USM-Lite: Quantization and Sparsity Aware Fine-tuning for Speech Recognition with Universal Speech Models

no code implementations • 13 Dec 2023 • Shaojin Ding, David Qiu, David Rim, Yanzhang He, Oleg Rybakov, Bo Li, Rohit Prabhavalkar, Weiran Wang, Tara N. Sainath, Zhonglin Han, Jian Li, Amir Yazdanbakhsh, Shivani Agrawal

We conducted extensive experiments with a 2-billion parameter USM on a large-scale voice search dataset to evaluate our proposed method.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +3

2-bit Conformer quantization for automatic speech recognition

no code implementations • 26 May 2023 • Oleg Rybakov, Phoenix Meadowlark, Shaojin Ding, David Qiu, Jian Li, David Rim, Yanzhang He

With the large-scale training data, we obtain a 2-bit Conformer model with over 40% model size reduction against the 4-bit version at the cost of 17% relative word error rate degradation

Automatic Speech Recognition Automatic Speech Recognition (ASR) +3

RAND: Robustness Aware Norm Decay For Quantized Seq2seq Models

no code implementations • 24 May 2023 • David Qiu, David Rim, Shaojin Ding, Oleg Rybakov, Yanzhang He

With the rapid increase in the size of neural networks, model compression has become an important area of research.

Machine Translation Model Compression +3

Improving Facial Analysis and Performance Driven Animation through Disentangling Identity and Expression

no code implementations • 27 Dec 2015 • David Rim, Sina Honari, Md. Kamrul Hasan, Chris Pal

We use a weakly-supervised approach in which identity labels are used to learn the different factors of variation linked to identity separately from factors related to expression.

Emotion Recognition Point Tracking