Deep Belief Networks (DBNs) are multi-layer generative models. They can be trained to model windows of coefficients extracted from speech and they discover multiple layers of fea...
Abdel-rahman Mohamed, Tara N. Sainath, George Dahl...
We propose a new approach to language modeling which utilizes discriminative learning methods. Our approach is an iterative one: starting with an initial language model, in each i...
This paper presents a discriminative pruning method of n-gram language model for Chinese word segmentation. To reduce the size of the language model that is used in a Chinese word...
In this paper, we propose a novel discriminative language model, which can be applied quite generally. Compared to the well known N-gram language models, discriminative language m...
This paper investigates syntactic and sub-lexical features in Turkish discriminative language models (DLMs). DLM is a featurebased language modeling approach. It reranks the ASR o...
Ebru Arisoy, Murat Saraclar, Brian Roark, Izhak Sh...