System and method for advanced turn-taking for interactive spoken dialog systems
Disclosed herein are systems, methods, and non-transitory computer-readable storage media for advanced turn-taking in an interactive spoken dialog system. A system configured according to this disclosure can incrementally process speech prior to completion of the speech utterance, and can communicate partial speech recognition results upon finding particular conditions. A first condition which, if found, allows the system to communicate partial speech recognition results, is that the most recent word found in the partial results is statistically likely to be the termination of the utterance, also known as a terminal node. A second condition is the determination that all search paths within a speech lattice converge to a common node, also known as a pinch node, before branching out again. Upon finding either condition, the system can communicate the partial speech recognition results. Stability and correctness probabilities can also determine which partial results are communicated.
1. A method for determining turn order between a user and an interactive turn-taking spoken dialog system based on a result, the method comprising:
receiving speech; and
while continuing to receive the speech:
identifying a starting point associated with the speech;
identifying content of the speech received so far, to yield identified content;
predicting a stability of the identified content; and
identifying an end point associated with the speech, wherein the end point is a pinch node in a content lattice; and
returning, via a processor, a result based on the stability between the starting point and the end point.
2. The method of claim 1 , wherein the starting point is one of a beginning of the speech and a previously marked pinch node.
3. The method of claim 1 , wherein the stability of the identified content of the identified content is determined using stability probability.
4. The method of claim 3 , wherein the stability probability is determined using a machine learning algorithm on a corpus of speech utterances.
5. The method of claim 4 , wherein the machine learning algorithm is a logistic regression.
6. The method of claim 1 , wherein the result comprises a path having a highest probability through a speech component lattice.
7. The method of claim 1 , wherein the result comprises partial speech recognition.
8. A system for determining turn order between a user and an interactive turn-taking spoken dialog system based on a result, the system comprising:
a processor; and
a computer-readable storage medium having instructions stored which, when executed by the processor, cause the processor to perform operations comprising:
receiving speech; and
while continuing to receive the speech:
identifying a starting point associated with the speech;
identifying content of the speech received so far, to yield identified content;
predicting a stability of the identified content; and
identifying an end point associated with the speech, wherein the end point is a pinch node in a content lattice; and
returning, a result based on the stability between the starting point and the end point.
9. The system of claim 8 , wherein the starting point is one of a beginning of the speech and a previously marked pinch node.
10. The system of claim 8 , wherein the stability of the identified content of the identified content is determined using stability probability.
11. The system of claim 10 , wherein the stability probability is determined using a machine learning algorithm on a corpus of speech utterances.
12. The system of claim 11 , wherein the machine learning algorithm is a logistic regression.
13. The system of claim 8 , wherein the result comprises a path having a highest probability through a speech component lattice.
14. The system of claim 8 , wherein the result comprises partial speech recognition.
15. A computer-readable storage device having instructions stored which, when executed by a computing device, cause the computing device to perform operations comprising:
receiving speech; and
while continuing to receive the speech:
identifying a starting point associated with the speech;
identifying content of the speech received so far, to yield identified content;
predicting a stability of the identified content; and
identifying an end point associated with the speech, wherein the end point is a pinch node in a content lattice; and
returning a result based on the stability between the starting point and the end point.
16. The computer-readable storage device of claim 15 , wherein the starting point is one of a beginning of the speech and a previously marked pinch node.
17. The computer-readable storage device of claim 15 , wherein the stability of the identified content of the identified content is determined using stability probability.
18. The computer-readable storage device of claim 17 , wherein the stability probability is determined using a machine learning algorithm on a corpus of speech utterances.
19. The computer-readable storage device of claim 18 , wherein the machine learning algorithm is a logistic regression.
20. The computer-readable storage device of claim 15 , wherein the result comprises a path having a highest probability through a speech component lattice.