3 papers
cs.CL2021
Self-Normalized Importance Sampling for Neural Language Modeling
Zijian Yang, Yingbo Gao, Alexander Gerstenberger +3
To mitigate the problem of having to traverse over the full vocabulary in the softmax normalization of a neural language model, sampling-based training criteria are proposed and in…
cs.CL2021
Conformer-based Hybrid ASR System for Switchboard Dataset
Mohammad Zeineldeen, Jingjing Xu, Christoph Lüscher +4
The recently proposed conformer architecture has been successfully used for end-to-end automatic speech recognition (ASR) architectures achieving state-of-the-art performance on di…
cs.CL2021
On Sampling-Based Training Criteria for Neural Language Modeling
Yingbo Gao, David Thulke, Alexander Gerstenberger +3
As the vocabulary size of modern word-based language models becomes ever larger, many sampling-based training criteria are proposed and investigated. The essence of these sampling…