System and method for caller intent labeling of the call-center conversations

Patent metadata

Field	Value
Publication number	US-2015179165-A1
Application number	US-201314135498-A
Country	US
Kind code	A1
Filing date	Dec 19, 2013
Priority date	Dec 19, 2013
Publication date	Jun 25, 2015
Grant date	—

Abstract

Labeling a call, for instance by identifying an intent (i.e., the reason why the caller has called into the call center), of a caller in a conversation between a caller and an agent is a useful task for efficient customer relationship management (CRM). In an embodiment, a method of labeling sentences for presentation to a human can include selecting an intent bearing excerpt from sentences, presenting the intent bearing excerpt to the human, and enabling the human to apply a label to each sentence based on the presentation of the intent bearing excerpt. The method can reduce a manual labeling budget while increasing the accuracy of labeling models based on manual labeling.

First claim

What is claimed is:

1 . A method of labeling sentences for presentation to a human, the method comprising:
in a processor: selecting an intent bearing excerpt from sentences stored in a database; presenting the intent bearing excerpt to the human; and enabling the human to apply a label to each sentence based on the presentation of the intent bearing excerpt, the label being stored in a field of the database corresponding to the respective sentence.

2 . The method of claim 1 , further comprising training the selecting of the intent bearing excerpt through use of manual input.

3 . The method of claim 2 , further comprising filtering the sentences used for training based on an intelligibility threshold.

4 . The method of claim 3 , wherein the intelligibility threshold is an automatic speech recognition confidence threshold.

5 . The method of claim 1 , further comprising:
choosing a representative sentence of a set of sentences based on at least one of similarity of the sentences of the set or similarity of intent bearing excerpts of the set of sentences; and applying the label to the entire set based on the label chosen for the intent bearing excerpt of the representative sentence.

6 . The method of claim 1 , wherein the intent bearing excerpt is a non-contiguous portion of the sentences.

7 . The method of claim 1 , further comprising determining a part of the excerpt likely to include an intent of the sentences; and
wherein selecting the intent bearing excerpt includes focusing the selection on the part of the excerpt that includes the intent.

8 . The method of claim 1 , further comprising loading the sentences by loading a record that includes a dialogue, monologue, transcription, dictation, or combination thereof.

9 . The method of claim 1 , further comprising annotating the excerpt with a suggested label and presenting the excerpt with the suggested annotation to the human.

10 . The method of claim 1 , further comprising presenting the intent bearing excerpt to a third party.

11 . A system for labeling sentences for presentation to a human, the system comprising:
a selection module configured to select an intent bearing excerpt from sentences stored in a database; a presentation module configured to present the intent bearing excerpt to the human; and a labeling module configured to enable the human to apply a label to each sentence based on the presentation of the intent bearing excerpt, the label being stored in a field of the database corresponding to the respective sentence.

12 . The system of claim 11 , further comprising a training module configured to train the selection module through use of manual input.

13 . The system of claim 12 , further comprising a filtering module configured to filter the sentences used for training based on an intelligibility threshold.

14 . The system of claim 13 , wherein the filtering module is configured to employ the intelligibility threshold as an automatic speech recognition confidence threshold.

15 . The system of claim 11 , further comprising a sampling module configured to choose a representative sentence of a set of sentences based on at least one of similarity of the sentences of the set or similarity of intent bearing excerpts of the set of sentences, and apply the label to the entire set based on the label chosen for the intent bearing excerpt of the representative sentence.

16 . The system of claim 11 , wherein the selection module is further configured to determine a part of the excerpt likely to include an intent of the sentences and select the intent bearing excerpt by focusing the selection on the part of the excerpt that includes the intent.

17 . The system of claim 11 , wherein the selection module is further configured to load the sentences by loading a record that includes a dialogue, monologue, transcription, dictation, or combination thereof.

18 . The system of claim 11 , wherein the labeling module is further configured to annotate the excerpt with a suggested label and presenting the excerpt with the suggested annotation to the human.

19 . The system of claim 11 , further comprising presenting the intent bearing excerpt to a third party.

20 . A non-transitory computer-readable medium configured to store instructions for labeling sentences for presentation to a human, the instructions, when loaded and executed by a processor, causes the processor to:
select an intent bearing excerpt from sentences in a database; present the intent bearing excerpt to the human; and enable the human to apply a label to each sentence based on the presentation of the intent bearing excerpt, the label being stored in a field of the database corresponding to the respective sentence.

Assignees

• Nuance Communications Inc

Inventors

• Mohamed Shajith Ikbal
• Ghosh Prasanta Kumar
• Verma Ashish
• Marcus Jeffrey N
• Church Kenneth W

Classifications

• G06F40/35

  Discourse or dialogue representation · CPC title

• H04M2203/2038

  Call context notifications · CPC title

• H04M3/5133

  Operator terminal details · CPC title

• H04M2201/40

  using speech recognition · CPC title

• G10L15/08 Primary

  Speech classification or search · CPC title