aishell example

游雁

2024-02-19 6a9c21a40882dc59676dc882954b290e0a867960

aishell example

 examples/aishell/paraformer/conf/train_asr_paraformer_conformer_12e_6d_2048_256.yaml

 examples/aishell/paraformer/run.sh

@@ -1,6 +1,6 @@
#!/usr/bin/env bash

. ./path.sh || exit 1;
workspace=`pwd`

# machines configuration
CUDA_VISIBLE_DEVICES="0,1"
@@ -39,7 +39,7 @@
valid_set=dev
test_sets="dev test"

asr_config=conf/train_asr_paraformer_conformer_12e_6d_2048_256.yaml
asr_config=train_asr_paraformer_conformer_12e_6d_2048_256.yaml
model_dir="baseline_$(basename "${asr_config}" .yaml)_${lang}_${token_type}_${tag}"

#inference_config=conf/decode_asr_transformer_noctc_1best.yaml
@@ -74,19 +74,21 @@
        utils/text2token.py -n 1 -s 1 ${feats_dir}/data/${x}/text > ${feats_dir}/data/${x}/text.org
        mv ${feats_dir}/data/${x}/text.org ${feats_dir}/data/${x}/text

        python funasr/datasets/audio_datasets/scp2jsonl.py \
        ++scp_file_list='["${feats_dir}/data/${x}/wav.scp", "${feats_dir}/data/${x}/text"]' \
        # convert wav.scp text to jsonl
        scp_file_list_arg="++scp_file_list='[\"${feats_dir}/data/${x}/wav.scp\",\"${feats_dir}/data/${x}/text\"]'"
        python ../../../funasr/datasets/audio_datasets/scp2jsonl.py \
        ++data_type_list='["source", "target"]' \
        ++jsonl_file_out=${feats_dir}/data/${x}/audio_datasets.jsonl
        ++jsonl_file_out=${feats_dir}/data/${x}/audio_datasets.jsonl \
        ${scp_file_list_arg}
    done
fi

if [ ${stage} -le 1 ] && [ ${stop_stage} -ge 1 ]; then
    echo "stage 1: Feature and CMVN Generation"
#    utils/compute_cmvn.sh --fbankdir ${feats_dir}/data/${train_set} --cmd "$train_cmd" --nj $nj --feats_dim ${feats_dim} --config_file "$asr_config" --scale 1.0
    python funasr/bin/compute_audio_cmvn.py \
    --config-path "/Users/zhifu/funasr1.0/examples/aishell/conf" \
    --config-name "train_asr_paraformer_conformer_12e_6d_2048_256.yaml" \
    python ../../../funasr/bin/compute_audio_cmvn.py \
    --config-path "${workspace}" \
    --config-name "${asr_config}" \
    ++train_data_set_list="${feats_dir}/data/${train_set}/audio_datasets.jsonl" \
    ++cmvn_file="${feats_dir}/data/${train_set}/cmvn.json" \
    ++dataset_conf.num_workers=$nj
@@ -119,9 +121,9 @@
torchrun \
--nnodes 1 \
--nproc_per_node ${gpu_num} \
funasr/bin/train.py \
--config-path "/Users/zhifu/funasr1.0/examples/aishell/conf" \
--config-name "train_asr_paraformer_conformer_12e_6d_2048_256.yaml" \
  ../../../funasr/bin/train.py \
  --config-path "${workspace}" \
  --config-name "${asr_config}" \
++train_data_set_list="${feats_dir}/data/${train_set}/audio_datasets.jsonl" \
++cmvn_file="${feats_dir}/data/${train_set}/am.mvn" \
++token_list="${token_list}" \

 examples/industrial_data_pretraining/paraformer/finetune.sh

@@ -6,10 +6,12 @@
#git clone https://www.modelscope.cn/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch.git ${local_path}

## generate jsonl from wav.scp and text.txt
#python funasr/datasets/audio_datasets/scp2jsonl.py \
#++scp_file_list='["/Users/zhifu/funasr1.0/test_local/wav.scp", "/Users/zhifu/funasr1.0/test_local/text.txt"]' \
#++data_type_list='["source", "target"]' \
#++jsonl_file_out=/Users/zhifu/funasr1.0/test_local/audio_datasets.jsonl
python funasr/datasets/audio_datasets/scp2jsonl.py \
++scp_file_list='["/Users/zhifu/funasr1.0/test_local/wav.scp", "/Users/zhifu/funasr1.0/test_local/text.txt"]' \
++data_type_list='["source", "target"]' \
++jsonl_file_out=/Users/zhifu/funasr1.0/test_local/audio_datasets.jsonl


# torchrun \
# --nnodes 1 \
# --nproc_per_node 1 \

 funasr/auto/auto_frontend.py

@@ -19,7 +19,6 @@
from funasr.utils.load_utils import load_audio_text_image_video, extract_fbank
from funasr.utils.timestamp_tools import timestamp_sentence
from funasr.models.campplus.utils import sv_chunk, postprocess, distribute_spk
from funasr.models.campplus.cluster_backend import ClusterBackend
from funasr.auto.auto_model import prepare_data_iterator



 funasr/auto/auto_model.py

@@ -20,7 +20,10 @@
from funasr.utils.load_utils import load_audio_text_image_video, extract_fbank
from funasr.utils.timestamp_tools import timestamp_sentence
from funasr.models.campplus.utils import sv_chunk, postprocess, distribute_spk
try:
from funasr.models.campplus.cluster_backend import ClusterBackend
except:
    print("If you want to use the speaker diarization, please `pip install hdbscan`")


def prepare_data_iterator(data_in, input_len=None, data_type=None, key=None):

 funasr/datasets/audio_datasets/scp2jsonl.py

@@ -19,7 +19,7 @@
        world_size = 1

    cpu_cores = os.cpu_count() or 1
    
    print(f"convert wav.scp text to jsonl, ncpu: {cpu_cores}")
    if rank == 0:
        json_dict = {}
        for data_type, data_file in zip(data_type_list, path):
@@ -65,7 +65,7 @@
            sample_num = len(waveform)
            context_len = int(sample_num//16000*1000/10)
        else:
            context_len = len(line)
            context_len = len(line.split()) if " " in line else len(line)
        res[key] = {data_type: line, f"{data_type}_len": context_len}
    return res
    
@@ -83,6 +83,8 @@
    kwargs = OmegaConf.to_container(cfg, resolve=True)

    scp_file_list = kwargs.get("scp_file_list", ("/Users/zhifu/funasr1.0/test_local/wav.scp", "/Users/zhifu/funasr1.0/test_local/text.txt"))
    if isinstance(scp_file_list, str):
        scp_file_list = eval(scp_file_list)
    data_type_list = kwargs.get("data_type_list", ("source", "target"))
    jsonl_file_out = kwargs.get("jsonl_file_out", "/Users/zhifu/funasr1.0/test_local/audio_datasets.jsonl")
    gen_jsonl_from_wav_text_list(scp_file_list, data_type_list=data_type_list, jsonl_file_out=jsonl_file_out)

 setup.py

@@ -37,7 +37,6 @@
        # "textgrid",
        # "protobuf",
        "tqdm",
        "hdbscan",
        "umap_learn",
        "jaconv",
        "hydra-core>=1.3.2",