Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: GPU-Accelerated Forward-Backward algorithm with Application to
  Lattice-Free MMI   We propose to express the forward-backward algorithm in terms of operations
between sparse matrices in a specific semiring. This new perspective naturally
leads to a GPU-friendly algorithm which is easy to implement in Julia or any
programming languages with native support of semiring algebra. We use this new
implementation to train a TDNN with the LF-MMI objective function and we
compare the training time of our system with PyChain - a recently introduced
C++/CUDA implementation of the LF-MMI loss. Our implementation is about two
times faster while not having to use any approximation such as the "leaky-HMM".

8
The categories of this paper are: hep-ex
18
The categories of this paper are: econ
4
The categories of this paper are: cond-mat
22
The categories of this paper are: chao-dyn
7
The categories of this paper are: hep-th
15
The categories of this paper are: nucl-ex
9
The categories of this paper are: nlin
6
The categories of this paper are: astro-ph
29
The categories of this paper are: funct-an
27
The categories of this paper are: comp-gas
33
The categories of this paper are: plasm-ph
26
The categories of this paper are: bayes-an
23
The categories of this paper are: solv-int
36
The categories of this paper are: cmp-lg
2
The categories of this paper are: math
20
The categories of this paper are: acc-phys