基于词图的音素识别及在语种识别中的应用

Lattice-based PPRLM and Its Application in Language Identification

本文介绍了一种基于词图的并行音素识别方法的自动语种识别系统,基于词图的并行音素识别方法是并行音素识别方法的一个扩展,它用识别产生的词图来描述声学候选结果空间,比并行音素识别方法中用最佳路径音子序列包含更丰富的信息。通过真实环境广播语音测试表明,该方法比并行音素识别方法识别性能提升了约6%,在每个语种约4小时的训练数据下,跟其他的几种语种识别方法也有可比的性能。

The paper presents an automatic language identification （LID） system which is based on the lattice-based PPRLM method. As an extension of the original PPRLM, the lattice-based PPRLM method uses lattice to generate the acoustic hypothesis space, which contains more information than that of 1-best phoneme sequence in the original PPRLM. Evaluations from the broadcasting speech in real environments show that the lattice-based PPRLM improves the accuracy rate by 6%. Results are also comparable with other approaches within different languages, while four-hour training set is given for each language.