A method for enabling training a machine-learning, ML, model for trigger-word detection, the method being performed in a training data provider , the method comprising: receiving sound-based data, the sound-based data being based on sounds captured in a space to be monitored; determining that the sound-based data corresponds to a trigger word, and labelling this sound-based data to correspond to the trigger word; and providing the labelled sound-based data to train the ML model; wherein the determining that the sound-based data corresponds to a trigger word comprises: performing speech recognition of the sound-based data; finding a section of sound-based data that, using the speech recognition, fails to be considered to be a trigger word, but is close to being considered to be a trigger word, wherein close is determined by a metric of speech-recognition similarity between the sound-based data and the trigger word being higher than a threshold, but lower than a threshold to consider the sound-based data to correspond to the trigger word; obtaining semantic vector data based on the found section of sound-based data; and determining that the found section of sound-based data corresponds to a trigger word when a distance, in vector space, between the semantic vector of the sound-based data and a vector corresponding to the trigger word, is less than a threshold distance. receiving sound-based data, the sound-based data being based on sounds captured in a space to be monitored; determining that the sound-based data corresponds to a trigger word, and labelling this sound-based data to correspond to the trigger word; and providing the labelled sound-based data to train the ML model; wherein the determining that the sound-based data corresponds to a trigger word comprises: performing speech recognition of the sound-based data; finding a section of sound-based data that, using the speech recognition, fails to be considered to be a trigger word, but is close to being considered to be a trigger word, wherein close is determined by a metric of speech-recognition similarity between the sound-based data and the trigger word being higher than a threshold, but lower than a threshold to consider the sound-based data to correspond to the trigger word; obtaining semantic vector data based on the found section of sound-based data; and determining that the found section of sound-based data corresponds to a trigger word when a distance, in vector space, between the semantic vector of the sound-based data and a vector corresponding to the trigger word, is less than a threshold distance. performing speech recognition of the sound-based data; finding a section of sound-based data that, using the speech recognition, fails to be considered to be a trigger word, but is close to being considered to be a trigger word, wherein close is determined by a metric of speech-recognition similarity between the sound-based data and the trigger word being higher than a threshold, but lower than a threshold to consider the sound-based data to correspond to the trigger word; obtaining semantic vector data based on the found section of sound-based data; and determining that the found section of sound-based data corresponds to a trigger word when a distance, in vector space, between the semantic vector of the sound-based data and a vector corresponding to the trigger word, is less than a threshold distance. <EOS>