Initial commit: V1

asr.py

@@ -0,0 +1,167 @@
+"""
+asr.py - ASR 强制对齐模块（简化版）
+使用 Qwen3-ForcedAligner 对齐音频和文本
+模型路径通过 config.py 中的绝对路径指向
+"""
+
+import os
+import json
+import re
+
+
+def _detect_language(text: str) -> str:
+    """根据文本字符分布自动检测语言"""
+    if not text:
+        return "English"
+    # 统计非 ASCII 字符（中文等）
+    non_ascii = sum(1 for c in text if ord(c) >= 0x4e00)
+    ratio = non_ascii / len(text)
+    return "Chinese" if ratio > 0.1 else "English"
+
+
+def run_asr(workspace: str, language: str = None) -> dict:
+    """
+    执行 ASR 强制对齐
+
+    Args:
+        workspace: 工作区路径（含 article.txt 和 voice.mp3）
+
+    Returns:
+        dict: {"audio": str, "text": str, "segments": list}
+    """
+    from config import ASR_MODEL_DIR
+    from qwen_asr import Qwen3ForcedAligner
+
+    audio_path = os.path.join(workspace, "voice.mp3")
+    text_path = os.path.join(workspace, "article.txt")
+    output_path = os.path.join(workspace, "result.json")
+
+    # 验证路径
+    if not os.path.exists(ASR_MODEL_DIR):
+        raise FileNotFoundError(f"ASR 模型路径不存在: {ASR_MODEL_DIR}")
+    if not os.path.exists(audio_path):
+        raise FileNotFoundError(f"音频文件不存在: {audio_path}")
+    if not os.path.exists(text_path):
+        raise FileNotFoundError(f"文本文件不存在: {text_path}")
+
+    # 读取文本
+    with open(text_path, 'r', encoding='utf-8') as f:
+        text = f.read().strip()
+
+    print(f"[ASR] 文本长度: {len(text)} 字符")
+    print(f"[ASR] 音频文件: {audio_path}")
+    print(f"[ASR] 模型路径: {ASR_MODEL_DIR}")
+
+    # 加载模型
+    print("[ASR] 正在加载模型...")
+    aligner = Qwen3ForcedAligner.from_pretrained(
+        ASR_MODEL_DIR,
+        local_files_only=True,
+        device_map="cpu"
+    )
+    print("[ASR] 模型加载成功")
+
+    # 自动检测语言（如果未指定）
+    if language is None:
+        language = _detect_language(text)
+    print(f"[ASR] 检测语言: {language}")
+
+    # 运行对齐
+    print("[ASR] 正在对齐...")
+    results = aligner.align(
+        audio=audio_path,
+        text=text,
+        language=language
+    )
+
+    # 整理结果
+    segments = []
+    for result in results:
+        for item in result.items:
+            segments.append({
+                "text": item.text,
+                "start": round(item.start_time, 3),
+                "end": round(item.end_time, 3)
+            })
+
+    output_data = {
+        "audio": audio_path,
+        "text": text,
+        "segments": segments
+    }
+
+    with open(output_path, 'w', encoding='utf-8') as f:
+        json.dump(output_data, f, ensure_ascii=False, indent=2)
+
+    print(f"[ASR] 完成，共 {len(segments)} 个片段，保存到 {output_path}")
+    return output_data
+
+
+def match_scenes_to_audio(workspace: str) -> dict:
+    """
+    将 ASR segments 与 scene_plan 的 scenes 做文本匹配，
+    给每个 scene 写入 start_time / end_time，并更新 scene_plan.json。
+
+    Returns:
+        dict: 更新后的 scene_plan（带时间信息）
+    """
+    from make_video import load_scene_plan, load_asr_result, assign_scenes_to_segments
+    from scene_plan import _get_audio_duration
+
+    plan_path = os.path.join(workspace, "scene_plan.json")
+    result_path = os.path.join(workspace, "result.json")
+    audio_path = os.path.join(workspace, "voice.mp3")
+
+    if not os.path.exists(plan_path):
+        raise FileNotFoundError(f"scene_plan.json 不存在: {plan_path}")
+    if not os.path.exists(result_path):
+        raise FileNotFoundError(f"result.json 不存在: {result_path}")
+    if not os.path.exists(audio_path):
+        raise FileNotFoundError(f"voice.mp3 不存在: {audio_path}")
+
+    scene_plan = load_scene_plan(workspace)
+    asr_result = load_asr_result(workspace)
+
+    audio_duration = _get_audio_duration(audio_path)
+    if audio_duration is None:
+        raise RuntimeError(f"无法获取音频时长: {audio_path}")
+
+    # 恢复每个场景的文本用于 ASR 匹配
+    # 优先用 text 字段（原文片段），兼容旧 lines 字段
+    for scene in scene_plan["scenes"]:
+        text_val = scene.get("text", "")
+        lines_val = scene.get("lines", "")
+        raw = text_val or lines_val or ""
+        if isinstance(raw, str) and raw:
+            # 按句号分句供匹配
+            scene["lines"] = [s.strip() for s in raw.split("。") if s.strip()]
+        else:
+            scene["lines"] = []
+
+    # 复用 make_video 的匹配逻辑
+    timeline = assign_scenes_to_segments(
+        scene_plan["scenes"], asr_result.get("segments", []), audio_duration
+    )
+
+    # 写回 scene_plan
+    for item in timeline:
+        scene_id = item["scene_id"]
+        for scene in scene_plan["scenes"]:
+            if scene["scene_id"] == scene_id:
+                scene["start_time"] = round(item["start"], 3)
+                scene["end_time"] = round(item["end"], 3)
+                break
+
+    with open(plan_path, 'w', encoding='utf-8') as f:
+        json.dump(scene_plan, f, ensure_ascii=False, indent=2)
+
+    print(f"[匹配] 完成，已将时间信息写入 {plan_path}")
+    for item in timeline:
+        dur = item["end"] - item["start"]
+        print(f"  Scene {item['scene_id']:2d}: {item['start']:6.2f}s - {item['end']:6.2f}s ({dur:.2f}s)")
+
+    return scene_plan
+
+
+if __name__ == "__main__":
+    run_asr(os.path.join(os.path.dirname(__file__), "workspace", "1"))