MISSPEAK RESOLUTION IN NATURAL LANGUAGE UNDERSTANDING FOR A MAN-MACHINE INTERFACE

• US 20180268813A1
• Filed: 03/17/2017
• Published: 09/20/2018
• Est. Priority Date: 03/17/2017
• Status: Abandoned Application

• Current Assignee: Intel Corporation
• Original Assignee: Intel IP Corporation (Intel Corporation)
• Inventors: Georges, Munir Nikolai Alexander, Stemmer, Georg, Jessa, Szymon
• Application Number:
  US15/462,428
• Publication Number:
  US 20180268813A1
• Time in Patent Office: Days
• CPC Class Codes: G06F 40/237 Lexical tools
• CPC Class Codes: G10L 15/1822 Parsing for meaning understanding
• CPC Class Codes: G10L 2015/223 Execution procedure of a spoken command

Abstract

Misspeaking is resolved in a natural language understanding system to interface with a machine. In one example, a user speech utterance is received. A sequence of classifiers is applied to words of the utterance to determine a meaning of the utterance. The meaning in interpreted as a command and the command is applied to a device for execution. The classifiers may include a first classifier to determine an intended function that is a subject of the utterance, a second classifier to determine words with properties that are related to the intended function, and a third classifier to select a property to apply to the function.

Claims

1. A method comprising:

receiving a user speech utterance;

applying a sequence of classifiers to words of the utterance to determine a meaning of the utterance;

interpreting the determined meaning as a command; and

applying the command to a device for execution.

2. The method of claim 1, wherein applying a sequence of classifiers comprises applying a first classifier to determine an intended function that is a subject of the utterance and then applying a second classifier to determine words with properties that are related to the intended function.

3. The method of claim 2, further comprising choosing a word to apply to the intended function by applying a neural network to the words with properties that are related to the function to choose a word.

4. The method of claim 3, wherein the words with properties are structured as a bag of words with sequence information.

5. The method of claim 4, wherein bag of words features are presented as vector representatives of word collections.

6. The method of claim 2, further comprising selecting a function and application using the intended function.

7. The method of claim 1, wherein the sequence of classifiers comprise a user intent detection, followed by a word property detection, followed by a property selection made by applying the intent to words having appropriate properties.

8. The method of claim 7, wherein the intent detection classifier determines an intent of the user by applying probabilities of possible intents to a bag-of-words representation of the utterance and selecting a most probable intent.

9. The method of claim 7, wherein the word property detection classifier associates words of the utterance with properties represented by the words.

10. The method of claim 9, wherein the word property detection classifier detects word properties using a vocabulary and a neural network.

11. The method of claim 9, wherein the word property detection classifier validates each detected property against a natural language understanding module to ensure that the corresponding word can be evaluated based on the property.

12. The method of claim 1, further comprising the classifiers of the sequence of classifiers using data driven machine learning.

13. The method of claim 1, further comprising using temporal features of the words to distinguish between properties and then revising properties in the utterance.

14. The method of claim 1, wherein applying a sequence of classifier comprises classifying at least a portion of the words, the method further comprising applying a pre-defined rule to words of the same classification.

15. The method of claim 1, wherein the pre-defined rule is to use the last word of the same classification as the meaning.

16. An apparatus comprising:

an automatic speech recognition module to receive a user speech utterance and determine a sequence of words;

a natural language understanding module to apply a sequence of classifiers to the words of the utterance to determine a meaning of the utterance; and

an application module to interpret the meaning as a command and to apply the command to a device for execution.

17. The apparatus of claim 17, wherein the natural language understanding module comprises a neural network to determine properties of words of the utterance.

18. The apparatus of claim 17, wherein the natural language understanding module classifier associates words of the utterance with properties represented by the words using temporal features of the words to distinguish between properties.

19. A speech operated system comprising:

a microphone to receive a speech utterance from a user;

an automatic speech recognition module to receive the speech utterance and determine a sequence of words;

a natural language understanding module to apply a sequence of classifiers to the words of the utterance to determine a meaning of the utterance;

an application module to interpret the meaning as a command; and

an actuator to execute the command.

20. The system of claim 19, wherein the sequence of classifiers comprise:

a first classifier to determine an intended function that is a subject of the utterance;

a second classifier to determine words with properties that are related to the intended function; and

a third classifier to select a property to apply to the function.