Semi-supervised training of destination map for call handling applications

#The present invention pertains to systems that employ automatic speech recognition. More particularly, the present invention relates to the development of destination maps for call handling applications, such as automated directory assistance and call steering.

#Automatic speech recognition technology has undergone rapid advancement in recent years and is finding widespread use in many different applications. One application in which automatic speech recognition is of particular interest is “call handling”. Two examples of call handling applications are automated directory assistance and call steering (or call routing). Automated directory assistance and call steering functions are being used by businesses more and more commonly to handle incoming telephone calls. An automated directory assistance application may receive a spoken request from a telephone caller for a “destination”, such as a telephone listing (telephone number), recognize the caller's speech to identify the requested destination, and provide the requested information to the caller using recorded or synthesized speech. Such a system might be implemented, for example, in a call center associated with a public switched telephone network (PSTN). A call steering system may be similar, except that it can automatically route a call to a spoken destination, rather than merely responding with information. For example, a call steering system can be used to connect a conventional telephone call, or to route a caller through a hierarchical structure of voice-responsive content, such as a “voice web”. Of course, automated directory assistance and call steering functions may also be combined in a given system.

#Call steering and directory assistance applications both operate generally by mapping an incoming utterance (request) to one of many possible destinations. The mapping between the incoming utterance and the desired destination is established by a combination of a speech recognition engine and a mapping engine. The speech recognition engine uses a language model to recognize a caller's speech. The language model may be a speech recognition grammar, for example, which is a data representation of the usable vocabulary and syntax for the set of destinations. As another example, the language model may be a statistical language model. A statistical language model typically includes a larger vocabulary than a grammar but does not include syntax information. Rather than requiring specific word strings to be detected for recognition, a statistical language model includes probabilities of occurrence for each possible sequence of words in the vocabulary. In general, the sequence of words with the highest probability for a particular input is taken as the recognition result.

#The present invention is illustrated by way of example and not limitation in the figures of the accompanying drawings, in which like references indicate similar elements and in which:

#FIG. 1 illustrates a system for automatically developing destination maps for a call handling application;

#FIG. 2 is a flow diagram illustrating a process performed by the system of FIG. 1 to automatically create a destination map;

#Before releasing a destination to a caller, a call handling system of the type described herein asks the caller whether the destination it found based on the caller's request is correct. If the system has low confidence with its listing hypothesis, or if the caller responds negatively to confirmation, then the call is redirected to an operator, who is assumed to be efficient in his interaction with the caller. As a result, one can have confidence that the final released destination reflects the desired destination with reasonable accuracy. This characteristic of call handling data permits accuracy evaluation with no further transcription or supervision of the data.

#Hence, as described in greater detail below, a destination map for automated call handling can be constructed based on multiple telephone calls to a call handling system. The destination map may include one or more grammars, statistical destination maps (e.g., a statistical semantic model), or a combination thereof. For each call, speech from the caller is recorded in the system during a dialog between the caller and a human operator. The speech represents a request by the caller for a destination. Also recorded in the system is destination identifying information specified by user input from the operator in response to the request. An automatic speech recognizer may be used to recognize the speech from the caller. The recorded speech and the recorded destination identifying information can be used to automatically build the destination map. The destination map may then be used to automatically associate recognized speech from a subsequent caller with a corresponding destination, either in the same call handling system or in a different call handling system.

#In this description, the term “destination” can mean, for example, a telephone listing (telephone number), an address, a name, a part of an organization, a topic or category of information, or any other type of entity or information which a caller may wish to contact or otherwise access.