The label decoded is not the same as the pmap data.

[gccyxy]

@HawkAaron I have met a mistake that the result decoded includes [52,53,54,55,56,57,......],
while the rephone length is just 51. Hence，I met a bug as followes:
the one of y (the result of decoded ) is as followes:
(53, 59, 53, 59, 56, 53, 43, 53, 43, 53, 5, 53, 43, 53, 43, 53, 43, 53, 43, 53, 43, 53, 43, 53, 43, 53, 43, 53, 43, 53, 25, 53, 25, 53, 48, 53, 59, 53, 25, 53, 43, 53, 43, 53, 43, 53, 59, 53, 59, 31, 43, 53, 43, 53, 43, 53, 43, 53, 43, 53, 43, 53, 43, 53, 43, 53, 43, 53, 43, 53, 43, 53, 43, 53, 43, 53, 25, 53, 25, 53, 43, 53, 35, 53, 43, 53, 31, 53, 43, 53, 43, 53, 31, 53, 43, 53, 48, 53, 59, 5, 53, 32, 53, 43, 53, 59, 43, 31, 53, 59, 53, 25, 53, 25, 5, 25, 32, 53, 43, 53, 43, 53, 43, 53, 43, 53, 59, 53, 31, 53, 59, 53, 59)
Traceback (most recent call last):
File "eval.py", line 93, in
decode()
File "eval.py", line 84, in decode
y = [pmap[rephone[i]] for i in y]
File "eval.py", line 84, in
y = [pmap[rephone[i]] for i in y]
KeyError: 53

Why my pmap'(or y) length is not as long as the rephone ? And one of the phoneme such as 'sil' is not included in the pmap dict

[zhoudoufu]

I am enchanting similar error when decoding with the TIMIT data set. I fix this by change the phone mapping part in eval.py.
here is my code

with open('conf/phones.60-48-39.map', 'r') as f:
    pmap = {rephone[1]: rephone[1]}
    for line in f:
        line = line.split()
        if len(line) < 2: pmap[line[0]] = rephone[0]
        else: pmap[line[1]] = line[1]
print(pmap)

[l2009312042]

@zhoudoufu why change from pmap[line[0]] = line[2] to pmap[line[1]] = line[1]?
and pmap = {rephone[1]: rephone[1]} not pmap = {rephone[0]: rephone[0]}

[PeiyanFlying]

So, dear friends,
Why does this happen? I mean what bugs result in this kind of problem?
I meet with the same one , either.

[PeiyanFlying]

@gccyxy
Hello, sir, I meet with the same problem as yours. So do you have some advice?
Many thanks and best.

[melody-rain]

I am enchanting similar error when decoding with the TIMIT data set. I fix this by change the phone mapping part in eval.py.
here is my code

with open('conf/phones.60-48-39.map', 'r') as f:
    pmap = {rephone[1]: rephone[1]}
    for line in f:
        line = line.split()
        if len(line) < 2: pmap[line[0]] = rephone[0]
        else: pmap[line[1]] = line[1]
print(pmap)

I replaced else: pmap[line[0]] = line[2] to else: pmap[line[1]] = line[2] and the final PER for RNN-T is 20.62% with 183 epoches of training.