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<Paper uid="N04-4016">
  <Title>Correction Grammars for Error Handling in a Speech Dialog System</Title>
  <Section position="4" start_page="0" end_page="0" type="metho">
    <SectionTitle>
3 Error Handling Based on Correction
Grammars
</SectionTitle>
    <Paragraph position="0"> To recognize the user's utterances in a dialog system, a grammar for potential user utterances must be prepared in advance for each dialog context. For error handling, it is also necessary to anticipate correction utterances and prepare a correction grammar. We propose a method to automatically create the correction grammar based on the current dialog context; error detection and repair is implemented using the correction grammar.</Paragraph>
    <Paragraph position="1"> To create the correction grammar, the system must know the user's utterances prior to the error, because correction utterances typically depend on them. If the user's utterances are consistent with what the system is expecting, the correction grammar can be generated based on the grammar previously in use by the speech recognizer. Therefore, the sequence of grammars used in the dialog so far is stored in the grammar history as the dialog context, and the correction grammar is created using the grammars in this history.</Paragraph>
    <Paragraph position="2"> Most of the forms of correction utterances can be expected in advance because correction utterances include many repetitions of words or phrases from previous turns (Kazemzadeh et al., 2003). We assume that the rules to generate the correction grammar can be prepared as templates; the correction grammar is created by inserting information extracted from the grammar history into a template.</Paragraph>
    <Paragraph position="3"> Figure 3 shows an example of a process flow in a dialog system which performs error handling based on a correction grammar. The &amp;quot;system prompt n&amp;quot; is the process to output the n-th prompt to the user. The correction grammar is created based on the grammar used in the &amp;quot;user response n-1&amp;quot;, which is the process to recognize the (n-1)-th user utterance, and it is used in the &amp;quot;user response n&amp;quot; together with the &amp;quot;grammar n&amp;quot; which is used to recognize the n-th normal user's utterance. The system detects the error when the user's utterance is recognized using the correction grammar, and then transits into the &amp;quot;correction of errors&amp;quot; to modify the error. The grammar history in Figure 3 stores only the grammar used in the last recognition process. The number of grammars stored in the history can be changed depending on the dialog management strategy and error handling requirements.</Paragraph>
  </Section>
  <Section position="5" start_page="0" end_page="0" type="metho">
    <SectionTitle>
4 Generation of Correction Grammar
</SectionTitle>
    <Paragraph position="0"> The correction grammar is created as follows.</Paragraph>
    <Paragraph position="1">  (1) Copying the grammar rules in the history The user often repeats the same utterance when the system misunderstood what s/he spoke. To detect when the user repeats exactly the same utterance, the grammar rules in the grammar history are copied into the correction grammar.</Paragraph>
    <Paragraph position="2"> (2) Inserting the rules in the history into the template  used to support this type of correction utterance. An example of the correction grammar rule generated by this method is shown in Figure 4. The &amp;quot;null&amp;quot; in Figure 4 implies a transition with no condition, and the &amp;quot;X&amp;quot; shows where the original rule is embedded. In this example, the created grammar rule in Figure 4(c) corresponds to the following sentences:  * No, I'd like to know the weather for Tokyo.</Paragraph>
    <Paragraph position="3"> * I said I'd like to know the weather for Tokyo. (3) Inserting slot-values into the template  The user often repeats only words or phrases which the system is focusing on (Kazemzadeh et al., 2003). In a slot-filling dialog, these correspond to the slot values. Therefore, correction grammar rules are also created by extracting the slot values from the grammar in the history and inserting them into the template. If there are several slot values that can be corrected at the same time, all of their possible combinations and permutations are also generated. An example is shown in Figure 5. In Figure 5(b), the slot-values are &amp;quot;Tokyo&amp;quot; and &amp;quot;tomorrow&amp;quot;. The grammar rule in Figure 5(c) includes each slot value plus their combination(s), and represents the following sentences:</Paragraph>
  </Section>
  <Section position="6" start_page="0" end_page="0" type="metho">
    <SectionTitle>
5 Prototype System with Error Handling
</SectionTitle>
    <Paragraph position="0"> We have implemented the proposed error handling method for a set of Japanese dialog scenarios in the CAMMIA system. We added to this system: a) a process to create a correction grammar file when the system sends a grammar file to the client, b) a process to repair errors based on the recognition result, and c) transitions to the repair action when the user's utterance is recognized by the correction grammar.</Paragraph>
    <Paragraph position="1"> There are two types of errors: task transition errors and slot value errors. If the error is a task transition error, the modification process cancels the current task and transits to the new task as specified by the correction utterance. When the error is a slot value error, the slot value is replaced by the value given in the correction utterance. However, if the new value is identical to the old one, we assume a recognition error and the second candidate in the recognition result is used. This technique requires a speech recognizer that can output N-best results; we used Julius for SAPI (Kyoto Univ., 2002) for this experiment.</Paragraph>
  </Section>
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