Generation of training data for verbal harassment detection
AssigneeBeijing Didi Infinity Technology and Development Co., Ltd.
InventorsYing Lyu, Kun Han
Life of this patent
Estimating the term…
Abstract
In some cases, one or more heuristics can be automatically generated using a small dataset of segments previously labeled by one or more domain experts. The generated one or more heuristics along with one or more patterns can be used to assign training labels to a large unlabeled dataset of segments. A subset of segments representing an occurrence of verbal harassment can be selected using the assigned training labels. Randomly selected segments can be used as being indicative of a non-occurrence of verbal harassment. The selected subset of segments and randomly selected segments can be used to train one or more machine learning models for verbal harassment detection.
Claims20
A computer-implemented method of training a machine learning model for detection of verbal harassment, the method comprising:
- by one or more hardware processors:
- determining a plurality of verbal harassment heuristics using a first plurality of segments, the segments of the first plurality of segments previously labeled with an occurrence of verbal harassment or a non-occurrence of verbal harassment;
- determining a plurality of labels for a second plurality of segments by applying the plurality of verbal harassment heuristics and a plurality of verbal harassment patterns, the segments of the second plurality of segments not previously labeled with the occurrence or the non-occurrence of verbal harassment;
- aggregating the plurality of labels into a plurality of likelihoods for the occurrence of verbal harassment;
- selecting a subset of segments from the second plurality of segments based on comparing the plurality of likelihoods to at least one threshold;
- and
- training a machine learning model for verbal harassment detection using the subset of segments from the second plurality of segments and a plurality of randomly selected segments.
A non-transitory computer readable medium storing instructions that, when executed by at least one processor, cause the at least one processor to perform a method comprising:
- determining a plurality of verbal harassment heuristics using a first plurality of segments, the segments of the first plurality of segments previously labeled with an occurrence of verbal harassment or a non-occurrence of verbal harassment;
- determining a plurality of labels for a second plurality of segments by applying the plurality of verbal harassment heuristics and a plurality of verbal harassment patterns, the segments of the second plurality of segments not previously labeled with the occurrence or the non-occurrence of verbal harassment;
- aggregating the plurality of labels into a plurality of likelihoods for the occurrence of verbal harassment;
- selecting a subset of segments from the second plurality of segments based on comparing the plurality of likelihoods to at least one threshold;
- and
- training a machine learning model for verbal harassment detection using the subset of segments from the second plurality of segments and a plurality of randomly selected segments.
Dependencies are inferred from the claim text.