Diagnosing voice application issues of an operational environment

• US 7,505,569 B2
• Filed: 03/18/2005
• Issued: 03/17/2009
• Est. Priority Date: 03/18/2005
• Status: Expired due to Fees

• Current Assignee: Nuance Communications, Inc. (Microsoft Corporation)
• Original Assignee: International Business Machines Corporation
• Inventors: Dhanakshirur, Girish
• Primary Examiner(s): Tsang; Fan
• Assistant Examiner(s): SING, SIMON P
• Application Number:
  US11/083,522
• Publication Number:
  US 20060210025A1
• Time in Patent Office: 1,460 Days
• Field of Search: 379/88.14, 379/88.17, 704/270, 704/275, 704/277
• US Class Current: 379/88.14
• CPC Class Codes: H04M 2201/60 Medium conversion
• CPC Class Codes: H04M 3/2227 Quality of service monitoring
• CPC Class Codes: H04M 3/493 Interactive information services, e.g. directory enquiries ; Arrangements therefor, e.g. interactive voice response [IVR] systems or voice portals

Abstract

A computerized method for diagnosing deployed voice-enabled application issues within a maintenance environment. The method can identify a recognition log file that includes details of previously occurring interactions of a voice-enabled application executing programmatic actions in an operational environment. The voice-enabled application can utilize a speech recognition service to convert utterances to text. Previously occurring interactions of the operational environment can be simulated in a maintenance environment. The maintenance environment can include a maintenance voice-enabled application component used in place of the voice-enabled application and can include a text-based speech recognition service used in place of the speech recognition service. The text-based speech recognition service can extract text from the recognition log file to simulate previously occurring utterance conversions performed by the speech recognition service without requiring the text-based speech recognition service to receive and convert utterances.

Claims

1. A computerized method for diagnosing deployed voice-enabled application issues within a maintenance environment comprising the steps of:

identifying a recognition log file that includes details of previously occurring interactions of a voice-enabled application executing programmatic actions in an operational environment, said voice-enabled application utilizing a speech recognition service to convert utterances to text, wherein said recognition log file is a session-specific log file and wherein the previously occurring interactions are interactions of a communication session involving a user and the voice-enabled application, and wherein the speech recognition service performs utterance conversions for a plurality of applications and conveys tasks to a cluster of automated speech recognition engines, which are used to perform the utterance conversions;

simulating said previously occurring interactions in a maintenance environment, said maintenance environment including a maintenance voice-enabled application component used in place of the voice-enabled application and including a text-based speech recognition service used in place of the speech recognition service;

said text-based speech recognition service extracting text from the recognition log file to simulate previously occurring utterance conversions performed by the speech recognition service without requiring the text-based speech recognition service to receive and convert utterances;

in the operational environment, detecting a technical problem during the communication session, and responsive to the detecting, automatically conveying the session-specific log file along with a problem indication to the maintenance environment.

2. A text based recognition service component comprising:

a event receiving mechanism configured to receive recognition requests originating from a voice browser;

a recognition log reading mechanism configured to extract textual information from a recognition log file to simulate previously occurring utterance conversions; and

an event response mechanism configured provide a response for each received recognition request based upon the extracted textual information, wherein the text-based recognition service component is a component of a maintenance environment used in place of a recognition service component of an operational environment, wherein at least a portion of the extracted textual information was previously placed within the recognition log file by the recognition service component

wherein the recognition log file is a session log for an interaction session involving a user and the voice browser, wherein the voice browser interfaces with a speech recognition service in a manner determined by voice-based markup code, and wherein the speech recognition service performs tasks on a per-turn basis, and wherein the recognition log file includes an entry for each turn.

3. A problem diagnostic method comprising the steps of:

in a session log, logging events handled by a speech recognition service for a deployed voice application during a telephony session, for each logged speech conversion event, said session log including a plurality of textual results, comprising a selected textual result and at least one alternative textual result, and a corresponding confidence score for each textual result, wherein said speech recognition service performs tasks on a per-turn basis, wherein the session log includes an entry for each turn, and wherein said plurality of textual results includes the n-best results generated for each utterance, the n of the n-best results being a parameter for the number of text results returned per utterance conversion and said n-best results being those results having greatest relative confidence scores;

in a maintenance environment that simulates the telephony session, reaching a point in a telephony session simulation where the speech recognition service handled an event;

conveying an indication of the event to a replacement component for the speech recognition service;

when the conveyed indication is a speech conversion event, said replacement component extracting from the session log the at least one textual result and corresponding confidence score associated with the speech conversion event; and

utilizing the extracted data from the session log within the maintenance environment as a simulation equivalent of results that were generated by the speech recognition service.