Work-in-progress: Computation offloading of acoustic model for client-edge-based speech-recognition

Young Min Lee, Joon Sung Yang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Speech recognition technology combined with artificial intelligence represents a quantum leap more accurate than past pattern recognition methods. And server-based system support for scalability, virtualization and huge amounts of unlimited storage resources that greatly contributed to the improvement of the accuracy of its prediction. However, the implementation of server-oriented reforms led to enormous latency and connectivity problems. Therefore, we propose a novel client-edge speech recognition system to enhance latency by using what we call semi-offloading technology. This proposal is promising big performance gains by offloading computing power-dependent tasks to edge nodes and processing throughput-dependent tasks by a client. The merit of semi-offloading as well as a division of workload allows for parallelism and re-ordering among the process. The experimental results show that, 23%∼62% improvement in response time.

Original languageEnglish
Title of host publicationProceedings of the International Conference on Compliers, Architectures and Synthesis for Embedded Systems Companion, CASES 2019
PublisherAssociation for Computing Machinery, Inc
ISBN (Electronic)9781450369251
DOIs
Publication statusPublished - 2019 Oct 13
Event2019 International Conference on Compliers, Architectures and Synthesis for Embedded Systems, CASES 2019 - New York, United States
Duration: 2019 Oct 132019 Oct 18

Publication series

NameProceedings of the International Conference on Compliers, Architectures and Synthesis for Embedded Systems Companion, CASES 2019

Conference

Conference2019 International Conference on Compliers, Architectures and Synthesis for Embedded Systems, CASES 2019
CountryUnited States
CityNew York
Period19/10/1319/10/18

All Science Journal Classification (ASJC) codes

  • Hardware and Architecture
  • Control and Optimization

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    Lee, Y. M., & Yang, J. S. (2019). Work-in-progress: Computation offloading of acoustic model for client-edge-based speech-recognition. In Proceedings of the International Conference on Compliers, Architectures and Synthesis for Embedded Systems Companion, CASES 2019 [a1] (Proceedings of the International Conference on Compliers, Architectures and Synthesis for Embedded Systems Companion, CASES 2019). Association for Computing Machinery, Inc. https://doi.org/10.1145/3349569.3351534