15. A non-transitory computer-readable medium storing software comprising instructions executable by one or more computers which, upon such execution, cause the one or more computers to perform operations comprising: during a trigger phrase enrollment process: prompting a user of the speech recognition-enabled electronic device to speak a trigger phrase; receiving, at the speech recognition-enabled device, a first audio signal corresponding to the user speaking the trigger phrase; determining a number of segments in the first audio signal that have voice activity, each segment comprising a corresponding sequence of continuous frames in the first audio signal that have voice activity; and when the number of segments in the first audio signal that have voice activity satisfies a threshold value, training a trigger phrase model with the first audio signal corresponding to the user speaking the trigger phrase, the trigger phrase model configured to detect the trigger phrase in a spoken utterance; and after the trigger phrase enrollment process: receiving, while the speech recognition-enabled electronic device is in a sleep mode, a second audio signal including an utterance of the trigger phrase spoken by the user; and detecting, using the trigger phrase model trained during the trigger phrase enrollment process, the utterance of the trigger phrase in the second audio signal, the trigger phrase when detected in the second audio signal causing the speech recognition-enabled electronic device to wake from the sleep mode, the sleep mode comprising a power-saving mode of operation in which one or more parts of the speech recognition-enabled electronic device are in a low-power state or powered off.
17. The computer-readable medium of claim 15 , wherein the operations further comprise, for each frame in the received first audio signal: identifying audio characteristics of the user speaking the trigger phrase and audio characteristics of background noise for the corresponding frame in the received first audio signal; comparing the identified audio characteristics of the user speaking the trigger phrase to predetermined threshold values associated with one or more values for trigger phrase model training; and determining a voice activity detection flag for the corresponding frame in the received first audio signal in response to comparing the identified audio characteristics of the user speaking the trigger phrase to the predetermined threshold values.