3. The computer-implemented method according to claim 1 , wherein the generating of the confusion network further comprises aligning, using dynamic programming approximation, tokens of normalized hypotheses based on time information and grapho-phonetical information associated with tokens of the normalized hypotheses.
3. The computer-implemented method according to claim 1 , wherein the generating of the confusion network further comprises aligning, using dynamic programming approximation, tokens of normalized hypotheses based on time information and grapho-phonetical information associated with tokens of the normalized hypotheses. 4. The computer-implemented method according to claim 3 , wherein the aligning uses exact Multiple Sequence Alignment algorithms to perform alignment.