speech_recognition/FunASR
1
0
Fork 0
mirror of https://github.com/modelscope/FunASR synced 2025-09-15 14:48:36 +08:00
Code Issues Actions Packages Projects Releases Wiki Activity

update repo

Browse Source
This commit is contained in:
嘉渊 2023-05-16 16:18:35 +08:00
parent 611ac5ea64
commit 90d8e42e9e
8 changed files with 64 additions and 40 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

22
egs/aishell2/conformer/run.sh
View File

@ -21,16 +21,16 @@ type=sound
scp=wav.scp
speed_perturb="0.9 1.0 1.1"
dataset_type=large
stage=3
stop_stage=4
stage=0
stop_stage=5
# feature configuration
feats_dim=80
nj=64
# data
tr_dir=/nfs/wangjiaming.wjm/asr_data/aishell2/AISHELL-2/iOS/data
dev_tst_dir=/nfs/wangjiaming.wjm/asr_data/aishell2/AISHELL-DEV-TEST-SET
tr_dir=
dev_tst_dir=
# exp tag
tag="exp1"
@ -107,10 +107,16 @@ if [ ${stage} -le 2 ] && [ ${stop_stage} -ge 2 ]; then
mkdir -p ${feats_dir}/asr_stats_fbank_zh_char/${valid_set}
fi
# Training Stage
# LM Training Stage
world_size=$gpu_num # run on one machine
if [ ${stage} -le 3 ] && [ ${stop_stage} -ge 3 ]; then
echo "stage 3: Training"
echo "stage 3: LM Training"
fi
# ASR Training Stage
world_size=$gpu_num # run on one machine
if [ ${stage} -le 4 ] && [ ${stop_stage} -ge 4 ]; then
echo "stage 4: ASR Training"
mkdir -p ${exp_dir}/exp/${model_dir}
mkdir -p ${exp_dir}/exp/${model_dir}/log
INIT_FILE=${exp_dir}/exp/${model_dir}/ddp_init
@ -151,8 +157,8 @@ if [ ${stage} -le 3 ] && [ ${stop_stage} -ge 3 ]; then
fi
# Testing Stage
if [ ${stage} -le 4 ] && [ ${stop_stage} -ge 4 ]; then
echo "stage 4: Inference"
if [ ${stage} -le 5 ] && [ ${stop_stage} -ge 5 ]; then
echo "stage 5: Inference"
for dset in ${test_sets}; do
asr_exp=${exp_dir}/exp/${model_dir}
inference_tag="$(basename "${inference_config}" .yaml)"

4
egs/aishell2/data2vec_pretrain/run.sh
View File

@ -24,8 +24,8 @@ feats_dim=80
nj=64
# data
tr_dir=/nfs/wangjiaming.wjm/asr_data/aishell2/AISHELL-2/iOS/data
dev_tst_dir=/nfs/wangjiaming.wjm/asr_data/aishell2/AISHELL-DEV-TEST-SET
tr_dir=
dev_tst_dir=
# exp tag
tag="exp1"

22
egs/aishell2/paraformer/run.sh
View File

@ -21,16 +21,16 @@ type=sound
scp=wav.scp
speed_perturb="0.9 1.0 1.1"
dataset_type=large
stage=3
stop_stage=4
stage=0
stop_stage=5
# feature configuration
feats_dim=80
nj=64
# data
tr_dir=/nfs/wangjiaming.wjm/asr_data/aishell2/AISHELL-2/iOS/data
dev_tst_dir=/nfs/wangjiaming.wjm/asr_data/aishell2/AISHELL-DEV-TEST-SET
tr_dir=
dev_tst_dir=
# exp tag
tag="exp1"
@ -105,10 +105,16 @@ if [ ${stage} -le 2 ] && [ ${stop_stage} -ge 2 ]; then
echo "<unk>" >> ${token_list}
fi
# Training Stage
# LM Training Stage
world_size=$gpu_num # run on one machine
if [ ${stage} -le 3 ] && [ ${stop_stage} -ge 3 ]; then
echo "stage 3: Training"
echo "stage 3: LM Training"
fi
# ASR Training Stage
world_size=$gpu_num # run on one machine
if [ ${stage} -le 4 ] && [ ${stop_stage} -ge 4 ]; then
echo "stage 4: ASR Training"
mkdir -p ${exp_dir}/exp/${model_dir}
mkdir -p ${exp_dir}/exp/${model_dir}/log
INIT_FILE=${exp_dir}/exp/${model_dir}/ddp_init
@ -149,8 +155,8 @@ if [ ${stage} -le 3 ] && [ ${stop_stage} -ge 3 ]; then
fi
# Testing Stage
if [ ${stage} -le 4 ] && [ ${stop_stage} -ge 4 ]; then
echo "stage 4: Inference"
if [ ${stage} -le 5 ] && [ ${stop_stage} -ge 5 ]; then
echo "stage 5: Inference"
for dset in ${test_sets}; do
asr_exp=${exp_dir}/exp/${model_dir}
inference_tag="$(basename "${inference_config}" .yaml)"

22
egs/aishell2/paraformerbert/run.sh
View File

@ -21,8 +21,8 @@ type=sound
scp=wav.scp
speed_perturb="0.9 1.0 1.1"
dataset_type=large
stage=3
stop_stage=4
stage=0
stop_stage=5
skip_extract_embed=false
bert_model_name="bert-base-chinese"
@ -32,8 +32,8 @@ feats_dim=80
nj=64
# data
tr_dir=/nfs/wangjiaming.wjm/asr_data/aishell2/AISHELL-2/iOS/data
dev_tst_dir=/nfs/wangjiaming.wjm/asr_data/aishell2/AISHELL-DEV-TEST-SET
tr_dir=
dev_tst_dir=
# exp tag
tag="exp1"
@ -108,10 +108,16 @@ if [ ${stage} -le 2 ] && [ ${stop_stage} -ge 2 ]; then
echo "<unk>" >> ${token_list}
fi
# Training Stage
# LM Training Stage
world_size=$gpu_num # run on one machine
if [ ${stage} -le 3 ] && [ ${stop_stage} -ge 3 ]; then
echo "stage 3: Training"
echo "stage 3: LM Training"
fi
# ASR Training Stage
world_size=$gpu_num # run on one machine
if [ ${stage} -le 4 ] && [ ${stop_stage} -ge 4 ]; then
echo "stage 4: ASR Training"
if ! "${skip_extract_embed}"; then
echo "extract embeddings..."
local/extract_embeds.sh \
@ -160,8 +166,8 @@ if [ ${stage} -le 3 ] && [ ${stop_stage} -ge 3 ]; then
fi
# Testing Stage
if [ ${stage} -le 4 ] && [ ${stop_stage} -ge 4 ]; then
echo "stage 4: Inference"
if [ ${stage} -le 5 ] && [ ${stop_stage} -ge 5 ]; then
echo "stage 5: Inference"
for dset in ${test_sets}; do
asr_exp=${exp_dir}/exp/${model_dir}
inference_tag="$(basename "${inference_config}" .yaml)"

22
egs/aishell2/transformer/run.sh
View File

@ -21,16 +21,16 @@ type=sound
scp=wav.scp
speed_perturb="0.9 1.0 1.1"
dataset_type=large
stage=3
stop_stage=4
stage=0
stop_stage=5
# feature configuration
feats_dim=80
nj=64
# data
tr_dir=/nfs/wangjiaming.wjm/asr_data/aishell2/AISHELL-2/iOS/data
dev_tst_dir=/nfs/wangjiaming.wjm/asr_data/aishell2/AISHELL-DEV-TEST-SET
tr_dir=
dev_tst_dir=
# exp tag
tag="exp1"
@ -105,10 +105,16 @@ if [ ${stage} -le 2 ] && [ ${stop_stage} -ge 2 ]; then
echo "<unk>" >> ${token_list}
fi
# Training Stage
# LM Training Stage
world_size=$gpu_num # run on one machine
if [ ${stage} -le 3 ] && [ ${stop_stage} -ge 3 ]; then
echo "stage 3: Training"
echo "stage 3: LM Training"
fi
# ASR Training Stage
world_size=$gpu_num # run on one machine
if [ ${stage} -le 4 ] && [ ${stop_stage} -ge 4 ]; then
echo "stage 4: ASR Training"
mkdir -p ${exp_dir}/exp/${model_dir}
mkdir -p ${exp_dir}/exp/${model_dir}/log
INIT_FILE=${exp_dir}/exp/${model_dir}/ddp_init
@ -149,8 +155,8 @@ if [ ${stage} -le 3 ] && [ ${stop_stage} -ge 3 ]; then
fi
# Testing Stage
if [ ${stage} -le 4 ] && [ ${stop_stage} -ge 4 ]; then
echo "stage 4: Inference"
if [ ${stage} -le 5 ] && [ ${stop_stage} -ge 5 ]; then
echo "stage 5 Inference"
for dset in ${test_sets}; do
asr_exp=${exp_dir}/exp/${model_dir}
inference_tag="$(basename "${inference_config}" .yaml)"

4
funasr/models/e2e_asr_transducer.py
View File

@ -17,7 +17,7 @@ from funasr.models.joint_net.joint_network import JointNetwork
from funasr.modules.nets_utils import get_transducer_task_io
from funasr.layers.abs_normalize import AbsNormalize
from funasr.torch_utils.device_funcs import force_gatherable
from funasr.train.abs_espnet_model import AbsESPnetModel
from funasr.models.base_model import FunASRModel
if V(torch.__version__) >= V("1.6.0"):
from torch.cuda.amp import autocast
@ -28,7 +28,7 @@ else:
yield
class TransducerModel(AbsESPnetModel):
class TransducerModel(FunASRModel):
"""ESPnet2ASRTransducerModel module definition.
Args:

4
funasr/models/e2e_sa_asr.py
View File

@ -29,7 +29,7 @@ from funasr.modules.add_sos_eos import add_sos_eos
from funasr.modules.e2e_asr_common import ErrorCalculator
from funasr.modules.nets_utils import th_accuracy
from funasr.torch_utils.device_funcs import force_gatherable
from funasr.train.abs_espnet_model import AbsESPnetModel
from funasr.models.base_model import FunASRModel
if LooseVersion(torch.__version__) >= LooseVersion("1.6.0"):
from torch.cuda.amp import autocast
@ -40,7 +40,7 @@ else:
yield
class ESPnetASRModel(AbsESPnetModel):
class ESPnetASRModel(FunASRModel):
"""CTC-attention hybrid Encoder-Decoder model"""
def __init__(

4
funasr/tasks/sa_asr.py
View File

@ -70,11 +70,11 @@ from funasr.models.preencoder.sinc import LightweightSincConvs
from funasr.models.specaug.abs_specaug import AbsSpecAug
from funasr.models.specaug.specaug import SpecAug
from funasr.models.specaug.specaug import SpecAugLFR
from funasr.models.base_model import FunASRModel
from funasr.modules.subsampling import Conv1dSubsampling
from funasr.tasks.abs_task import AbsTask
from funasr.text.phoneme_tokenizer import g2p_choices
from funasr.torch_utils.initialize import initialize
from funasr.train.abs_espnet_model import AbsESPnetModel
from funasr.train.class_choices import ClassChoices
from funasr.train.trainer import Trainer
from funasr.utils.get_default_kwargs import get_default_kwargs
@ -129,7 +129,7 @@ model_choices = ClassChoices(
mfcca=MFCCA,
timestamp_prediction=TimestampPredictor,
),
type_check=AbsESPnetModel,
type_check=FunASRModel,
default="asr",
)
preencoder_choices = ClassChoices(