You will be shown an excerpt from a computer science scientific research paper, followed by a question about the paper. Please answer the question. Do not include any text in your response other than the answer.

Context: We closely followed the procedure in [16]. All experimentswere performed on the TIMIT corpus [19]. We used the train-dev-testsplit from the Kaldi [20] TIMIT s5 recipe. We trained on thestandard 462 speaker set with all SA utterances removed and used the 50 speakerdev set for early stopping. We tested on the 24 speaker core test set. Allnetworks were trained on 40 mel-scale filter-bank features together with theenergy in each frame, and first and second temporal differences, yielding intotal 123 features per frame. Each feature was rescaled to have zero mean andunit variance over the training set. Networks were trained on the full 61-phoneset extended with an extra “end-of-sequence” token that was appended to eachtarget sequence. Similarly, we appended an all-zero frame at the end of eachinput sequence to indicate the end of the utterance. Decoding was performedusing the 61+1 phoneme set, while scoring was done on the 39 phoneme set.

Question: Why did the authors use a different set of phonemes for decoding and scoring?
There is no evidential information about using a different set of phonemes for decoding and scoring, this question cannot be answered in this paper. However, since the authors follow the settings from existing works so this could be found in those references.