Speech recognition error correction method, related devices, and readable storage medium

A speech recognition error correction device comprising:

• an acquisition unit configured to acquire to-be-recognized speech data and a first recognition result of the speech data;
• a keyword extraction unit configured to extract a correctly recognized field-specific word from the first recognition result as a keyword;
• a second speech recognition unit configured to re-recognize the speech data with reference to context information in the first recognition result and the keyword to obtain a second recognition result, comprising:
• acquiring an acoustic feature of the speech data;
• and
• inputting the acoustic feature of the speech data, the first recognition result and the keyword to a pre-trained speech recognition error correction model to obtain the second recognition result, wherein the speech recognition error correction model is obtained by training a preset model with an error-correction training data set, wherein the speech recognition error correction model is a neural network-based model, wherein the inputting the acoustic feature of the speech data, the first recognition result and the keyword to the pre-trained speech recognition error correction model to obtain the second recognition result comprises performing encoding and attention calculation on the acoustic feature of the speech data, the first recognition result and the keyword by using the speech recognition error correction model, to obtain the second recognition result based on a calculation result, wherein the performing encoding and attention calculation on the acoustic feature of the speech data, the first recognition result and the keyword by using the speech recognition error correction model to obtain the second recognition result based on the calculation result comprises:
• performing encoding and attention calculation on each of the acoustic feature of the speech data, the first recognition result and the keyword by using an encoding layer and an attention layer of the speech recognition error correction model to obtain the calculation result;
• and
• decoding the calculation result by using a decoding layer of the speech recognition error correction model to obtain the second recognition result;
• and
• a recognition result determination unit configured to determine a final recognition result based on the second recognition result.