Word alignment in bilingual or multilingual parallel corpora has been a challenging issue for natural language engineering. An efficient algorithm for automatically aligning word translation equivalents across different languages will be of use for a number of practical applications such as multilingual lexical construction, machine translation, etc. This paper presents a hybrid algorithm for English–Chinese word alignment, which incorporates co‐occurrence association measures, word distribution distances, English word lemmatization, and part‐of‐speech information. Eleven co‐occurrence association coefficients and eight distance measures of word distribution are explored to compare their efficiency for word alignment. The paper also describes an experiment in which the algorithm is evaluated on sentence‐aligned English–Chinese parallel corpora. In the experiment, the algorithm produced encouraging success rates on two test corpora, with the highest success rate of 89.37 per cent. It provides a practical tool for extracting word translation equivalents from English–Chinese parallel corpora.