icefall/egs/mucs/ASR/RESULTS.md

Results for mucs hi-en and bn-en

This page shows the WERs for the code switched test corpus of MUCS hi-en and bn-en.

using conformer ctc

The following results are obtained with run.sh

Specify the language through dataset arg (hi-en or bn-en) LM is trained using kenlm, with the training corpus

Here are the results with different decoding methods

bn-en

	test
ctc decoding	31.72
1best	28.05
nbest	27.92
nbest-rescoring	27.22
whole-lattice-rescoring	27.24
attention-decoder	26.46

hi-en

	test
ctc decoding	31.43
1best	28.48
nbest	28.55
nbest-rescoring	28.23
whole-lattice-rescoring	28.77
attention-decoder	28.16

The training command for reproducing is given below:

cd egs/mucs/ASR/
./prepare.sh

dataset="hi-en" #hi-en or bn-en
bpe=400
datadir=data_"$dataset"
./conformer_ctc/train.py \
    --num-epochs 60 \
    --max-duration 300 \
    --exp-dir ./conformer_ctc/exp_"$dataset"_bpe"$bpe" \
    --manifest-dir $datadir/fbank \
    --lang-dir $datadir/lang_bpe_"$bpe" \
    --enable-musan False \

The decoding command is given below:

dataset="hi-en" #hi-en or bn-en
bpe=400
datadir=data_"$dataset"
num_paths=10
max_duration=10
decode_methods="attention-decoder 1best nbest nbest-rescoring ctc-decoding whole-lattice-rescoring"

for decode_method in $decode_methods; 
do
    ./conformer_ctc/decode.py \
        --epoch 59 \
        --avg 10 \
        --manifest-dir $datadir/fbank \
        --exp-dir ./conformer_ctc/exp_"$dataset"_bpe"$bpe" \
        --max-duration $max_duration \
        --lang-dir $datadir/lang_bpe_"$bpe" \
        --lm-dir $datadir/"lm" \
        --method $decode_method \
        --num-paths $num_paths \
        
done