2 citations · 2 across the 5 of their papers we have counts for
6 papers
Unsupervised Discriminative Learning of Sounds for Audio Event Classification
Sascha Hornauer, Ke Li, Stella X. Yu +2
Recent progress in network-based audio event classification has shown the benefit of pre-training models on visual data such as ImageNet. While this process allows knowledge transf…
A Parallelizable Lattice Rescoring Strategy with Neural Language Models
Ke Li, Daniel Povey, Sanjeev Khudanpur
This paper proposes a parallel computation strategy and a posterior-based lattice expansion algorithm for efficient lattice rescoring with neural language models (LMs) for automati…
Neural Language Modeling With Implicit Cache Pointers
Ke Li, Daniel Povey, Sanjeev Khudanpur
A cache-inspired approach is proposed for neural language models (LMs) to improve long-range dependency and better predict rare words from long contexts. This approach is a simpler…
Efficient MDI Adaptation for n-gram Language Models
Ruizhe Huang, Ke Li, Ashish Arora +2
This paper presents an efficient algorithm for n-gram language model adaptation under the minimum discrimination information (MDI) principle, where an out-of-domain language model…
The JHU Multi-Microphone Multi-Speaker ASR System for the CHiME-6 Challenge
Ashish Arora, Desh Raj, Aswin Shanmugam Subramanian +7
This paper summarizes the JHU team's efforts in tracks 1 and 2 of the CHiME-6 challenge for distant multi-microphone conversational speech diarization and recognition in everyday h…
Speaker Adaptation for End-to-End CTC Models
Ke Li, Jinyu Li, Yong Zhao +2
We propose two approaches for speaker adaptation in end-to-end (E2E) automatic speech recognition systems. One is Kullback-Leibler divergence (KLD) regularization and the other is…