SYSTEM FOR HANDLING FREQUENTLY ASKED QUESTIONS IN A NATURAL LANGUAGE DIALOG SERVICE

• US 20090070113A1
• Filed: 11/07/2008
• Published: 03/12/2009
• Est. Priority Date: 04/23/2002
• Status: Abandoned Application

• Current Assignee: Nuance Communications, Inc. (Microsoft Corporation)
• Original Assignee: AT&T Corporation (AT&T, Inc.)
• Inventors: Riccardi, Giuseppe, Gupta, Narendra K., Rahim, Mazin G.
• Application Number:
  US12/266,835
• Publication Number:
  US 20090070113A1
• Time in Patent Office: Days
• US Class Current: 704/257
• CPC Class Codes: G06F 3/167 Audio in a user interface, e.g. using voice commands for navigating, audio feedback
• CPC Class Codes: G10L 15/22 Procedures used during a speech recognition process, e.g. man-machine dialogue

Abstract

A voice-enabled help desk service is disclosed. The service comprises an automatic speech recognition module for recognizing speech from a user, a spoken language understanding module for understanding the output from the automatic speech recognition module, a dialog management module for generating a response to speech from the user, a natural voices text-to-speech synthesis module for synthesizing speech to generate the response to the user, and a frequently asked questions module. The frequently asked questions module handles frequently asked questions from the user by changing voices and providing predetermined prompts to answer the frequently asked question.

Claims

1. A method of responding to user utterances in a spoken dialog service, the method comprising:

receiving a user utterance;

identifying a question and an answer selected from a question and answer table based on a similarity computation that calculates a similarity between the user utterance and at least one question in the question and answer table and a set of words in the user utterance that are not found in a set of unique words in the question and answer table; and

presenting an answer to the user utterance from the identified question and answer.

2. The method of claim 1, further comprising:

classifying the recognized text associated with the user utterance; and

selecting the question and answer table from a plurality of question and answer tables according at least to the classified text.

3. The method of claim 1, wherein the identified question and answer is output to a dialog management module and wherein the similarity computation further comprises:

$\mathrm{Sim}<br><br>\left(Q,{\mathrm{FAQ}}_j\right)=\frac{\underset{i}{\overset{}{\sum <br><br>}}<br><br><br><br>q_i·<br><br>{\mathrm{faq}}_{\mathrm{ji}}}{\sqrt{\underset{i}{\overset{}{\sum <br><br>}}<br><br><br><br>{\left(q_i\right)}^2+{c<br><br>\left(0.5\right)}^2}·<br><br>\sqrt{\underset{i}{\sum <br><br>}<br><br><br><br>{\left({\mathrm{faq}}_{\mathrm{ij}}\right)}^2}}$

wherein the term faq_ji represents the questions in the question and answer table and the term q_i represents the user utterance and c is the set of words.

4. The method of responding to utterances in a spoken dialog service of claim 1, wherein the identified question and answer output is selected according to a most similar question to the received utterance.

5. The method of responding to utterances of claim 1, wherein the answer is selected from the selected question and answer table as being associated with a question that is the most similar to the received utterance.

6. The method of responding to utterances of claim 1, wherein each question and answer table includes questions and associated answers.

7. A computer-readable medium storing a computer program having instructions for controlling a computing device to perform the steps of:

receiving a user utterance;

identifying a question and an answer selected from a question and answer table based on a similarity computation that calculates a similarity between the user utterance and at least one question in the question and answer table and a set of words in the user utterance that are not found in a set of unique words in the question and answer table; and

presenting an answer to the user utterance from the identified question and answer.

8. The computer-readable medium of claim 7, wherein the instructions further comprise:

classifying the recognized text associated with the user utterance; and

selecting the question and answer table from a plurality of question and answer tables according at least to the classified text.

9. The computer-readable medium of claim 7, wherein the instructions further comprise:

outputting the identified question and answer to a dialog management module and wherein the similarity computation further comprises;

$\mathrm{Sim}<br><br>\left(Q,{\mathrm{FAQ}}_j\right)=\frac{\underset{i}{\overset{}{\sum <br><br>}}<br><br><br><br>q_i·<br><br>{\mathrm{faq}}_{\mathrm{ji}}}{\sqrt{\underset{i}{\overset{}{\sum <br><br>}}<br><br><br><br>{\left(q_i\right)}^2+{c<br><br>\left(0.5\right)}^2}·<br><br>\sqrt{\underset{i}{\sum <br><br>}<br><br><br><br>{\left({\mathrm{faq}}_{\mathrm{ij}}\right)}^2}}$

wherein the term faq_ji represents the questions in the question and answer table and the term q_i represents the user utterance and c is the set of words.

10. The computer readable medium of claim 7, wherein the identified question and answer output is selected according to a most similar question to the received utterance.

11. The computer-readable medium of claim 7, wherein the answer is selected from the selected question and answer table as being associated with the question that is most similar to the received utterance.

12. The computer-readable medium of claim 7, wherein the question and answer table includes questions and associated answers.

13. A computing device for responding to utterances in a spoken dialog service, the computing device comprising:

a module configured to receive a user utterance;

a module configured to identify a question and answer selected from a question and answer table based on a similarity computation that calculates a similarity between the user utterance and at least one question in the question and answer table, a set of words in the user utterance that are not found in a set of unique words in the question and answer table; and

a module configured to present an answer to the user from the identified question and answer.

14. The computing device of claim 13, further comprising:

a module configured to classify recognized text associated with the user utterance; and

a module configured to select the question and answer table from a plurality of question and answer tables according at least to the classified text.

15. The computing device of claim 13, wherein the identified question and answer is output to a dialog management module, and wherein similarity computation further comprises:

$\mathrm{Sim}<br><br>\left(Q,{\mathrm{FAQ}}_j\right)=\frac{\underset{i}{\overset{}{\sum <br><br>}}<br><br><br><br>q_i·<br><br>{\mathrm{faq}}_{\mathrm{ji}}}{\sqrt{\underset{i}{\overset{}{\sum <br><br>}}<br><br><br><br>{\left(q_i\right)}^2+{c<br><br>\left(0.5\right)}^2}·<br><br>\sqrt{\underset{i}{\sum <br><br>}<br><br><br><br>{\left({\mathrm{faq}}_{\mathrm{ij}}\right)}^2}}$

wherein the term faq_ji represents the questions in the question and answer table and the term q_i represents the user utterance and c is the set of words.

16. The computing device of claim 13, wherein the identified question and answer output is selected according to a most similar question to the received utterance.

17. The computing device of claim 13, wherein the answer is selected from the selected question and answer table as being associated with a question that is the most similar to the received utterance.

18. The computing device of claim 13, wherein the question and answer table includes questions and associated answers.