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Identifying speakers in novels aims at determining who says a quote in a given context by text analysis. This task is important for speech synthesis systems to assign appropriate voices to the quotes when producing audio books. Several English datasets have been constructed for this task. However, the difference between English and Chinese impedes processing Chinese novels using the models built on English datasets directly. Therefore, this paper presents a Chinese dataset, which contains 2,548 quotes from World of Plainness, a famous Chinese novel, with manually labelled speaker identities. Furthermore, two baseline speaker identification methods, i.e., a rule-based one and a classifier-based one, are designed and experimented using this Chinese dataset. These two methods achieve accuracies of 53.77% and 58.66% respectively on the test set.