New English SOFA model trained on data only labelled by myself or hand verified by myself. I was having lots of issues with past models so I decided to do some experiments. I'll be doing more in the future, but I am happy with the results this got, so I'm gonna come back to it at another point. Trained on SOFA v1.0.3
To install, unzip "tgm_en_v100" into the "models" folder in LabelMakr v31. Then to use it, select "tgm_en_v100" from the drop-down in the "Alignments" tab.
Known Issues:
- Sometimes when an
[r]follows a vowel, it doesn't get labelled properly. - Needs more high range/femme voice data.
- Biggest issue is the dictionary. I notice when the phonemes aren't exact, the model struggles to place them, but when they're manually edited in the transcription editor, the placements of phonemes are much more accurate.
Training Data information:
Name | Voice Provider
A. (Unrevealed) | N.
Bitter | Guillotama
Canary | Mina Moonrise
C.B. (Unrevealed) | M.B.
Leif | FerretFather
Luther | imsupposedto
Miyo | ShiWeiMigi
TIGER | tigermeat
TRITON | Ryan M.