Conformer-Based Speech Recognition On Extreme Edge-Computing Devices

Mingbin Xu, Alex Jin, Sicheng Wang, Mu Su, Tim Ng, Henry Mason, Shiyi Han, Zhihong Lei, Yaqiao Deng, Zhen Huang, Mahesh Krishnamoorthy


Abstract
With increasingly more powerful compute capabilities and resources in today’s devices, traditionally compute-intensive automatic speech recognition (ASR) has been moving from the cloud to devices to better protect user privacy. However, it is still challenging to implement on-device ASR on resource-constrained devices, such as smartphones, smart wearables, and other small home automation devices. In this paper, we propose a series of model architecture adaptions, neural network graph transformations, and numerical optimizations to fit an advanced Conformer based end-to-end streaming ASR system on resource-constrained devices without accuracy degradation. We achieve over 5.26 times faster than realtime (0.19 RTF) speech recognition on small wearables while minimizing energy consumption and achieving state-of-the-art accuracy. The proposed methods are widely applicable to other transformer-based server-free AI applications. In addition, we provide a complete theory on optimal pre-normalizers that numerically stabilize layer normalization in any Lp-norm using any floating point precision.
Anthology ID:
2024.naacl-industry.12
Volume:
Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 6: Industry Track)
Month:
June
Year:
2024
Address:
Mexico City, Mexico
Editors:
Yi Yang, Aida Davani, Avi Sil, Anoop Kumar
Venue:
NAACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
131–139
Language:
URL:
https://aclanthology.org/2024.naacl-industry.12
DOI:
10.18653/v1/2024.naacl-industry.12
Bibkey:
Cite (ACL):
Mingbin Xu, Alex Jin, Sicheng Wang, Mu Su, Tim Ng, Henry Mason, Shiyi Han, Zhihong Lei, Yaqiao Deng, Zhen Huang, and Mahesh Krishnamoorthy. 2024. Conformer-Based Speech Recognition On Extreme Edge-Computing Devices. In Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 6: Industry Track), pages 131–139, Mexico City, Mexico. Association for Computational Linguistics.
Cite (Informal):
Conformer-Based Speech Recognition On Extreme Edge-Computing Devices (Xu et al., NAACL 2024)
Copy Citation:
PDF:
https://aclanthology.org/2024.naacl-industry.12.pdf