788 citations · 1.4k across the 24 of their papers we have counts for
5 papers · 1 filter
Efficient Adapters for Giant Speech Models
Nanxin Chen, Izhak Shafran, Yu Zhang +4
Large pre-trained speech models are widely used as the de-facto paradigm, especially in scenarios when there is a limited amount of labeled data available. However, finetuning all…
How to Estimate Model Transferability of Pre-Trained Speech Models?
Zih-Ching Chen, Chao-Han Huck Yang, Bo Li +6
In this work, we introduce a "score-based assessment" framework for estimating the transferability of pre-trained speech models (PSMs) for fine-tuning target tasks. We leverage upo…
Noise2Music: Text-conditioned Music Generation with Diffusion Models
Qingqing Huang, Daniel S. Park, Tao Wang +12
We introduce Noise2Music, where a series of diffusion models is trained to generate high-quality 30-second music clips from text prompts. Two types of diffusion models, a generator…
Google USM: Scaling Automatic Speech Recognition Beyond 100 Languages
Yu Zhang, Wei Han, James Qin +24
We introduce the Universal Speech Model (USM), a single large model that performs automatic speech recognition (ASR) across 100+ languages. This is achieved by pre-training the enc…
From English to More Languages: Parameter-Efficient Model Reprogramming for Cross-Lingual Speech Recognition
Chao-Han Huck Yang, Bo Li, Yu Zhang +4
In this work, we propose a new parameter-efficient learning framework based on neural model reprogramming for cross-lingual speech recognition, which can \textbf{re-purpose} well-t…