计划执行与检查节点
executing-plans
按既定实施计划完成工作,保持过程检查和反馈。
asr【效率与协作】Use for NeMo Speech ASR model selection, checkpoint loading, transcription, timestamps, streaming, fine-tuning, Lhotse batching, decoding customization, and ASR evaluation.
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Use this sub-skill for NeMo Speech automatic speech recognition tasks: selecting CTC/RNNT/TDT/Hybrid/AED Canary models, loading .nemo checkpoints or pretrained names, offline transcription, timestamps, long-audio inference, cache-aware or buffered streaming, fine-tuning, Lhotse/dynamic bucketing, tokenizer changes, decoding customization, confidence/LM/word boosting, and WER/BLEU-style ASR evaluation.
Route elsewhere when the task is primarily speaker diarization, VAD, or forced alignment; generic manifest sharding/tokenizer utilities; repository testing/formatting; or SpeechLM2/SALM duplex work. For generic data tooling, prefer ../data-tools/SKILL.md when present; for repo workflows, prefer ../repo-development/SKILL.md when present; for SpeechLM2, prefer ../speechlm2/SKILL.md when present.
references/workflows.md for task-specific command and Python patterns.references/api-reference.md before using model classes, transcribe(), timestamps, streaming pipeline builders, or decoding APIs.references/configuration.md before editing Hydra YAML, manifests, Lhotse settings, tokenizer changes, Canary prompts, LM/customization, or evaluation settings.references/troubleshooting.md when installs, CUDA/backends, Hydra overrides, manifests, Lhotse, streaming, decoding, or fine-tuning fail.scripts/check_asr_manifest.py validates small or large ASR JSONL manifests without importing NeMo, downloading models, touching audio contents, or writing outputs unless explicitly redirected by the caller.python scripts/check_asr_manifest.py train.jsonl --canary --min-duration 0.1 --max-duration 30.This sub-skill distills repository evidence from docs/source/asr/inference.rst, docs/source/asr/fine_tuning.rst, docs/source/asr/configs.rst, docs/source/asr/datasets.rst, docs/source/asr/asr_language_modeling_and_customization.rst, docs/source/dataloaders.rst, ASR example scripts/configs, ASR model/inference source, ASR tests, and the prior .claude/skills/nemo-speech-asr-finetune/SKILL.md. Runtime guidance is self-contained; do not require future agents to reopen those source files.