新增 Silero VAD 时间轴评分对比与可复现推理

2026-10-22 21:25:47 +08:00
parent 43724c13e4
commit c9b618e634
14 changed files with 379 additions and 14 deletions
@@ -0,0 +1,3 @@
+.venv/
+__pycache__/
+models/
@@ -0,0 +1 @@
+3.11
@@ -0,0 +1,25 @@
+# Silero VAD 时间轴基线
+
+本机 Apple M4 Mac mini / CPU，独立 Python 3.11 uv 环境；依赖锁见 uv.lock。ONNX Runtime CPU 单线程，不修改 MaAI 和 Smart Turn 环境。环境的实际版本、模型和录音 SHA256、标注文件 SHA256 记入 results/score-timeline.json。
+
+曲线为 `1 - speech_probability`，高分仅表示当前用户声道更可能未发声，不是语义话轮结束概率。不加静音时长阈值、hangover 或服务层超时策略。
+
+输入为韩泰六通原录音的用户左声道（channel 0），原生 8 kHz，int16 / 32768；同时支持 16 kHz。每个完整 32 ms 帧执行一次，使用 4 ms 过去上下文并连续保留循环状态，每通录音开始清零。分数的时间戳是帧末：只有整帧收到后才可用。不重采样，不读取标注转写，不因标注点重置，不补齐末尾残帧，不使用未来音频。
+
+44 个标注点取该时刻之前最后一个完整帧的输出，最多陈旧 <32 ms。原始 speech 分数和可用时刻见 results/checkpoints.csv；不覆盖人工标注或其他模型结果。脚本对每通录音重放前 50 帧，验证短前缀与完整回放一致。
+
+权重使用已安装的 `pipecat-ai==1.12.0` 发行包所带 Silero ONNX，SHA256 为 `597d30b3ec076608d059477bb14cfeffdf951bf5cae370d38f65d33bbfe82004`；发行包未标明 Silero 上游版本，故按权重哈希识别，不猜测版本。状态接口参考 [Silero 官方实现](https://github.com/snakers4/silero-vad/blob/master/src/silero_vad/utils_vad.py)。权重不加入 Git。
+
+从项目根目录恢复及运行：
+
+```bash
+cd experiments/silero-vad
+uv sync --locked
+# 将上述 SHA256 的 Silero ONNX 放入 models/silero_vad.onnx。
+# 本项目已有 Smart Turn 环境时，可从该固定发行包复制：
+mkdir -p models
+cp ../smart-turn-v3.2/.venv/lib/python3.11/site-packages/pipecat/audio/vad/data/silero_vad.onnx models/silero_vad.onnx
+uv run --locked python export_timeline.py
+```
+
+网页读取随项目提交的 results/score-timeline.json 即可显示，无需在网页进程加载模型。修改录音或判断点后需重新生成；接口会校验录音 SHA256。
@@ -0,0 +1,104 @@
+"""Causal Silero ONNX baseline: frame ends mark when scores become available."""
+import bisect
+import csv
+import hashlib
+import importlib.metadata
+import json
+import platform
+import sys
+from pathlib import Path
+
+import numpy as np
+import onnxruntime as ort
+import soundfile as sf
+
+HERE = Path(__file__).resolve().parent
+ROOT = HERE.parents[1]
+WEIGHT_SHA256 = '597d30b3ec076608d059477bb14cfeffdf951bf5cae370d38f65d33bbfe82004'
+
+
+class SileroStream:
+    """Same state/context contract as the official Silero ONNX wrapper."""
+    def __init__(self, session, sr):
+        if sr not in (8000, 16000):
+            raise ValueError(f'Unsupported sample rate: {sr}')
+        self.session, self.sr = session, sr
+        self.frame = sr * 32 // 1000
+        self.context = np.zeros((1, sr * 4 // 1000), dtype=np.float32)
+        self.state = np.zeros((2, 1, 128), dtype=np.float32)
+
+    def step(self, samples):
+        if len(samples) != self.frame:
+            raise ValueError('Only complete 32 ms frames may be submitted')
+        x = np.concatenate([self.context, samples[None, :]], axis=1)
+        output, self.state = self.session.run(None, {
+            'input': x, 'state': self.state, 'sr': np.array(self.sr, dtype=np.int64)})
+        self.context = x[:, -self.context.shape[1]:].copy()
+        speech = float(output.item())
+        if not np.isfinite(speech) or not 0 <= speech <= 1:
+            raise ValueError('Invalid model output')
+        return speech
+
+
+def main():
+    weight = HERE / 'models/silero_vad.onnx'
+    if hashlib.sha256(weight.read_bytes()).hexdigest() != WEIGHT_SHA256:
+        raise ValueError('Silero model checksum mismatch')
+    options = ort.SessionOptions()
+    options.intra_op_num_threads = options.inter_op_num_threads = 1
+    session = ort.InferenceSession(str(weight), sess_options=options, providers=['CPUExecutionProvider'])
+    label_path = ROOT / 'labels/EOT标注/工作数据/eot_labels.csv'
+    with label_path.open(encoding='utf-8-sig', newline='') as f:
+        labels = list(csv.DictReader(f))
+    calls, checks = [], []
+    for call in sorted({r['call_id'] for r in labels}):
+        path = ROOT / 'data/韩泰机器人抢话/音频' / f'{call}.mp3'
+        pcm, sr = sf.read(path, dtype='int16', always_2d=True)
+        stream = SileroStream(session, sr)  # reset only between recordings
+        user = np.ascontiguousarray(pcm[:, 0].astype(np.float32) / 32768.)
+        points = []
+        for end in range(stream.frame, len(user) + 1, stream.frame):
+            speech = stream.step(user[end-stream.frame:end])
+            points.append([end * 1000 // sr, round(1 - speech, 7)])
+        times = [p[0] for p in points]
+        checkpoints = []
+        for row in labels:
+            if row['call_id'] != call:
+                continue
+            decision = int(row['decision_ms'])
+            if decision > len(user) * 1000 / sr:
+                raise ValueError('Annotation beyond recording')
+            index = bisect.bisect_right(times, decision) - 1
+            if index < 0:
+                continue  # No complete frame is available yet; never invent zero.
+            available, score = points[index]
+            checkpoints.append([decision, score])
+            checks.append(dict(call_id=call, decision_ms=decision, available_ms=available,
+                               non_speech_score=score, speech_score=round(1-score, 7)))
+        calls.append(dict(call_id=call, audio_path=f'韩泰机器人抢话/音频/{call}.mp3',
+            audio_sha256=hashlib.sha256(path.read_bytes()).hexdigest(), duration_ms=round(len(user)*1000/sr,3),
+            sample_rate=sr, channel=0, points=points, checkpoints=sorted(checkpoints)))
+        # A fresh stream reproduces a prefix without any later samples.
+        witness = SileroStream(session, sr)
+        for index in range(min(50, len(points))):
+            end = (index+1)*stream.frame
+            assert round(1-witness.step(user[end-stream.frame:end]),7) == points[index][1]
+        print(f'{call}: {len(points)} frames, {len(checkpoints)} checkpoints; prefix witness passed', flush=True)
+    output = dict(schema_version=1, model='silero_vad', name='Silero VAD',
+        score='1 - speech_probability (non-speech baseline, not semantic EOT)', sample_interval_ms=32,
+        method='CPU, one thread. User channel 0, native 8/16 kHz, int16 / 32768. Sequential complete 32ms frames plus 4ms past context; recurrent state reset per call. Timestamp is frame END. No future audio, resampling, silence timeout, hangover or annotation text. Checkpoints hold last available complete frame; trailing partial frame is not padded.',
+        model_source='Silero ONNX bundled with pipecat-ai==1.12.0; upstream https://github.com/snakers4/silero-vad',
+        model_sha256=WEIGHT_SHA256, annotation_sha256=hashlib.sha256(label_path.read_bytes()).hexdigest(),
+        script_sha256=hashlib.sha256(Path(__file__).read_bytes()).hexdigest(),
+        environment=dict(machine=platform.platform(), architecture=platform.machine(), python=sys.version,
+            dependencies={p:importlib.metadata.version(p) for p in ['numpy','onnxruntime','soundfile']},
+            provider='CPUExecutionProvider', threads=1), calls=calls)
+    out = HERE/'results'
+    out.mkdir(exist_ok=True)
+    (out/'score-timeline.json').write_text(json.dumps(output,ensure_ascii=False,separators=(',',':'))+'\n')
+    with (out/'checkpoints.csv').open('w',encoding='utf-8',newline='') as f:
+        writer=csv.DictWriter(f,fieldnames=list(checks[0]));writer.writeheader();writer.writerows(checks)
+
+
+if __name__ == '__main__':
+    main()
@@ -0,0 +1,5 @@
+[project]
+name = "silero-vad-timeline"
+version = "0.1.0"
+requires-python = ">=3.11,<3.12"
+dependencies = ["numpy==2.2.6", "onnxruntime==1.24.4", "soundfile==0.13.1"]
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