초록 ▼

A method and system for charging a fee to an end user where a service company services a lighting system of the end user's facility. To determine the fee, an original power consumption of the facility is determined before the lighting system is retrofitted with at least one power savings device. The

A method and system for charging a fee to an end user where a service company services a lighting system of the end user's facility. To determine the fee, an original power consumption of the facility is determined before the lighting system is retrofitted with at least one power savings device. Thereafter, the lighting system is retro-fitted with the at least one power saving device. Then, a new power consumption is measured of the facility. Finally, the fee is charged to the end user, such that the fee is a function of a difference between the original power consumption and the new power consumption.

대표청구항 ▼

A method and system for charging a fee to an end user where a service company services a lighting system of the end user's facility. To determine the fee, an original power consumption of the facility is determined before the lighting system is retrofitted with at least one power savings device. The

A method and system for charging a fee to an end user where a service company services a lighting system of the end user's facility. To determine the fee, an original power consumption of the facility is determined before the lighting system is retrofitted with at least one power savings device. Thereafter, the lighting system is retro-fitted with the at least one power saving device. Then, a new power consumption is measured of the facility. Finally, the fee is charged to the end user, such that the fee is a function of a difference between the original power consumption and the new power consumption. erein identifying a set of one or more no-cross regions includes identifying a change in utterance energy that satisfies specified no-cross region criteria. 11. The method as recited in claim 10, wherein the specified no-cross region criteria includes a minimum increase in utterance energy and identifying a set of one or more no-cross regions includes identifying an increase in utterance energy that exceeds the minimum increase in utterance energy. 12. The method as recited in claim 11, wherein the specified no-cross region criteria includes a minimum decrease in utterance energy and identifying a set of one or more no-cross regions includes identifying a decrease in utterance energy that exceeds the minimum decrease in utterance energy. 13. The method as recited in claim 11, wherein the specified no-cross region criteria includes dip no-cross region criteria and identifying a set of one or more no-cross regions includes identifying a region of utterance data with a dip in energy that satisfies the dip no-cross region criteria. 14. The method as recited in claim 11, wherein the specified no-cross region criteria includes broad category change no-cross region criteria and identifying a set of one or more no-cross regions includes identifying a region of utterance data over which the broad phonetic classification changed sufficiently to satisfy the broad category no-cross region criteria. 15. The method as recited in claim 1, wherein the step of selecting the set of phonetic units from the set of filtered candidate phonetic units includes selecting the set of N number of phonetic units having the relatively highest probability of boundaries at the ends and relatively lowest probability of boundaries internal to the unit. 16. A computer-readable medium carrying one or more sequences or one or more instructions for automatically determining a set of phonetic units from a body of utterance data, the one or more sequences or one or more instructions including instructions which, when executed by one or more processors, cause the one or more processors to perform the steps of: receiving the body of utterance data; determining a first set of candidate phonetic units from the body of utterance data; determining a set of no-cross regions from the body of utterance data wherein the no-cross regions correspond to a time span of utterance data having a high probability of containing a boundary between phonetic units; filtering the first set of candidate phonetic units to generate a subset of candidate phonetic units therefrom wherein the filtering analyzes the candidate phonetic units to determine if the candidate spans a no-cross region for the utterance data such that the subset omits candidate phonetic units which spanned a no-cross region. 17. The computer-readable medium as recited in claim 16, wherein the step of determining a set of candidate phonetic units from the body of utterance data includes identifying peaks in a smoothed Cepstral change measure. 18. The computer-readable medium as recited in claim 16, wherein the step of determining a set of candidate phonetic units from the body of utterance data includes identifying peaks in a smoothed energy change measure. 19. The computer-readable medium as recited in claim 16, wherein the step of determining a set of candidate phonetic units from the body of utterance data includes identifying peaks in a smoothed phonetic classification measure. 20. The computer-readable medium as recited in claim 16, wherein the step of determining a set of candidate phonetic units from the body of utterance data includes identifying the presence of regions with a high probability of belonging to some broad phonetic category and adding boundaries at the edges. 21. The computer-readable medium as recited in claim 16, wherein the step of determining a set of candidate phonetic units from the body of utterance data includes detecting the onset of a sonorant and adding an additional boundary to ac