g2p-seq2seq
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Unexpectedly long outputs
I'm finding repeatedly that the g2p-seq2seq model generates strangely long pronunciations using the included model. For all sequences up to three letters long, the following strange outputs occur:
ysl output: IY EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH
ybr output: IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B
xsn output: EH K S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH
wsq output: D AH B AH L Y UW EH S K Y UW EH S K Y UW EH S K Y UW EH S K Y UW EH S K Y UW EH S K Y UW EH S K Y UW EH S K Y UW EH S K Y UW EH S K Y UW EH S K Y UW EH S K Y UW EH S K Y UW EH S K Y UW EH S K Y UW EH S K Y UW EH S K Y UW EH S K Y UW EH S K Y UW EH S
wsk output: D AH B AH L Y UW EH S K Y UW EH S K Y UW EH S K Y UW EH S K Y UW EH S K Y UW EH S K Y UW EH S K Y UW EH S K EY
wjr output: W JH UW JH AH B AH L Y UW Y UW JH UW JH UW JH UW JH UW JH UW JH UW JH UW JH UW JH UW JH UW JH UW JH UW JH UW JH UW JH UW JH UW JH UW JH UW JH UW JH UW JH UW JH UW JH UW JH UW JH UW JH UW JH UW JH UW JH UW JH UW JH UW JH UW JH UW JH UW JH UW JH UW JH UW JH UW JH UW JH UW JH UW JH UW JH UW JH UW JH UW JH UW
vsl output: V IY EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S
ssc output: EH S EH S S S S S S S S S S S S S S S S S S S S S S IY
qsn output: K Y UW EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH
qrk output: K Y UW EH R K Y UW EH R K Y UW EH R K Y UW EH R K Y T IH K Y UW EH R K Y UW EH R K Y UW EH R K Y UW EH R K Y UW EH R K Y UW EH R K Y UW AA R K Y UW AA R K Y UW AA R K Y UW EH R K Y UW AA R K Y UW EH R K Y UW EH R K Y UW EH R K Y UW EH R K Y UW EH R
nqn output: EH N D IY EH N Y UW EH N Y UW EH N Y UW EH N Y UW EH N Y UW EH N Y UW EH N Y UW EH N Y UW EH N D IY EH N Y UW EH N D IY EH N Y UW EH N Y UW EH N Y UW EH N Y UW EH N Y UW EH N D IY EH N D IY EH N Y UW EH N D IY EH N Y UW EH N Y UW EH N D IY EH N Y UW EH N D IY
lqr output: EH L K Y UW EH L Y UW EH L K Y UW EH L K Y UW EH L K Y UW EH L K Y UW EH L K Y UW EH L K Y UW EH L K Y UW EH L K AA R
But these are all fairly arbitrary. Actual words get such results, too:
uncleanness output: AH N K L IY N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N K L IY S
micrometeorological output: M AY K R OW M IY T AO R AA L AO JH IH K AH L AA L AA L AA L AA L AA L AA L AA L AA L AA L AA L AA L AA L AA L AA L AA L AA L AA L AA L AA L AA L AA L AA L AA L AA L AA JH IH K AH L AA L AA L AA L AA L AA L AA L AA L AA L AA L AA L AA L AH L AA L AA JH IH K AH L AH JH IH K AH L AA L AA L AA L AA L AA L
quadrituberculate output: K W AA D R AH T UW B ER K Y UW B ER K Y UW B ER K Y UW B ER K Y UW B ER K Y UW B ER K Y UW B ER K Y UW AE T
unexceptionableness output: AH N IH K S EH P SH AH N AH B AH L IY N AH L N AH L N AH L N AH L AH L AH L N AH L N AH B AH L AH L AH L AH L AH S
The recurring theme seems to be that for whatever reason these words get stuck in a loop for a long time.
These are pretty rare, but are so egregiously bad that it makes me wonder if there is a bug somewhere? If not, guidance would be appreciated on how to train a model that avoids these issues.
it depends on tensor2tensor version, they break it every month
I am facing a similar issue as well:
> kittipeumpoonwong
S IH T IY P IY AH M P UW N W AO N W AO N W AO N W AO N W AO N W AO N W AO N W AO N W AO N W AO N W AO NG
Is this a model issue or a bug in the decoder code?
I tried using the suggestion that it might be due to the tensor2tensor lib but I am getting the same results for tensor2tensor==1.6.6 and tensor2tensor==1.7.0
@joshhansen I solved this issue by adjusting the beam size of the decoding from 1 to 5.
g2p-seq2seq --decode wordlist.txt --model_dir g2p-seq2seq-model-6.2-cmudict-nostress --return_beams --beam_size 5
ysl IY EH S EH S EH L
ysl IH S AH L
ysl IY EH S EH S EH S EH S EH S EH L
ysl IY EH S EH S EH S EH S EH L
ysl IY EH S EH S EH S EH L
ybr W AY B ER
ybr IH B ER
ybr IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY
ybr IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY
ybr IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY B IY
xsn EH K S EH S EH N
xsn EH K S EH S EH S EH S EH N
xsn EH K S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH N
xsn EH K S EH S EH S EH N
xsn EH K S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH S EH N
wsq D AH B AH L Y UW EH S K Y UW EH S K Y UW
wsq D AH B AH L Y UW EH S K Y UW
wsq D AH B AH L Y UW EH S K Y UW EH S K EY
wsq D AH B AH L Y UW EH S IY
wsq D AH B AH L Y UW EH S K Y UW EH S K
wsk D AH B AH L Y UW EH S K Y UW EH S K EY
wsk D AH B AH Y UW EH S K Y UW EH S K EY
wsk W EH S K
wsk D AH B AH L Y UW EH S K Y UW EH S K Y UW EH S K EY
wsk D AH B AH L Y UW EH S K Y UW EH S K Y UW EH S K Y
wjr W ER
wjr W AA R
wjr W AY R
wjr W JH UW N Y ER
wjr D AH B AH L Y UW JH UW JH IY AA R
lqr EH L K Y UW EH S AA R
lqr EH L K Y UW EH R
lqr EH L K Y UW EH L AA R
lqr EH L K Y UW EH L Y ER
lqr EH L K Y UW EH L Y UW AA R