全局配置详解 (config.yaml)
OneASR 的所有服务行为、VAD 策略与引擎加载均由项目根目录下的 config.yaml 集中管理。
配置文件完整示例
yaml
# OneASR 统一配置文件
# 主 API Key(所有接口鉴权所需)
api_key: sk-oneasr-v1-p_L3kXm9QZ8sT2vA4wE7rY1u
# ASR Toolkit 音频预处理与 VAD 切片参数
ASR-Toolkit:
vad:
model: "silero_vad" # VAD 模型类型: silero_vad
threshold: 0.5 # 语音置信度阈值 (0.0~1.0)
min_speech_duration_ms: 250 # 最小语音段时长 (ms)
min_silence_duration_ms: 300 # 静音断句停顿时长 (ms)
padding_ms: 100 # 前后缓冲填充 (ms)
chunking:
target_chunk_duration: 6.0 # 理想字幕/切片时长 (秒)
max_chunk_duration: 8.0 # 最大切片时长硬上限 (秒)
min_pause_duration: 0.4 # 自然断句停顿阈值 (秒)
min_sentence_duration: 2.0 # 触发断句最小语义时长 (秒)
post_process:
remove_repeats: true # 过滤连续复读幻觉
normalize_text: true # 标点与空格规范化
# 引擎提供者配置
ASR-Providers:
# 1. 实时流式识别引擎 (Sherpa-ONNX Zipformer)
xasr:
enable: true
engine: xasr
load:
model_name: xasr-zh-en
tokens_path: models/chunk-160ms-model/tokens.txt
encoder_path: models/chunk-160ms-model/encoder-160ms.onnx
decoder_path: models/chunk-160ms-model/decoder-160ms.onnx
joiner_path: models/chunk-160ms-model/joiner-160ms.onnx
provider: cpu
sample_rate: 16000
decoding_method: greedy_search
properties:
categories:
- RealtimeASR
languages: zh, en
# 2. Faster-Whisper 文件转录
faster-whisper:
enable: true
engine: faster-whisper
load:
model_name: medium
model_path: models/faster-whisper-medium
device: cuda # 或 cpu
compute_type: float16 # 或 int8
properties:
categories:
- FileASR
languages: zh, en, ja, ko, fr, de, es, it, ru, pt