3.2.3 Step 8 - Realigning the Training Data

As noted earlier, the dictionary contains multiple pronunciations for some words, particularly function words. The phone models created so far can be used to realign the training data and create new transcriptions. This can be done with a single invocation of the  HTK recognition tool HVITE , viz

    HVite -l '*' -o SWT -b silence -C config -a -H hmm7/macros \
        -H hmm7/hmmdefs -i aligned.mlf -m -t 250.0  -I words.mlf \
        -S train.scp  dict monophones1

This command uses the HMMs stored in hmm7 to tranform the input word level transcription words.mlf to the new phone level transcription aligned.mlf using the pronunciations stored in the dictionary dict (see Fig 3.11). The key difference between this operation and the original word-to-phone mapping performed by HLED in step 4 is that the recogniser considers all pronunciations for each word and outputs the pronunciation that best matches the acoustic data.   

In the above, the -b option is used to insert a silence model  at the start and end of each utterance. The name silence is used on the assumption that the dictionary contains an entry

    silence sil

The -t option sets a pruning level of 250.0 and the -o option is used to suppress the printing of scores, word names and time boundaries in the output MLF.

 

Once the new phone alignments have been created, another 2 passes of HEREST can be applied to reestimate the HMM set parameters again. Assuming that this is done, the final monophone HMM set will be stored in directory hmm9.