Automated recognition system for natural language understanding
View Patent ↗An interactive response system directs input to a software-based router, which is able to intelligently respond to the input by drawing on a combination of human agents, advanced recognition and expert systems. The system utilizes human “intent analysts” for purposes of interpreting customer input. Automated recognition subsystems are trained by coupling customer input with IA-selected intent corresponding to the input, using model-updating subsystems to develop the training information for the automated recognition subsystems.
1. A system for processing an interaction with a person, comprising:
a routing processor configured to receive data representing an input provided by the person;
a real-time automated speech recognizer (ASR) in communication with the routing processor and configured to receive therefrom the data, the real-time ASR producing an output responsive to the data;
a graphical analyst user interface device in communication with the routing processor, configured to present to a human analyst information related to the input in perceptible form and to accept an intent from the human analyst, the information presented in the graphical analyst user interface comprising at least one of: the output, location information corresponding to the person, historical information corresponding to the person, characteristics of the person, and prior interactions related to the input, the graphical analyst user interface including a drop-down list of predetermined options for selecting the intent; and
a training subsystem configured to:
receive the information and the intent;
train a first model used by a training ASR and generated based at least in part on the information and the intent, the training ASR configured to generate statistics responsive to the information; and
train a second model used by the real-time ASR responsive to the statistics.
2. The system of claim 1 , wherein the training subsystem is configured to train the real-time ASR by updating the second model.
3. The system of claim 1 , wherein the training subsystem is configured to continue training the real-time ASR responsive to the real-time ASR not reaching a performance threshold.
4. A computer-implemented method for operating an interactive response system comprising:
receiving data representing an input from a person;
using a processor, automatically presenting information relating to the input to an intent analyst through a graphical analyst user interface, the information presented in the graphical analyst user interface comprising at least one of: an output produced responsive to the received data, location information corresponding to the person, historical information corresponding to the person, characteristics of the person, and prior interactions with the person;
accepting an intent from the intent analyst through the analyst user interface;
providing the information and the intent to a training subsystem;
accepting from the training subsystem a training model used by a training automated speech recognizer (ASR), the training ASR generated responsive to the information and the intent;
accepting from the training ASR statistics generated responsive to the information; and
training, via the statistics, a second model used by a real-time ASR in order to improve performance thereof.
5. The computer-implemented method of claim 4 , wherein the training comprises updating the second model.
6. The computer-implemented method of claim 4 , wherein the training comprises testing performance of the real-time ASR and continuing training responsive to the performance not exceeding a performance threshold.
7. A system for managing interactions with a person, comprising non-transitory computer storage media storing programming instructions executable by at least one processor for:
receiving data representing an input from a person;
using a processor, automatically presenting information relating to the input to an intent analyst through a graphical analyst user interface, the information presented in the graphical analyst user interface comprising at least one of: an output produced responsive to the received data, location information corresponding to the person, historical information corresponding to the person, characteristics of the person, and prior interactions related to the input;
accepting an intent from the intent analyst through the analyst user interface;
providing the information and the intent to a training subsystem;
accepting from the training subsystem a training model used by a training automated speech recognizer (ASR), the training ASR generated responsive to the information and the intent;
accepting from the training ASR statistics generated responsive to the information; and
training, via the statistics, a second model used by a real-time ASR in order to improve performance thereof.
8. The system of claim 7 , wherein the training comprises updating the second model.
9. The system of claim 7 , wherein the training comprises testing performance of the real-time ASR and continuing training responsive to the performance not exceeding a performance threshold.