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A trademark is a mark used to identify various commodities. If same orsimilar trademark is registered for the same or similar commodity, thepurchaser of the goods may be confused. Therefore, in the process of trademarkregistration examination, the examiner judges whether the trademark is the sameor similar to the other applied or registered trademarks. The confusion intrademarks is based on the visual, phonetic or conceptual similarity of themarks. In this paper, we focus specifically on the phonetic similarity betweentrademarks. We propose a method to generate 2D phonetic feature forconvolutional neural network in assessment of trademark similarity. Thisproposed algorithm is tested with 12,553 trademark phonetic similar pairs and34,020 trademark phonetic non-similar pairs from 2010 to 2016. As a result, wehave obtained approximately 92% judgment accuracy.

2-gram-based Phonetic Feature Generation for Convolutional Neural Network in Assessment of Trademark Similarity