Three phase verification for spoken dialog clarification

ABSTRACT

Spoken dialog tasks incur many errors including speech recognition errors, understanding errors, and even dialog management errors. These errors create a big gap between user's will and the system's understanding, and eventually result in a misinterpretation. To fill in the gap, people in human-to-human dialog try to clarify the major causes of the misunderstanding and selectively correct them. This paper presents a method for applying the human's clarification techniques to human-machine spoken dialog systems. To increase the error detection precision and error recovery efficiency for the clarification dialogs, error detection phase is organized into three systematic phases and a clarification expert is devised for recovering the errors using the three phase verification. The experiment results demonstrate that the three phase verification could effectively catch the word and utterance-level errors in order to increase the SLU (spoken language understanding) performance and the clarification experts can actually increase the dialog success rate and the dialog efficiency.

REFERENCES

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INDEX TERMS

Primary Classification:
  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
      I.2.7 Natural Language Processing
          Subjects: Discourse

Additional Classification:
  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
      I.2.7 Natural Language Processing
          Subjects: Speech recognition and synthesis

General Terms:
Algorithms, Design, Human Factors, Languages, Performance, Verification

Keywords:
clarification dialog, clarification expert, dialog management, spoken language understanding, three phase verification