A method, performed by a server , of controlling a device (121 to 127) among a plurality of devices in a network environment, based on a speech input, the method comprising: receiving (S1112), from a client device , a speech input of a user; performing (S1120), by a first assistant model , automatic speech recognition, ASR, to convert the received speech input into text by using an ASR model; analyzing (S1130), by a device dispatcher model of the first assistant model , the converted text by parsing the converted text in at least one of morphemes, words and phrases and determine, by using a first natural language understanding, NLU, model , a first intent based on the analysis result; determining (S1140), by the device dispatcher model , a type of a target device based on the first intent; determining (S1150), by the device dispatcher model , a target device from a plurality of previously-registered target device candidates based on the determined type and device information; providing (S1160), by the first assistant model , the parsed text and the device information to a second assistant model ; determining (S1170), by the second assistant model , a second intent and a parameter by analyzing the parsed text by using a second NLU model corresponding to the determined type of the target device among a plurality of second NLU models ; obtaining (S1180), by an action plan management model of the second assistant model , the operation information of operations to be performed by the target device based on the determined second intent and the determined parameter; and providing (S1190), by the second assistant model , the operation information obtained through the action plan management model to the first assistant model . receiving (S1112), from a client device , a speech input of a user; performing (S1120), by a first assistant model , automatic speech recognition, ASR, to convert the received speech input into text by using an ASR model; analyzing (S1130), by a device dispatcher model of the first assistant model , the converted text by parsing the converted text in at least one of morphemes, words and phrases and determine, by using a first natural language understanding, NLU, model , a first intent based on the analysis result; determining (S1140), by the device dispatcher model , a type of a target device based on the first intent; determining (S1150), by the device dispatcher model , a target device from a plurality of previously-registered target device candidates based on the determined type and device information; providing (S1160), by the first assistant model , the parsed text and the device information to a second assistant model ; determining (S1170), by the second assistant model , a second intent and a parameter by analyzing the parsed text by using a second NLU model corresponding to the determined type of the target device among a plurality of second NLU models ; obtaining (S1180), by an action plan management model of the second assistant model , the operation information of operations to be performed by the target device based on the determined second intent and the determined parameter; and providing (S1190), by the second assistant model , the operation information obtained through the action plan management model to the first assistant model . <EOS>