Abstract: A text error correction method includes splitting a text obtained by automatic speech recognition into short sentences; inputting each of the short sentences into a trained error correction model, respective parameters in each layer of the model are synchronously updated during training thereof; acquiring phoneme information by the phoneme extractor; converting the phoneme information into a phoneme feature by the phoneme feature encoder; obtaining a language feature by the language feature encoder, combining the phoneme feature and the language feature to obtain a combined feature by the feature combination module; decoding the combined feature to correct an error of the short sentence by the decoder, determining first perplexity and second perplexity of the short sentence, comparing the two kinds of perplexity to determine a correct text of the short sentence, and combining the correct texts of all of the short sentences in order into a correct text.