Create app.py

app.py

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+import streamlit as st
+import torch
+from transformers import pipeline, AutoTokenizer, AutoModelForSeq2SeqLM
+import torchaudio
+import os
+import re
+import jieba
+
+# Device setup: 自动选择使用 CUDA 或 CPU
+device = "cuda" if torch.cuda.is_available() else "cpu"
+
+# 加载 Whisper 模型，用于音频转录（粤语版）
+MODEL_NAME = "alvanlii/whisper-small-cantonese"
+language = "zh"
+pipe = pipeline(task="automatic-speech-recognition", model=MODEL_NAME, chunk_length_s=60, device=device)
+pipe.model.config.forced_decoder_ids = pipe.tokenizer.get_decoder_prompt_ids(language=language, task="transcribe")
+
+def transcribe_audio(audio_path):
+    """
+    对音频文件进行转录，支持大于60秒的音频分段处理
+    """
+    waveform, sample_rate = torchaudio.load(audio_path)
+    duration = waveform.shape[1] / sample_rate
+    if duration > 60:
+        results = []
+        for start in range(0, int(duration), 50):
+            end = min(start + 60, int(duration))
+            chunk = waveform[:, start * sample_rate:end * sample_rate]
+            temp_filename = f"temp_chunk_{start}.wav"
+            torchaudio.save(temp_filename, chunk, sample_rate)
+            result = pipe(temp_filename)["text"]
+            results.append(result)
+            os.remove(temp_filename)
+        return " ".join(results)
+    return pipe(audio_path)["text"]
+
+# 加载翻译模型（粤语到中文）
+tokenizer = AutoTokenizer.from_pretrained("botisan-ai/mt5-translate-yue-zh")
+model = AutoModelForSeq2SeqLM.from_pretrained("botisan-ai/mt5-translate-yue-zh").to(device)
+
+def split_sentences(text):
+    """根据中文标点分割句子"""
+    return [s for s in re.split(r'(?<=[。！？])', text) if s]
+
+def translate(text):
+    """
+    将转录文本翻译为中文，逐句翻译后拼接输出
+    """
+    sentences = split_sentences(text)
+    translations = []
+    for sentence in sentences:
+        inputs = tokenizer(sentence, return_tensors="pt").to(device)
+        outputs = model.generate(inputs["input_ids"], max_length=1000, num_beams=5)
+        translations.append(tokenizer.decode(outputs[0], skip_special_tokens=True))
+    return " ".join(translations)
+
+# 加载质量评分模型，用于评价对话质量
+rating_pipe = pipeline("text-classification", model="Leo0129/CustomModel_dianping-chinese")
+
+def split_text(text, max_length=512):
+    """
+    将文本按照最大长度拆分成多个片段，使用 jieba 分词
+    """
+    words = list(jieba.cut(text))
+    chunks, current_chunk = [], ""
+    for word in words:
+        if len(current_chunk) + len(word) < max_length:
+            current_chunk += word
+        else:
+            chunks.append(current_chunk)
+            current_chunk = word
+    if current_chunk:
+        chunks.append(current_chunk)
+    return chunks
+
+def rate_quality(text):
+    """
+    对翻译后的文本进行质量评价，返回最频繁的评分结果
+    """
+    chunks = split_text(text)
+    results = []
+    for chunk in chunks:
+        result = rating_pipe(chunk)[0]
+        label_map = {"LABEL_0": "Poor", "LABEL_1": "Neutral", "LABEL_2": "Good"}
+        results.append(label_map.get(result["label"], "Unknown"))
+    return max(set(results), key=results.count)
+
+def main():
+    # 设置页面配置和图标，吸引用户注意
+    st.set_page_config(page_title="Cantonese Audio Analyzer", page_icon="🎙️")
+    
+    # 自定义 CSS 样式（引用 Comic Neue 字体，并设置背景渐变、边框圆角等效果）
+    st.markdown("""
+    <style>
+    @import url('https://fonts.googleapis.com/css2?family=Comic+Neue:wght@700&display=swap');
+    .header {
+        background: linear-gradient(45deg, #FF9A6C, #FF6B6B);
+        border-radius: 15px;
+        padding: 2rem;
+        text-align: center;
+        box-shadow: 0 4px 6px rgba(0, 0, 0, 0.1);
+        margin-bottom: 2rem;
+    }
+    .subtitle {
+        font-family: 'Comic Neue', cursive;
+        color: #4B4B4B;
+        font-size: 1.2rem;
+        margin: 1rem 0;
+        padding: 1rem;
+        background: rgba(255,255,255,0.9);
+        border-radius: 10px;
+        border-left: 5px solid #FF6B6B;
+    }
+    </style>
+    """, unsafe_allow_html=True)
+    
+    # 页面头部展示
+    st.markdown("""
+    <div class="header">
+        <h1 style='margin:0;'>🎙️ Cantonese Audio Analyzer</h1>
+        <p style='color: white; font-size: 1.2rem;'>Transcribe, translate, and evaluate your audio magic!</p>
+    </div>
+    """, unsafe_allow_html=True)
+    
+    # 上传音频文件（支持 wav、mp3、flac 格式）
+    uploaded_file = st.file_uploader("👉🏻 Upload your Cantonese audio file here...", type=["wav", "mp3", "flac"])
+    
+    if uploaded_file is not None:
+        # 直接播放上传的音频
+        st.audio(uploaded_file, format="audio/wav")
+        # 将上传的文件保存为临时文件
+        temp_audio_path = "uploaded_audio.wav"
+        with open(temp_audio_path, "wb") as f:
+            f.write(uploaded_file.getbuffer())
+        
+        # 初始化进度条和状态提示区域
+        progress_bar = st.progress(0)
+        status_container = st.empty()
+        
+        # Step 1: 音频转录
+        status_container.info("🔮 **Step 1/3**: Transcribing audio...")
+        transcript = transcribe_audio(temp_audio_path)
+        progress_bar.progress(33)
+        st.write("**Transcript:**", transcript)
+        
+        # Step 2: 翻译转录内容
+        status_container.info("📚 **Step 2/3**: Translating transcript...")
+        translated_text = translate(transcript)
+        progress_bar.progress(66)
+        st.write("**Translation:**", translated_text)
+        
+        # Step 3: 音频质量评分
+        status_container.info("🎵 **Step 3/3**: Evaluating audio quality...")
+        quality_rating = rate_quality(translated_text)
+        progress_bar.progress(100)
+        st.write("**Quality Rating:**", quality_rating)
+        
+        # 处理完成后删除临时文件
+        os.remove(temp_audio_path)
+
+if __name__ == "__main__":
+    main()