Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Transformer in action: a comparative study of transformer-based acoustic
  models for large scale speech recognition applications   In this paper, we summarize the application of transformer and its streamable
variant, Emformer based acoustic model for large scale speech recognition
applications. We compare the transformer based acoustic models with their LSTM
counterparts on industrial scale tasks. Specifically, we compare Emformer with
latency-controlled BLSTM (LCBLSTM) on medium latency tasks and LSTM on low
latency tasks. On a low latency voice assistant task, Emformer gets 24% to 26%
relative word error rate reductions (WERRs). For medium latency scenarios,
comparing with LCBLSTM with similar model size and latency, Emformer gets
significant WERR across four languages in video captioning datasets with 2-3
times inference real-time factors reduction.

31
The categories of this paper are: ao-sci
21
The categories of this paper are: adap-org
0
The categories of this paper are: hep-ph
34
The categories of this paper are: chem-ph
8
The categories of this paper are: hep-ex
9
The categories of this paper are: nlin
12
The categories of this paper are: nucl-th
24
The categories of this paper are: dg-ga
15
The categories of this paper are: nucl-ex
36
The categories of this paper are: cmp-lg
28
The categories of this paper are: alg-geom
4
The categories of this paper are: cond-mat
18
The categories of this paper are: econ
19
The categories of this paper are: eess
32
The categories of this paper are: atom-ph
2
The categories of this paper are: math