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NPU-ASLP

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yufan-aslp 2023-02-16 16:31:33 +08:00
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commit c78474c979
4 changed files with 6 additions and 6 deletions
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2
egs_modelscope/asr/mfcca/speech_mfcca_asr-zh-cn-16k-alimeeting-vocab4950/RESULTS.md
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@ -1,5 +1,5 @@
# Paraformer-Large
- Model link: <https://www.modelscope.cn/models/yufan6/speech_mfcca_asr-zh-cn-16k-alimeeting-vocab4950/summary>
- Model link: <https://www.modelscope.cn/models/NPU-ASLP/speech_mfcca_asr-zh-cn-16k-alimeeting-vocab4950/summary>
- Model size: 45M
# Environments

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egs_modelscope/asr/mfcca/speech_mfcca_asr-zh-cn-16k-alimeeting-vocab4950/finetune.py
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@ -24,12 +24,12 @@ def modelscope_finetune(params):
if __name__ == '__main__':
params = modelscope_args(model="yufan6/speech_mfcca_asr-zh-cn-16k-alimeeting-vocab4950")
params = modelscope_args(model="NPU-ASLP/speech_mfcca_asr-zh-cn-16k-alimeeting-vocab4950")
params.output_dir = "./checkpoint" # m模型保存路径
params.data_path = "./example_data/" # 数据路径
params.dataset_type = "small" # 小数据量设置small，若数据量大于1000小时，请使用large
params.batch_bins = 1000 # batch size，如果dataset_type="small"，batch_bins单位为fbank特征帧数，如果dataset_type="large"，batch_bins单位为毫秒，
params.max_epoch = 10 # 最大训练轮数
params.lr = 0.0001 # 设置学习率
params.model_revision = 'v2.0.0'
params.model_revision = 'v1.0.0'
modelscope_finetune(params)

4
egs_modelscope/asr/mfcca/speech_mfcca_asr-zh-cn-16k-alimeeting-vocab4950/infer.py
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@ -18,8 +18,8 @@ def modelscope_infer_core(output_dir, split_dir, njob, idx):
os.environ['CUDA_VISIBLE_DEVICES'] = str(gpu_id)
inference_pipline = pipeline(
task=Tasks.auto_speech_recognition,
model='yufan6/speech_mfcca_asr-zh-cn-16k-alimeeting-vocab4950',
model_revision='v2.0.0',
model='NPU-ASLP/speech_mfcca_asr-zh-cn-16k-alimeeting-vocab4950',
model_revision='v1.0.0',
output_dir=output_dir_job,
batch_size=1,
)

2
egs_modelscope/asr/mfcca/speech_mfcca_asr-zh-cn-16k-alimeeting-vocab4950/infer_after_finetune.py
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@ -59,7 +59,7 @@ def modelscope_infer_after_finetune(params):
if __name__ == '__main__':
params = {}
params["modelscope_model_name"] = "yufan6/speech_mfcca_asr-zh-cn-16k-alimeeting-vocab4950"
params["modelscope_model_name"] = "NPU-ASLP/speech_mfcca_asr-zh-cn-16k-alimeeting-vocab4950"
params["required_files"] = ["feats_stats.npz", "decoding.yaml", "configuration.json"]
params["output_dir"] = "./checkpoint"
params["data_dir"] = "./example_data/validation"