Abstract: A method for operating a server system that includes a plurality of servers for processing a voice command recorded by a recording device connected, via an interface, to the server system includes, in response to the recording of the voice command, reading in a session activation signal from the recording device; checking if there is an association between the session activation signal and a session ID; if it is established that there is the association between the session activation signal and the session ID, ascertaining an availability of a prior server that previously processed a session assigned to the session ID; and activating the session on the prior server if it is available, but, if it is not available, then activating the session on a free server of the server system by loading the session from a session database. The voice command is received by the corresponding server during the activation of the session or even subsequent to the activation of the session, in order to be processed.

Abstract: A method for operating a server system that includes a plurality of servers for processing a voice command recorded by a recording device connected, via an interface, to the server system includes, in response to the recording of the voice command, reading in a session activation signal from the recording device; checking if there is an association between the session activation signal and a session ID; if it is established that there is the association between the session activation signal and the session ID, ascertaining an availability of a prior server that previously processed a session assigned to the session ID; and activating the session on the prior server if it is available, but, if it is not available, then activating the session on a free server of the server system by loading the session from a session database. The voice command is received by the corresponding server during the activation of the session or even subsequent to the activation of the session, in order to be processed.

Abstract: Embodiments of a name recognition process for use in dialog systems are described. In one embodiment, the name recognition process assigns weighting values to names used in a dialog based on the usage of these names. This process takes advantage of the general tendency of people to speak names, either full or partial, only after they have heard or read these names. Name input is taken in several different forms, including a static background database that contains all possible names, a background database that contains commonly used names (such as common trademarks or references), a database that contains names from a user model, and a dynamic database that constantly takes the names just mentioned. The names are then appended with proper weighting values. A high weight is given to names that have been mentioned recently, a lower weight is given to common names, and a lowest weight is given to names for the ones that have never been used or mentioned.

Abstract: Representation-neutral dialogue systems and methods (“RNDS”) are described that include multi-application, multi-device spoken-language dialogue systems based on the information-state update approach. The RNDS includes representation-neutral core components of a dialogue system that provide scripted domain-specific extensions to routines such as dialogue move modeling and reference resolution, easy substitution of specific semantic representations and associated routines, and clean interfaces to external components for language-understanding (i.e., speech-recognition and parsing) and language-generation, and to domain-specific knowledge sources. The RNDS also resolves multi-device dialogue by evaluating and selecting among candidate dialogue moves based on features at multiple levels. Multiple sources of information are combined, multiple speech recognition and parsing hypotheses tested, and multiple device and moves considered to choose the highest scoring hypothesis overall.

Abstract: Embodiments of a name recognition process for use in dialog systems are described. In one embodiment, the name recognition process assigns weighting values to names used in a dialog based on the usage of these names. This process takes advantage of the general tendency of people to speak names, either full or partial, only after they have heard or read these names. Name input is taken in several different forms, including a static background database that contains all possible names, a background database that contains commonly used names (such as common trademarks or references), a database that contains names from a user model, and a dynamic database that constantly takes the names just mentioned. The names are then appended with proper weighting values. A high weight is given to names that have been mentioned recently, a lower weight is given to common names, and a lowest weight is given to names for the ones that have never been used or mentioned.

Abstract: Representation-neutral dialogue systems and methods (“RNDS”) are described that include multi-application, multi-device spoken-language dialogue systems based on the information-state update approach. The RNDS includes representation-neutral core components of a dialogue system that provide scripted domain-specific extensions to routines such as dialogue move modeling and reference resolution, easy substitution of specific semantic representations and associated routines, and clean interfaces to external components for language-understanding (i.e., speech-recognition and parsing) and language-generation, and to domain-specific knowledge sources. The RNDS also resolves multi-device dialogue by evaluating and selecting among candidate dialogue moves based on features at multiple levels. Multiple sources of information are combined, multiple speech recognition and parsing hypotheses tested, and multiple device and moves considered to choose the highest scoring hypothesis overall.