Abstract: Devices and techniques are generally described for generating per-topic review summarization. In some examples, a plurality of text descriptions of a first item may be received. In at least some examples, a list of categories may be determined. In some examples, at least one machine learned model may generate a first summary of the plurality of text descriptions. In some examples, the first summary may be relevant to a first category of the list of categories. In further examples, the at least one machine learned model may generate a second summary of the plurality of text descriptions. The second summary may be relevant to a second category of the list of categories. In various cases, first output data that includes the first summary and the second summary may be generated.