Speech analytics system and system and method for determining structured speech

• US 8,719,016 B1
• Filed: 04/07/2010
• Issued: 05/06/2014
• Est. Priority Date: 04/07/2009
• Status: Active Grant

• Current Assignee: Verint Systems Incorporated
• Original Assignee: Verint Americas Incorporated (Verint Systems Incorporated)
• Inventors: Ziv, Omer, Achituv, Ran, Shapira, Ido
• Primary Examiner(s): Saint Cyr, Leonard
• Application Number:
  US12/755,549
• Time in Patent Office: 1,490 Days
• Field of Search: None
• US Class Current: 704/235
• CPC Class Codes: G10L 15/19 Grammatical context, e.g. disambiguation of the recognition hypotheses based on word sequence rules
• CPC Class Codes: G10L 15/197 Probabilistic grammars, e.g. word n-grams
• 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

Abstract

A method for converting speech to text in a speech analytics system is provided. The method includes receiving audio data containing speech made up of sounds from an audio source, processing the sounds with a phonetic module resulting in symbols corresponding to the sounds, and processing the symbols with a language module and occurrence table resulting in text. The method also includes determining a probability of correct translation for each word in the text, comparing the probability of correct translation for each word in the text to the occurrence table, and adjusting the occurrence table based on the probability of correct translation for each word in the text.

Claims

1. A method for determining structured speech, the method comprising:

translating an audio recording into text using a text-to-speech communication processing system;

receiving a transcript of the audio recording;

analyzing text in the transcript to determine repetitions within the text, the repetitions being indicative of structured speech, wherein the text is analyzed using Large Vocabulary Continuous Speech Recognition (LVCSR);

determining a duration distribution of the repetitions to ascertain a first type of structured speech; and

determining a length of the repetitions to ascertain a second type of structured speech;

comparing probability of correct translation of the text-to-speech communication for each word in the text to an appropriate occurrence table, wherein the occurrence table is selected based upon dialect or language of the speech, and domain in which the speech was obtained; and

modifying the occurrence table based on the probability of correct translation for each word in the text.

2. The method of claim 1, further comprising determining a third type of structured speech when the length of the repetitions is greater than a predetermined threshold.

3. The method of claim 2, wherein the first type of structured speech is interactive voice response (IVR) generated speech, wherein the second type of structured speech is scripts, and wherein the third type of structured speech is figures of speech.

4. The method of claim 1, further comprising applying a distance threshold to determine contacts that contain the second type of structured speech.

5. The method of claim 4, wherein the distance threshold is approximately 18.

6. The method of claim 1, further comprising analyzing the second type of speech to determine one of compliance, quality management, and categories.

7. The method of claim 6, further comprising:

defining the second type of speech as a category; and

evaluating a contact to determine if the contact contains the category.

8. The method of claim 6, further comprising using the second type of speech as a filter in a query.

9. The method of claim 1, further comprising:

storing the second type of structured speech in a database; and

applying meta data to the second type of structured speech to annotate the second type of structured speech.

10. The method of claim 1, wherein modification of the occurrence table changes the occurrence probability by a fixed percentage or a variable percentage based on the probability of correct translation of a given word.

11. A method of determining scripts within speech associated with a contact center, comprising:

translating a speech into text using a text-to-speech communication processing system;

receiving a transcript of the speech;

analyzing the transcript to determine repetitions within the speech that are indicative of structured speech, wherein the text is analyzed using Large Vocabulary Continuous Speech Recognition (LVCSR); and

determining a duration distribution and length of the repetitions with the speed to determine which repetitions are scripts;

comparing probability of correct translation of the text-to-speech communication for each word in the text to an appropriate occurrence table, wherein the occurrence table is selected based upon dialect or language of the speech, and domain in which the speech was obtained; and

modifying the occurrence table based on the probability of correct translation for each word in the text.

12. The method of claim 11, further comprising:

storing a corpus of contacts in a database; and

applying a distance threshold to determine the contacts that contain the scripts.

13. The method of claim 11, further comprising applying analytics to the scripts to categorize the scripts.

14. The method of claim 13, further comprising querying contacts using categories of scripts.

15. The method of claim 11, wherein modification of the occurrence table changes the occurrence probability by a fixed percentage or a variable percentage based on the probability of correct translation of a given word.