Please use this identifier to cite or link to this item:
https://hdl.handle.net/10356/156701
Title: | Deploying ASR system for scalability and robustness on AWS | Authors: | Lee, Kai Shern | Keywords: | Engineering::Computer science and engineering | Issue Date: | 2022 | Publisher: | Nanyang Technological University | Source: | Lee, K. S. (2022). Deploying ASR system for scalability and robustness on AWS. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/156701 | Abstract: | The project aims to provide a robust solution for deploying automatic speech recognition (ASR) system on Cloud. The solutions will enable the system to be provisioned at a lower cost and also simplify the process of deploying systems on Amazon Web Service(AWS). The solutions are implemented based on the concept of Infrastructure as Code (IaC). This enables the process of building and destroying speech recognition system to be completed in minimum steps which come in convenient at the development stage. This report will introduce the solutions in terms of the architecture diagram, comparison over different services, frameworks, and tools. The report will demonstrate the provision of the infrastructure of ASR on AWS using Terraform. | URI: | https://hdl.handle.net/10356/156701 | Fulltext Permission: | restricted | Fulltext Availability: | With Fulltext |
Appears in Collections: | SCSE Student Reports (FYP/IA/PA/PI) |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
FYP_AmendedFinalReport_LeeKaiShern.pdf Restricted Access | 1.14 MB | Adobe PDF | View/Open |
Page view(s)
17
Updated on May 15, 2022
Download(s)
1
Updated on May 15, 2022
Google ScholarTM
Check
Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.