Following utterances are generated using evaluate.py script. First raw represents predicted utternace and the second is ground truth
target.
Speaker 7 utterance 0
Speaker 12 utterance 2
Speaker 4 utterance 3
Speaker 11 utterance 4
Speaker 3 utterance 5
Speaker 15 utterance 10
Speaker 17 utterance 17
Speaker 1 utterance 23
Speakers
The speaker indeces correspond to speker directories in Liepa database in order specified in dataset (See var. available_speakers). Notice that only speakers with sentence utterances were considered.