word graph based speech rcognition error correction by handwriting input
We propose a convenient handwriting user interface for correcting speech recognition errors efficiently. Via the proposed hand-marked correction on the displayed recognition result, substitution, deletion and insertion errors can be corrected efficiently by rescoring the word graph generated in the recognition pass. A new path in the graph that matches the user's feedback in the maximum likelihood sense is found.With the aid of language model and hand corrections part in the best decoded path, rescoring the word graph can correct more errors than user provides. All recognition errors can be corrected after finite number of corrections. Experimental results show that by indicating one word error in user feedback, 33.8\% of the erroneous sentences can be corrected; while by indicating one character error, 12.9\% of the erroneous sentences can be corrected.
word graph speech recognition interactive error correction handwriting recognition multimodal interface