update repo

嘉渊

2023-05-10 e422c6197b5bcada0429986500d8d5ca4ffcb3e4

 egs/librispeech_100h/conformer/run.sh

@@ -3,8 +3,8 @@
. ./path.sh || exit 1;

# machines configuration
CUDA_VISIBLE_DEVICES="0,1,2,3,4,5,6,7"
gpu_num=8
CUDA_VISIBLE_DEVICES="0,1"
gpu_num=2
count=1
gpu_inference=true  # Whether to perform gpu decoding, set false for cpu decoding
# for gpu decoding, inference_nj=ngpu*njob; for cpu decoding, inference_nj=njob
@@ -16,30 +16,26 @@
feats_dir="../DATA" #feature output dictionary
exp_dir="."
lang=en
dumpdir=dump/fbank
feats_type=fbank
token_type=bpe
dataset_type=large
scp=feats.scp
type=kaldi_ark
stage=3
stop_stage=4
type=sound
scp=wav.scp
stage=0
stop_stage=0

# feature configuration
feats_dim=80
sample_frequency=16000
nj=100
speed_perturb="0.9,1.0,1.1"
nj=64

# data
data_librispeech=
raw_data=
data_url=www.openslr.org/resources/12

# bpe model
nbpe=5000
bpemode=unigram

# exp tag
tag=""
tag="exp1"

. utils/parse_options.sh || exit 1;

@@ -54,8 +50,7 @@
test_sets="test_clean test_other dev_clean dev_other"

asr_config=conf/train_asr_conformer.yaml
#asr_config=conf/train_asr_conformer_uttnorm.yaml
model_dir="baseline_$(basename "${asr_config}" .yaml)_${feats_type}_${lang}_${token_type}_${tag}"
model_dir="baseline_$(basename "${asr_config}" .yaml)_${lang}_${token_type}_${tag}"

inference_config=conf/decode_asr_transformer.yaml
#inference_config=conf/decode_asr_transformer_beam60_ctc0.3.yaml
@@ -73,11 +68,19 @@
    _ngpu=0
fi


if [ ${stage} -le -1 ] && [ ${stop_stage} -ge -1 ]; then
    echo "stage -1: Data Download"
    for part in dev-clean test-clean dev-other test-other train-clean-100; do
        local/download_and_untar.sh ${raw_data} ${data_url} ${part}
    done
fi

if [ ${stage} -le 0 ] && [ ${stop_stage} -ge 0 ]; then
    echo "stage 0: Data preparation"
    # Data preparation
    for x in train-clean-100 train-clean-360 train-other-500 dev-clean dev-other test-clean test-other; do
        local/data_prep_librispeech.sh ${data_librispeech}/LibriSpeech/${x} ${feats_dir}/data/${x//-/_}
        local/data_prep_librispeech.sh ${raw_data}/LibriSpeech/${x} ${feats_dir}/data/${x//-/_}
    done
fi