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OpenWakeWord.AXERA

keyword-spotting
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config.json 标准化 + README frontmatter（HF 模型卡规范）

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by inoryQwQ - opened
base: refs/heads/main
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from: refs/pr/2
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Files changed (14) hide show
  1. README.md +11 -0
  2. config.json +18 -1
  3. models/630C/openwakeword__alexa_v0.1.axmodel +2 -2
  4. models/630C/openwakeword__hey_jarvis_v0.1.axmodel +2 -2
  5. models/630C/openwakeword__hey_mycroft_v0.1.axmodel +2 -2
  6. models/630C/openwakeword__hey_rhasspy_v0.1.axmodel +2 -2
  7. models/630C/openwakeword__timer_v0.1.axmodel +2 -2
  8. models/630C/openwakeword__weather_v0.1.axmodel +2 -2
  9. models/650/openwakeword__alexa_v0.1.axmodel +2 -2
  10. models/650/openwakeword__hey_jarvis_v0.1.axmodel +2 -2
  11. models/650/openwakeword__hey_mycroft_v0.1.axmodel +2 -2
  12. models/650/openwakeword__hey_rhasspy_v0.1.axmodel +2 -2
  13. models/650/openwakeword__timer_v0.1.axmodel +2 -2
  14. models/650/openwakeword__weather_v0.1.axmodel +2 -2
README.md CHANGED
@@ -123,3 +123,14 @@ THRESHOLD=0.5 bash cpp/run_batch_openwakeword_ax630c.sh
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  - [openWakeWord](https://github.com/dscripka/openWakeWord)
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  - [Pulsar2](https://pulsar2-docs.readthedocs.io/en/latest/pulsar2/introduction.html)
 
 
 
 
 
 
 
 
 
 
 
 
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  - [openWakeWord](https://github.com/dscripka/openWakeWord)
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  - [Pulsar2](https://pulsar2-docs.readthedocs.io/en/latest/pulsar2/introduction.html)
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+
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+ ## 已知问题与改进
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+
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+ - **mel 请使用 CPU 实现**：`melspectrogram.axmodel` 在 AX650/AX630C 板上输出全零
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+ （NPU 定点无法表达 mel 前端动态范围），`config.json` 默认 `mel_backend=numpy`，
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+ Python/C++ 运行时均使用 `config/openwakeword_mel_weights.npz` 在 CPU 计算。
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+ - **hey_rhasspy / weather 分类器已重新校准**：旧发布版在真实触发窗口得分退化
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+ （峰值窗口实测 0.005 / 0.79）；本版本改用包含 TTS 唤醒词正样本的校准集
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+ （高响应窗口采样），峰值窗口得分恢复到 0.97 / 1.00（alexa/mycroft/timer 保持 1.0）。
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+ 校准与编译配方见 https://github.com/AXERA-TECH/openWakeWord.AXERA/pull/1 。
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+
config.json CHANGED
@@ -1,7 +1,24 @@
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  {
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  "model_type": "keyword-spotting",
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  "source": "openWakeWord",
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- "target_hardware": "AX630C/AX650",
 
 
 
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  "runtime": "axengine",
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  "sample_rate": 16000,
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  "default_threshold": 0.5,
 
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  {
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  "model_type": "keyword-spotting",
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+ "pipeline_tag": "audio-classification",
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+ "library_name": "axengine",
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+ "tags": [
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+ "keyword-spotting",
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+ "wake-word",
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+ "audio-classification",
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+ "axera",
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+ "ax650",
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+ "ax630c"
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+ ],
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+ "license": "apache-2.0",
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+ "language": [
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+ "en"
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+ ],
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  "source": "openWakeWord",
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+ "target_hardware": [
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+ "AX650",
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+ "AX630C"
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+ ],
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  "runtime": "axengine",
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  "sample_rate": 16000,
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  "default_threshold": 0.5,
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