# Polyphone Disambiguation for Mandarin Chinese Using Conditional Neural Network with Multi-level Embedding Features

arXiv: https://arxiv.org/abs/1907.01749 · HTML: https://mlsanity.com/paper/1907.01749/

## Key facts

- Cited by 8 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 3 Jul 2019.

## Built on by (most cited first, 8 of 8)

- [A Survey on Neural Speech Synthesis](https://mlsanity.com/paper/2106.15561/) (2021)
- [g2pW: A Conditional Weighted Softmax BERT for Polyphone Disambiguation in Mandarin](https://mlsanity.com/paper/2203.10430/) (2022)
- [Back-Translation-Style Data Augmentation for Mandarin Chinese Polyphone Disambiguation](https://mlsanity.com/paper/2211.09495/) (2022)
- [Polyphone Disambiguation in Mandarin Chinese with Semi-Supervised Learning](https://mlsanity.com/paper/2102.00621/) (2021)
- [A Polyphone BERT for Polyphone Disambiguation in Mandarin Chinese](https://mlsanity.com/paper/2207.12089/) (2022)
- [External Knowledge Augmented Polyphone Disambiguation Using Large Language Model](https://mlsanity.com/paper/2312.11920/) (2023)
- [Dict-TTS: Learning to Pronounce with Prior Dictionary Knowledge for Text-to-Speech](https://mlsanity.com/paper/2206.02147/) (2022)
- [LACTOSE: Linear Array of Conditions, TOpologies with Separated Error-backpropagation -- The Differentiable "IF" Conditional for Differentiable Digital Signal Processing](https://mlsanity.com/paper/2502.15829/) (2025)

## Abstract (arXiv)

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.