A Simplified Fully Quantized Transformer for End-to-end Speech Recognition

9 November 2019

Papers citing "A Simplified Fully Quantized Transformer for End-to-end Speech Recognition"

4 / 4 papers shown

Title
USM-Lite: Quantization and Sparsity Aware Fine-tuning for Speech Recognition with Universal Speech Models Shaojin Ding David Qiu David Rim Yanzhang He Oleg Rybakov ... Tara N. Sainath Zhonglin Han Jian Li Amir Yazdanbakhsh Shivani Agrawal MQ 31 9 0 13 Dec 2023
Training Acceleration of Low-Rank Decomposed Networks using Sequential Freezing and Rank Quantization Habib Hajimolahoseini Walid Ahmed Yang Liu OffRL MQ 19 6 0 07 Sep 2023
Transformers in Speech Processing: A Survey S. Latif Aun Zaidi Heriberto Cuayáhuitl Fahad Shamshad Moazzam Shoukat Junaid Qadir 42 47 0 21 Mar 2023
4-bit Conformer with Native Quantization Aware Training for Speech Recognition Shaojin Ding Phoenix Meadowlark Yanzhang He Lukasz Lew Shivani Agrawal Oleg Rybakov MQ 31 32 0 29 Mar 2022