Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Conversational Speech Recognition By Learning Conversation-level
  Characteristics   Conversational automatic speech recognition (ASR) is a task to recognize
conversational speech including multiple speakers. Unlike sentence-level ASR,
conversational ASR can naturally take advantages from specific characteristics
of conversation, such as role preference and topical coherence. This paper
proposes a conversational ASR model which explicitly learns conversation-level
characteristics under the prevalent end-to-end neural framework. The highlights
of the proposed model are twofold. First, a latent variational module (LVM) is
attached to a conformer-based encoder-decoder ASR backbone to learn role
preference and topical coherence. Second, a topic model is specifically adopted
to bias the outputs of the decoder to words in the predicted topics.
Experiments on two Mandarin conversational ASR tasks show that the proposed
model achieves a maximum 12% relative character error rate (CER) reduction.

17
The categories of this paper are: q-fin
13
The categories of this paper are: quant-ph
21
The categories of this paper are: adap-org
27
The categories of this paper are: comp-gas
12
The categories of this paper are: nucl-th
35
The categories of this paper are: mtrl-th
0
The categories of this paper are: hep-ph
7
The categories of this paper are: hep-th
22
The categories of this paper are: chao-dyn
3
The categories of this paper are: physics
20
The categories of this paper are: acc-phys
34
The categories of this paper are: chem-ph
8
The categories of this paper are: hep-ex
33
The categories of this paper are: plasm-ph
14
The categories of this paper are: math-ph
9
The categories of this paper are: nlin