ESPnet-EZ让语音模型微调和集成更简单，无需写繁琐脚本。
ESPnet-EZ: Python-only ESPnet for Easy Fine-tuning and Integration
- 用纯Python接口替代旧版Kaldi风格设计，告别复杂Bash脚本
- 微调语音模型时代码量减少2.7倍，依赖代码减少6.7倍
- 轻松对接PyTorch-Lightning、Hugging Face等主流框架
我们提出ESPnet-EZ，作为开源语音处理工具包ESPnet的扩展，旨在实现语音模型的快速便捷开发。该工具聚焦两个方面：(i) 在多种任务上轻松微调和推理现有ESPnet模型；(ii) 与PyTorch-Lightning、Hugging Face transformers及datasets、Lhotse等主流深度学习框架和数据集实现无缝集成。通过将原有继承自Kaldi的设计改为纯Python、无Bash的接口，显著降低新模型构建、调试和使用的工作量。例如，在微调语音基础模型时，相比原版ESPnet，ESPnet-EZ将新增代码量减少2.7倍，依赖代码量减少6.7倍，同时大幅减少Bash脚本依赖。ESPnet-EZ的代码库已公开。
原文摘要 · Abstract (English)
We introduce ESPnet-EZ, an extension of the open-source speech processing toolkit ESPnet, aimed at quick and easy development of speech models. ESPnet-EZ focuses on two major aspects: (i) easy fine-tuning and inference of existing ESPnet models on various tasks and (ii) easy integration with popular deep neural network frameworks such as PyTorch-Lightning, Hugging Face transformers and datasets, and Lhotse. By replacing ESPnet design choices inherited from Kaldi with a Python-only, Bash-free interface, we dramatically reduce the effort required to build, debug, and use a new model. For example, to fine-tune a speech foundation model, ESPnet-EZ, compared to ESPnet, reduces the number of newly written code by 2.7x and the amount of dependent code by 6.7x while dramatically reducing the Bash script dependencies. The codebase of ESPnet-EZ is publicly available.
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