@article{stoyanchev-stent-2012-concept,
    title = "Concept Type Prediction and Responsive Adaptation in a Dialogue System",
    author = "Stoyanchev, Svetlana  and
      Stent, Amanda J.",
    editor = "Aist, Gregory  and
      Piwek, Paul  and
      Boyer, Kristy Elizabeth",
    journal = "Dialogue {\&} Discourse",
    volume = "3",
    year = "2012",
    url = "https://preview.aclanthology.org/ingest-dnd/2012.dnd-3.9/",
    doi = "10.5087/dad.2012.101",
    pages = "1--31",
    abstract = "Responsive adaptation in spoken dialog systems involves a change in dialog system behavior in response to a user or a dialog situation. In this paper we address responsive adaptation in the automatic speech recognition (ASR) module of a spoken dialog system. We hypothesize that information about the content of a user utterance may help improve speech recognition for the utterance. We use a two-step process to test this hypothesis: first, we automatically predict the task-relevant concept types likely to be present in a user utterance using features from the dialog context and from the output of first-pass ASR of the utterance; and then, we adapt the ASR{'}s language model to the predicted content of the user{'}s utterance and run a second pass of ASR. We show that: (1) it is possible to achieve high accuracy in determining presence or absence of particular concept types in a post-confirmation utterance; and (2) 2-pass speech recognition with concept type classification and language model adaptation can lead to improved speech recognition performance for post-confirmation utterances."
}