8 citations · 8 across the 5 of their papers we have counts for
5 papers
Deferred NAM: Low-latency Top-K Context Injection via Deferred Context Encoding for Non-Streaming ASR
Zelin Wu, Gan Song, Christopher Li +9
Contextual biasing enables speech recognizers to transcribe important phrases in the speaker's context, such as contact names, even if they are rare in, or absent from, the trainin…
Hierarchical Recurrent Adapters for Efficient Multi-Task Adaptation of Large Speech Models
Tsendsuren Munkhdalai, Youzheng Chen, Khe Chai Sim +3
Parameter efficient adaptation methods have become a key mechanism to train large pre-trained models for downstream tasks. However, their per-task parameter overhead is considered…
Contextual Biasing with the Knuth-Morris-Pratt Matching Algorithm
Weiran Wang, Zelin Wu, Diamantino Caseiro +10
Contextual biasing refers to the problem of biasing the automatic speech recognition (ASR) systems towards rare entities that are relevant to the specific user or application scena…
Improving Speech Recognition for African American English With Audio Classification
Shefali Garg, Zhouyuan Huo, Khe Chai Sim +11
Automatic speech recognition (ASR) systems have been shown to have large quality disparities between the language varieties they are intended or expected to recognize. One way to m…
Reasoning with Memory Augmented Neural Networks for Language Comprehension
Tsendsuren Munkhdalai, Hong Yu
Hypothesis testing is an important cognitive process that supports human reasoning. In this paper, we introduce a computational hypothesis testing approach based on memory augmente…