基于韵律信息的连续语流调型评测研究

Tone Evaluation of Chinese Continuous Speech Based on Prosodic Words

汉语连续语流中的调型评测是汉语语音评测的一个重要环节,利用连续语流中韵律耦合效应和韵律结构紧密相关这一特性,以韵律词为基本建模单元,建立基于多空间概率分布的HMM调型模型(MSD-HMM),使得汉语普通话水平评测系统针对标准连续语流的调型识别率从82.0%提升至84.6%;针对有方言背景的非标准发音,机器评分与专家评分的相关度绝对提升超过3.0%。

The tone evaluation of Chinese continuous speech is a key aspect in Mandarin Chinese pronunciation test. Taking advantage of the close correlation between the prosody framework and the modified tonal curve, this paper presents a Multi-Space Distribution Hidden Markov Model （MSD-HMM） built on the prosodic word for the tone evaluation. The experimental results show that the proposed Mandarin Chinese Pronunciation Evaluation System improves from 82.0% to 84.6% in the performance of tonal syllable error rate for the standard Chinese continuous speech. And for the non-standard Chinese Mandarin speech, the correlation between computer score and expert score achieves over 3.0% absolute improvements compared with that of the baseline system without tone pronunciation test.