## 5 Conclusions  
As the window of ASEAN cooperation and communication in \"the Belt and Road Initiative\", the research and development of speech recognition for the Zhuang language can not only enrich the research of minority languages and cultures, but also contribute to the strengthening of communication between the Zhuang language and other languages in Guangxi and ASEAN countries. An online cloud-based platform was required to enhance linguistic communication. First, standard Zhuang news speeches were collected to build a database of 200 h of Zhuang speeches with annotations. Zhuang speech recognition was realized by an end-to-end automatic speech recognition neural network. Second, a machine translation model from Chinese to each country's language was established. Considering that edge-computing technology can reduce the transmission of a large amount of data, which can alleviate the pressure on network bandwidth. Finally, for the network's responsiveness to real-world needs, edge-computing techniques are applied to relieve network bandwidth pressure. An edge-computing private cloud system based on FPGA acceleration is proposed to improve model operation efficiency. The experiments show that the applicability of the model is verified, with satisfactory results in terms of accuracy and speed. SAformerNet-S outperforms the baseline model Conformer-S by 2.1%/3.3% on the dev/test dataset of the AISHELL-1 and has a recognition rate of 5.92% on the Zhuang language dataset. Compared to the baseline model, SAformerNet demonstrated a 26% improvement in training speed and a 29% average acceleration in inference time. In the practical implementation of the model, the computational delay for the MHSA and FFN modules has been reduced by 7.1 and 1.9 times, respectively, resulting in an overall average improvement in speech recognition result-to-terminal time of 20%. The scheme is suitable for small-scale remote natural language tasks in real-time applications. It serves as a prototype for a tool that supports remote Zhuang speech and multilingual conversational translation in mountainous areas. In future studies, more emphasis will be placed on the practical application of the system, and improvements will continue to be made in response to new problems. Conceptualization, Z.F. and X.Z. ; methodology, Z.F. ; software, Z.F. and R.L. ; validation, X.Z. and Z.B. ; investigation, M.H. and X.L. ; data curation, Z.F. ; writing--original draft preparation, Z.F. and T.D. ; writing--review and editing, Z.F. and X.Z. ; visualization, X.L. ; supervision, X.Z. and J.L. ; project administration, X.Z. and Z.B. All authors have read and agreed to the published version of the manuscript. This research was funded by the Science and Technology Key Projects of Guangxi Province, grant number 2020 AA21077007; the Innovation Project of Guangxi Graduate Education, grant number YCSW2022042; and the Guangxi New Engineering Research and Practice Project, grant number XGK2022003. Not applicable. **Data Availability Statement**: ASPEC, Asian Scientific Paper Excerpt Corpus, is constructed by the Japan Science and Technology Agency (JST) in collaboration with the National Institute of Information and Communications Technology (NICT); AISHELL-1, Part of the Hill Shell Chinese Mandarin open-source speech database. The data presented in this study are available on request from the corresponding author. The authors would like to express appreciation to the editors and reviewers for their valuable comments and suggestions. Relevant teachers from the School of Foreign Languages of Guangxi University are greatly appreciated for their valuable comments and suggestions. This work is supported by Guangxi Key Laboratory of Multimedia Communications and Network Technology, Guangxi, China, School of Computer, Electronics and Information, Guangxi University, Nanning, Guangxi, China. Author [PERSON] was employed by the company Guangxi Big White & Little Black Robots Co., Ltd., Nanning 530007, China.