The classic approach for error correction is to add controlled external redundancy to data. This approach, called error-correcting codes, has been studied extensively. And the rates of ECCs are approaching theoretical limits. We explore a second approach for error correction in this work, which is to use the redundancy inside data, even if it is just the residual redundancy after data compression. We focus on text data, and show that this approach based on language processing can significantly improve the error correction performance.