1. A computer-implemented method comprising: receiving, by at least one processor, digital graphic novel content; producing, by at least one processor, a numerical map that represents an image extracted from the digital graphic novel content; responsive to inputting the numerical map into a first artificial neural network of a machine learning model configured to determine regions of the digital graphic novel content that are likely to include speech bubbles, receiving, by the at least one processor, from the first artificial neural network, a plurality of candidate regions of the digital graphic novel content that are likely to include speech bubbles; and responsive to inputting the plurality of candidate regions into a second artificial neural network of the machine learning model, receiving, by at least one processor, from the second artificial neural network, features of the digital graphic novel content that include a plurality of speech bubbles containing text; generating, by at least one processor, based on the features of the digital graphic novel content, contextual information corresponding to the features, the contextual information including the text of the plurality of speech bubbles in an intended reading order of the plurality of speech bubbles; and automatically translating, by at least one processor, based at least in part on the contextual information, from a first natural language to a second natural language, the text contained in the plurality of speech bubbles to produce translated text.
1. A computer-implemented method comprising: receiving, by at least one processor, digital graphic novel content; producing, by at least one processor, a numerical map that represents an image extracted from the digital graphic novel content; responsive to inputting the numerical map into a first artificial neural network of a machine learning model configured to determine regions of the digital graphic novel content that are likely to include speech bubbles, receiving, by the at least one processor, from the first artificial neural network, a plurality of candidate regions of the digital graphic novel content that are likely to include speech bubbles; and responsive to inputting the plurality of candidate regions into a second artificial neural network of the machine learning model, receiving, by at least one processor, from the second artificial neural network, features of the digital graphic novel content that include a plurality of speech bubbles containing text; generating, by at least one processor, based on the features of the digital graphic novel content, contextual information corresponding to the features, the contextual information including the text of the plurality of speech bubbles in an intended reading order of the plurality of speech bubbles; and automatically translating, by at least one processor, based at least in part on the contextual information, from a first natural language to a second natural language, the text contained in the plurality of speech bubbles to produce translated text. 8. The computer-implemented method of claim 1 , wherein generating the contextual information associated with the features of the digital graphic novel content includes limiting the contextual information to information contained in each panel of the digital graphic novel content that includes the plurality of speech bubbles.