Systems and methods of interpreting speech data

• US 10,068,583 B2
• Filed: 03/09/2018
• Issued: 09/04/2018
• Est. Priority Date: 06/05/2014
• Status: Active Grant

• Current Assignee: Interdev Technologies Inc. (Valsef Group)
• Original Assignee: Interdev Technologies Inc. (Valsef Group)
• Inventors: Rice, Janet M., Liang, Peng, Kuehn, Terence W.
• Primary Examiner(s): Sharma, Neeraj
• Application Number:
  US15/916,942
• Publication Number:
  US 20180211680A1
• Time in Patent Office: 179 Days
• Field of Search: None
• CPC Class Codes: G10L 15/08 Speech classification or search
• CPC Class Codes: G10L 15/20 Speech recognition techniques specially adapted for robustness in adverse environments, e.g. in noise, of stress induced speech G10L21/02 takes precedence
• CPC Class Codes: G10L 15/26 Speech to text systems G10L15/08 takes precedence
• CPC Class Codes: G10L 19/26 Pre-filtering or post-filtering
• CPC Class Codes: G10L 21/02 Speech enhancement, e.g. noise reduction or echo cancellation reducing echo effects in line transmission systems H04B3/20; echo suppression in hands-free telephones H04M9/08
• CPC Class Codes: G10L 25/93 Discriminating between voiced and unvoiced parts of speech signals G10L25/90 takes precedence
• CPC Class Codes: H04R 29/006 Microphone matching

Abstract

Method and systems are provided for interpreting speech data. A method and system for recognizing speech involving a filter module to generate a set of processed audio data based on raw audio data; a translation module to provide a set of translation results for the raw audio data; and a decision module to select the text data that represents the raw audio data. A method for minimizing noise in audio signals received by a microphone array is also described. A method and system of automatic entry of data into one or more data fields involving receiving a processed audio data; and operating a processing module to: search in a trigger dictionary for a field identifier that corresponds to the trigger identifier; identify a data field associated with a data field identifier corresponding to the field identifier; and providing content data associated with the trigger identifier to the identified data field.

Claims

1. An uncontrolled environment-based speech recognition system, the system comprising:

one or more filters to each generate a set of processed audio data based on raw audio data received from one or more computing devices, the one or more filters applying filter processes to the raw audio data to generate the set of processed audio data, the one or more filters comprising at least one filter appropriate for the uncontrolled environment-based speech recognition system;

a translator, operable by a processor, to provide a set of translation results for the raw audio data based on the set of processed audio data, each translation result being associated with at least one processed audio data and each translation result including a text data and a confidence level associated with that text data; and

in response to receiving the set of translation results, a decision controller is automatically triggered by the processor to select the text data that represents the raw audio data, the decision controller is operable to;

identify at least one translation result from the set of translation results that includes the text data associated with the confidence level that exceeds a confidence threshold;

determine whether the identified at least one translation result comprises more than one translation result;

in response to determining the identified at least one translation result comprises more than one translation result, determine an occurrence frequency for each text data of the identified at least one translation result and select the text data based on the occurrence frequency, the occurrence frequency representing a number of times that the text data appears in the set of translation results; and

generate an output signal associated with the selection by the decision controller.

2. The speech recognition system of claim 1, wherein the filter processes comprise at least two different filter processes.

3. The speech recognition system of claim 1, wherein the one or more filters comprises two or more filters.

4. The speech recognition system of claim 1, wherein each translation result comprises a sub-set of translation results for at least one of the processed audio data, the sub-set of translation results including two or more text data and each text data is associated with a respective confidence level.

5. The speech recognition system of claim 4, wherein the two or more text data correspond to alternative representations of the raw audio data.

6. The speech recognition system of claim 1, wherein the decision controller selects the text data associated with a highest occurrence frequency as the text data that corresponds to the raw audio data.

7. The speech recognition system of claim 1, wherein:

the confidence threshold comprises a set of confidence thresholds, the set of confidence thresholds including a first confidence threshold and at least one subsequent confidence threshold that is lower than the first confidence threshold; and

the decision controller;

determines that none of the text data is associated with the respective confidence level that exceeds the first confidence threshold; and

determines whether any text data is associated with the respective confidence level that exceeds the at least one subsequent confidence threshold.

8. The speech recognition system of claim 7, wherein the decision controller:

determines that none of the text data is associated with the respective confidence level that exceeds the at least one subsequent confidence threshold; and

indicates additional processing is required to translate the raw audio data.

9. The speech recognition system of claim 7, wherein:

the at least one subsequent confidence threshold comprises a first subsequent confidence threshold and a second subsequent confidence threshold that is lower than the first subsequent confidence threshold; and

the decision controller;

determines that none of the text data is associated with a confidence level that exceeds the first subsequent confidence threshold;

determines that at least one text data is associated with a confidence level that exceeds the second subsequent confidence threshold; and

indicates additional processing on the at least one text data is required to translate the raw audio data.

18. The speech recognition system of claim 1, wherein the one or more filters comprises at least one of a blind source filter, a phase shift filter, a subtract spectrum filter, a comb filter, a low pass filter, a high pass filter, and a band pass filter.

19. The speech recognition system of claim 1, wherein the occurrence threshold is at least three.

20. The speech recognition system of claim 7, wherein the at least one subsequent confidence threshold is within a range of 40% to 75%.

10. A computer-implemented method of operating an uncontrolled environment-based recognition system for recognizing speech, the method comprising:

operating one or more filters to each generate a set of processed audio data based on raw audio data received from one or more computing devices, the one or more filters being operated to apply filter processes to the raw audio data to generate the set of processed audio data, wherein the one or more filters comprise at least one filter appropriate for the uncontrolled environment-based recognition system for recognizing speech;

operating a translator to provide a set of translation results for the raw audio data based on the set of processed audio data, each translation result being associated with at least one processed audio data and each translation result including a text data and a confidence level associated with that text data; and

in response to receiving the set of translation results, automatically trigger a decision controller to select the text data that corresponds to the raw audio data, wherein the decision controller is operable to;

identify at least one translation result from the set of translation results that includes the text data associated with the confidence level that exceeds a confidence threshold;

determine whether the identified at least one translation result comprises more than one translation result;

in response to determining the identified at least one translation result comprises more than one translation result, determine an occurrence frequency for each text data of the identified at least one translation result and select the text data based on the occurrence frequency, the occurrence frequency representing a number of times that the text data appears in the set of translation results; and

generate an output signal associated with the selection by the decision controller.

11. The computer-implemented method of claim 10, wherein the filter processes comprise at least two different filter processes.

12. The computer-implemented method of claim 10, wherein each translation result comprises a sub-set of translation results for at least one of the processed audio data, the sub-set of translation results including two or more text data and each text data is associated with a respective confidence level.

13. The computer-implemented method of claim 12, wherein the two or more text data correspond to alternative representations of the raw audio data.

14. The computer-implemented method of claim 10 further comprises selecting the text data associated with a highest occurrence frequency as the text data that corresponds to the raw audio data.

15. The computer-implemented method of claim 10, wherein

the confidence threshold comprises a set of confidence thresholds, the set of confidence thresholds including a first confidence threshold and at least one subsequent confidence threshold that is lower than the first confidence threshold;

and

the method further comprises;

determining that none of the text data is associated with the respective confidence level that exceeds the first confidence threshold; and

determining whether any text data is associated with the respective confidence level that exceeds the at least one subsequent confidence threshold.

16. The computer-implemented method of claim 15 further comprises:

determining that none of the text data is associated with the respective confidence level that exceeds the at least one subsequent confidence threshold; and

indicating additional processing is required to translate the raw audio data.

17. The computer-implemented method of claim 15, wherein

the at least one subsequent confidence threshold comprises a first subsequent confidence threshold and a second subsequent confidence threshold that is lower than the first subsequent confidence threshold;

and

the method further comprises;

determining that none of the text data is associated with a confidence level that exceeds the first subsequent confidence threshold;

determining that at least one text data is associated with a confidence level that exceeds the second subsequent confidence threshold; and

indicating additional processing on the at least one text data is required to translate the raw audio data.

21. The computer-implemented method of claim 10, wherein the one or more filters comprises at least one of a blind source filter, a phase shift filter, a subtract spectrum filter, a comb filter, a low pass filter, a high pass filter, and a band pass filter.

22. The computer-implemented method of claim 15, wherein the at least one subsequent confidence threshold is within a range of 40% to 75%.