1. An electronic device to execute a context-aware query recognition, the device comprising: an input device to receive user speech; memory to store instructions for performing a context-aware query; and a controller, coupled to the memory and the input device, the controller being configured to: generate a speech signal including applying the user speech to a statistically-based speech recognition algorithm, determine, using a first machine learning process employing at least one of a condition random field, hidden Markov model, or neural network, if the speech signal includes words implying an action and whether the words implying the action request the action to be performed, determine, using a second machine learning process employing at least one of a condition random field, Gaussian mixture model, or neural network, the second machine learning process running in parallel with the first machine learning process, if the speech signal includes words associated with an intended recipient of the user speech, and if the speech signal requests the action to be performed and if the intended recipient of the user speech is the electronic device, generate a command for the electronic device to perform the action, wherein the user speech and the speech signal do not include a wake-up phrase.
1. An electronic device to execute a context-aware query recognition, the device comprising: an input device to receive user speech; memory to store instructions for performing a context-aware query; and a controller, coupled to the memory and the input device, the controller being configured to: generate a speech signal including applying the user speech to a statistically-based speech recognition algorithm, determine, using a first machine learning process employing at least one of a condition random field, hidden Markov model, or neural network, if the speech signal includes words implying an action and whether the words implying the action request the action to be performed, determine, using a second machine learning process employing at least one of a condition random field, Gaussian mixture model, or neural network, the second machine learning process running in parallel with the first machine learning process, if the speech signal includes words associated with an intended recipient of the user speech, and if the speech signal requests the action to be performed and if the intended recipient of the user speech is the electronic device, generate a command for the electronic device to perform the action, wherein the user speech and the speech signal do not include a wake-up phrase. 9. The device of claim 1 , wherein the electronic device is a kitchen appliance, a computer, a control system in a vehicle, a personal electronic device, or a home controller.