System and method for generating manually designed and automatically optimized spoken dialog systems
Disclosed herein are systems, computer-implemented methods, and tangible computer-readable storage media for generating a natural language spoken dialog system. The method includes nominating a set of allowed dialog actions and a set of contextual features at each turn in a dialog, and selecting an optimal action from the set of nominated allowed dialog actions using a machine learning algorithm. The method includes generating a response based on the selected optimal action at each turn in the dialog. The set of manually nominated allowed dialog actions can incorporate a set of business rules. Prompt wordings in the generated natural language spoken dialog system can be tailored to a current context while following the set of business rules. A compression label can represent at least one of the manually nominated allowed dialog actions.
1. A method comprising:
nominating, via a processor configured to use a partially observable Markov decision process in parallel with a conventional dialog state, a set of dialog actions and a set of contextual features; and
generating an audible response in a dialog between a user and a spoken dialog system based at least in part on the set of contextual features.
2. The method of claim 1 , further comprising generating the audible response based on the set of dialog actions and via a machine learning algorithm.
3. The method of claim 2 , further comprising augmenting the machine learning algorithm using reinforcement learning.
4. The method of claim 2 , wherein the machine learning algorithm augmented by the reinforcement learning is based on the partially observable Markov decision process.
5. The method of claim 2 , further comprising:
assigning a reward to the set of dialog actions as part of the machine learning algorithm.
6. The method of claim 1 , further comprising tailoring wordings in the spoken dialog system associated with the dialog based on a current context and a set of business rules.
7. A system comprising:
a processor configured to perform speech recognition; and
a computer-readable storage medium having instructions stored which, when executed by the processor, cause the processor to perform operations comprising:
nominating, via a processor configured to use a partially observable Markov decision process in parallel with a conventional dialog state, a set of dialog actions and a set of contextual features; and
generating an audible response in a dialog between a user and a spoken dialog system based at least in part on the set of contextual features.
8. The system of claim 7 , further comprising generating the audible response based on the set of dialog actions and via a machine learning algorithm.
9. The system of claim 8 , further comprising augmenting the machine learning algorithm using reinforcement learning.
10. The system of claim 8 , wherein the machine learning algorithm augmented by the reinforcement learning is based on the partially observable Markov decision process.
11. The system of claim 7 , the computer-readable storage medium having additional instructions stored which, when executed by the processor, cause the processor to perform operations comprising:
assigning a reward to the set of dialog actions as part of the machine learning algorithm.
12. The system of claim 7 , the computer-readable storage medium having additional instructions stored which, when executed by the processor, cause the processor to perform operations comprising tailoring wordings in the spoken dialog system associated with the dialog based on a current context and a set of business rules.
13. A computer-readable storage device having instructions stored which, when executed by a computing device configured to perform speech recognition, cause the computing device to perform operations comprising:
nominating a set of dialog actions and a set of contextual features, wherein the computing device uses a partially observable Markov decision process in parallel with a conventional dialog state; and
generating an audible response in a dialog between a user and a spoken dialog system based at least in part on the set of contextual features.
14. The computer-readable storage device of claim 13 , further comprising generating the audible response based on the set of dialog actions and via a machine learning algorithm.
15. The computer-readable storage device of claim 14 , further comprising augmenting the machine learning algorithm using reinforcement learning.
16. The computer-readable storage device of claim 14 , wherein the machine learning algorithm augmented by the reinforcement learning is based on the partially observable Markov decision process.
17. The computer-readable storage device of claim 13 , having additional instructions stored which, when executed by the computing device, cause the computing device to perform operations comprising:
assigning a reward to the set of dialog actions as part of the machine learning algorithm.
18. The computer-readable storage device of claim 13 , having additional instructions stored which, when executed by the computing device, cause the computing device to perform operations comprising tailoring wordings in the spoken dialog system associated with the dialog based on a current context and a set of business rules.