This talk focuses on the fragmentation of speech model evaluation, examining the difficulties in horizontal comparison, experimental reproduction, and industrial adaptation caused by inconsistent evaluation frameworks, metrics, processes, and interfaces. It discusses the core modules of a general speech evaluation framework, including process normalization, metric unification, interface standardization, and reproducible experiment protocols. Furthermore, it explores the construction model, sharing mechanisms, iteration rules, and collaborative governance schemes of an open speech evaluation community, providing an overall roadmap for co-building public evaluation infrastructure.

This talk takes speech research challenges as the entry point, analyzing how competition rules, scoring mechanisms, task designs, and public baselines in challenges drive industry standardization. It summarizes the value of challenges in unifying evaluation baselines, standardizing model evaluation paradigms, exposing weaknesses in complex scenarios, and promoting open evaluation deployment. It also discusses how public competitions can advance the unification of evaluation rules and the normalization of evaluation processes, building a fair, open, and comparable model evaluation ecosystem.

This talk focuses on the standardized construction and open sharing of open-source speech evaluation datasets. Addressing current issues such as single-scenario datasets, uneven quality, inconsistent annotation standards, and insufficient data in complex scenarios, it discusses dataset construction specifications, annotation standards, quality verification systems, and sharing mechanisms for general scenarios, complex acoustic scenarios, and complex linguistic scenarios. It clarifies the foundational supporting role of standardized datasets in unified evaluation, open comparison, and model robustness assessment.

This talk addresses the rapid iteration of open-source speech models, analyzing—from the full chain of model R&D, fine-tuning iteration, fair comparison, and industrial deployment—how inconsistent evaluation standards constrain model capability judgment, R&D path selection, and deployment decision-making. It explores how standardized and open evaluation systems can support unified baseline evaluation, controllable training comparison, model capability grading, and differentiated capability assessment, promoting the formation of a closed-loop mechanism of "R&D—Evaluation—Iteration—Open Source—Deployment."