Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Polyphone Disambiguation for Mandarin Chinese Using Conditional Neural
  Network with Multi-level Embedding Features   This paper describes a conditional neural network architecture for Mandarin
Chinese polyphone disambiguation. The system is composed of a bidirectional
recurrent neural network component acting as a sentence encoder to accumulate
the context correlations, followed by a prediction network that maps the
polyphonic character embeddings along with the conditions to corresponding
pronunciations. We obtain the word-level condition from a pre-trained
word-to-vector lookup table. One goal of polyphone disambiguation is to address
the homograph problem existing in the front-end processing of Mandarin Chinese
text-to-speech system. Our system achieves an accuracy of 94.69\% on a publicly
available polyphonic character dataset. To further validate our choices on the
conditional feature, we investigate polyphone disambiguation systems with
multi-level conditions respectively. The experimental results show that both
the sentence-level and the word-level conditional embedding features are able
to attain good performance for Mandarin Chinese polyphone disambiguation.

21
The categories of this paper are: adap-org
12
The categories of this paper are: nucl-th
14
The categories of this paper are: math-ph
6
The categories of this paper are: astro-ph
37
The categories of this paper are: supr-con
26
The categories of this paper are: bayes-an
8
The categories of this paper are: hep-ex
35
The categories of this paper are: mtrl-th
7
The categories of this paper are: hep-th
13
The categories of this paper are: quant-ph
30
The categories of this paper are: q-alg
0
The categories of this paper are: hep-ph
36
The categories of this paper are: cmp-lg
15
The categories of this paper are: nucl-ex
9
The categories of this paper are: nlin
2
The categories of this paper are: math