Comments (2)
Marvin84
commented on August 11, 2024
The comparison is done under the same exact training conditions for a Conformer diphone factored hybrid HMM, Viterbi trained for 15 epochs on Librispeech 960h, using an alignment of a from-scratch monophone posterior-HMM.
The decoding has been tuned in a fair manner for both results. On dev-other, the models trained with TF 2.3 and TF2.14 have 6.6% and 7.7% WER, respectively. Both decodings use a 4-gram LM.
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Marvin84
commented on August 11, 2024
One thing I should mention, not sure if it is relevant, is that the TF2.3 setup has ran within Ubuntu16 and TF2.14 within Ubuntu22.
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Related Issues (20)
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