7. A method, comprising: identifying a set of entities in video content; for a portion of the video content, identifying first confidence values that are representative of features of the portion and that are a result of a video recognition process, one confidence value of the first confidence values defining a probability that a face of an entity from the set of entities is present; for the portion, identifying second confidence values that are representative of features of the portion and that are a result of an audio recognition process, one confidence value of the second confidence values defining a probability that a category of phone is being uttered by the entity; and based on the first confidence values and the second confidence values, determining, by a computing device, at least one identifier that defines whether the entity is present in the portion.
7. A method, comprising: identifying a set of entities in video content; for a portion of the video content, identifying first confidence values that are representative of features of the portion and that are a result of a video recognition process, one confidence value of the first confidence values defining a probability that a face of an entity from the set of entities is present; for the portion, identifying second confidence values that are representative of features of the portion and that are a result of an audio recognition process, one confidence value of the second confidence values defining a probability that a category of phone is being uttered by the entity; and based on the first confidence values and the second confidence values, determining, by a computing device, at least one identifier that defines whether the entity is present in the portion. 11. The method of claim 7 , wherein determining the second confidence values comprises determining the second confidence values using a set of mixture models, wherein each model in the set of mixture models calculates a probability that an input phone belongs to a phone category uttered by the entity, and wherein each model in the set of mixture models corresponds to one of a plurality of phone categories.