64 citations · 99 across the 12 of their papers we have counts for
3 papers · 1 filter
2-bit Conformer quantization for automatic speech recognition
Oleg Rybakov, Phoenix Meadowlark, Shaojin Ding +4
Large speech models are rapidly gaining traction in research community. As a result, model compression has become an important topic, so that these models can fit in memory and be…
RAND: Robustness Aware Norm Decay For Quantized Seq2seq Models
David Qiu, David Rim, Shaojin Ding +2
With the rapid increase in the size of neural networks, model compression has become an important area of research. Quantization is an effective technique at decreasing the model s…
Sharing Low Rank Conformer Weights for Tiny Always-On Ambient Speech Recognition Models
Steven M. Hernandez, Ding Zhao, Shaojin Ding +5
Continued improvements in machine learning techniques offer exciting new opportunities through the use of larger models and larger training datasets. However, there is a growing ne…