A hierarchical tag-graph search scheme with layered grammar rules for spontaneous speech understanding

Bor Shen Lin*, Berlin Chen, Hsin Min Wang, Lin Shan Lee

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)


It has always been difficult for language understanding systems to handle spontaneous speech with satisfactory robustness, primarily due to such problems as the fragments, disfluencies, out-of-vocabulary words, and ill-formed sentence structures. Also, the search schemes used are usually not flexible enough in accepting different input linguistic units, and great efforts are therefore required when they are used with different acoustic front ends in different tasks, specially in multi-modal and multi-lingual systems. In this paper, a new hierarchical tag-graph-based search scheme for spontaneous speech understanding is proposed. This scheme is based on a layered hierarchy of grammar rules, and therefore can integrate all the statistical and rule-based knowledge including acoustic scores, language model scores and grammar rules into the search process. More robust speech understanding is thus achievable. In addition, this scheme can accept graphs of different linguistic units such as phonemes, syllables, characters, words, spotted keywords, or phrases as the input, thus compatible to different acoustic front ends and multi-modal and multi-lingual applications can be easily developed. This search scheme has been successfully applied to a multi-domain, multi-modal dialogue system.

Original languageEnglish
Pages (from-to)819-831
Number of pages13
JournalPattern Recognition Letters
Issue number7
Publication statusPublished - 2002 May
Externally publishedYes


  • Robustness
  • Speech understanding
  • Spontaneous speech
  • Tag-graph search

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence


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