.sub(r'[^\w\s,.!?;:]', '', text)
+
+# Load translation models
+tokenizer_en2zh = MarianTokenizer.from_pretrained("Helsinki-NLP/opus-mt-en-zh")
+model_en2zh = MarianMTModel.from_pretrained("Helsinki-NLP/opus-mt-en-zh")
+
+tokenizer_zh2en = MarianTokenizer.from_pretrained("Helsinki-NLP/opus-mt-zh-en")
+model_zh2en = MarianMTModel.from_pretrained("Helsinki-NLP/opus-mt-zh-en")
+
+def translate_text(input_text, target_language):
+    cleaned_text = clean_text(input_text)
+    if target_language == "en":
+        tokenizer, model = tokenizer_zh2en, model_zh2en
+    else:
+        tokenizer, model = tokenizer_en2zh, model_en2zh
+    
+    inputs = tokenizer(cleaned_text, return_tensors="pt", padding=True, truncation=True, max_length=512)
+    translated_tokens = model.generate(**inputs)
+    translated_text = tokenizer.decode(translated_tokens[0], skip_special_tokens=True)
+    return translated_text
+
+def speech_to_text(audio_file):
+    recognizer = sr.Recognizer()
+    with sr.AudioFile(audio_file) as source:
+        audio = recognizer.record(source)
+    return recognizer.recognize_google(audio)
+
+def synthesize_speech(text, language, method='gtts'):
+    if method == 'gtts':
+        tts = gTTS(text=text, lang=language)
+        temp_audio = tempfile.NamedTemporaryFile(delete=False, suffix=".mp3")
+        tts.save(temp_audio.name)
+    elif method == 'pyttsx3':
+        engine = pyttsx3.init()
+        engine.save_to_file(text, temp_audio.name)
+        engine.runAndWait()
+    return temp_audio.name
+
+def process_input(input_text=None, audio_file=None, method='gtts'):
+    recognized_text = ""
+    if audio_file:
+        recognized_text = speech_to_text(audio_file)
+    elif input_text:
+        recognized_text = input_text
+    else:
+        return "No input provided", "", None
+    
+    detected_lang = "zh" if re.search(r'[\u4e00-\u9fff]', recognized_text) else "en"
+    target_language = "zh" if detected_lang == "en" else "en"
+    
+    translated_text = translate_text(recognized_text, target_language)
+    audio_path = synthesize_speech(translated_text, target_language, method=method)
+    
+    return recognized_text, translated_text, audio_path
+
+# Gradio interface
+# Gradio Interface
+with gr.Blocks() as demo:
+    gr.Markdown("## 中英文互译及语音播报")
+    
+    inputs = [
+        gr.Textbox(label="Enter Text"),
+        gr.Audio(sources=["upload","microphone"], type="filepath", label="Or speak into the microphone")
+    ]
+    
+    translate_button = gr.Button("翻译并播报")
+    
+    outputs = [
+        gr.Textbox(label="Recognized Text"),
+        gr.Textbox(label="翻译结果"),
+        gr.Audio(label="语音播报")
+    ]
+
+    translate_button.click(fn=process_input, inputs=inputs, outputs=outputs)
+
+demo.launch(server_name="0.0.0.0", server_port=7860,share=True)