From 2c167ecef3421f1f5e876fd7c158f57faa1abceb Mon Sep 17 00:00:00 2001
From: speech_asr <wangjiaming.wjm@alibaba-inc.com>
Date: 星期四, 09 二月 2023 15:12:29 +0800
Subject: [PATCH] Merge branch 'dev' of https://github.com/alibaba-damo-academy/FunASR into dev
---
egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-ko-16k-common-vocab6400-tensorflow1-offline/infer.py | 2
egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-fa-16k-common-vocab1257-pytorch-online/finetune.py | 35 ++++
egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-ru-16k-common-vocab1664-tensorflow1-offline/finetune.py | 2
funasr/bin/vad_inference_launch.py | 149 ++++++++++++++++++
egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-fa-16k-common-vocab1257-pytorch-offline/finetune.py | 35 ++++
egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-fr-16k-common-vocab3472-tensorflow1-online/finetune.py | 35 ++++
egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-ko-16k-common-vocab6400-tensorflow1-offline/finetune.py | 2
egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-fr-16k-common-vocab3472-tensorflow1-offline/finetune.py | 35 ++++
egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-de-16k-common-vocab3690-tensorflow1-offline/infer.py | 13 +
egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-en-16k-common-vocab1080-tensorflow1-offline/finetune.py | 2
egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-de-16k-common-vocab3690-tensorflow1-online/infer.py | 13 +
egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-fr-16k-common-vocab3472-tensorflow1-online/infer.py | 13 +
egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-de-16k-common-vocab3690-tensorflow1-offline/finetune.py | 35 ++++
egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-de-16k-common-vocab3690-tensorflow1-online/finetune.py | 35 ++++
egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-fa-16k-common-vocab1257-pytorch-offline/infer.py | 13 +
egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-fr-16k-common-vocab3472-tensorflow1-offline/infer.py | 13 +
egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-es-16k-common-vocab3445-tensorflow1-offline/infer.py | 2
egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-fa-16k-common-vocab1257-pytorch-online/infer.py | 13 +
egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-ru-16k-common-vocab1664-tensorflow1-offline/infer.py | 2
egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-es-16k-common-vocab3445-tensorflow1-offline/finetune.py | 2
egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-en-16k-common-vocab1080-tensorflow1-offline/infer.py | 2
21 files changed, 445 insertions(+), 8 deletions(-)
diff --git a/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-de-16k-common-vocab3690-tensorflow1-offline/finetune.py b/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-de-16k-common-vocab3690-tensorflow1-offline/finetune.py
new file mode 100644
index 0000000..68d7ba8
--- /dev/null
+++ b/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-de-16k-common-vocab3690-tensorflow1-offline/finetune.py
@@ -0,0 +1,35 @@
+import os
+from modelscope.metainfo import Trainers
+from modelscope.trainers import build_trainer
+from funasr.datasets.ms_dataset import MsDataset
+
+
+def modelscope_finetune(params):
+ if not os.path.exists(params["output_dir"]):
+ os.makedirs(params["output_dir"], exist_ok=True)
+ # dataset split ["train", "validation"]
+ ds_dict = MsDataset.load(params["data_dir"])
+ kwargs = dict(
+ model=params["model"],
+ model_revision=params["model_revision"],
+ data_dir=ds_dict,
+ dataset_type=params["dataset_type"],
+ work_dir=params["output_dir"],
+ batch_bins=params["batch_bins"],
+ max_epoch=params["max_epoch"],
+ lr=params["lr"])
+ trainer = build_trainer(Trainers.speech_asr_trainer, default_args=kwargs)
+ trainer.train()
+
+
+if __name__ == '__main__':
+ params = {}
+ params["output_dir"] = "./checkpoint"
+ params["data_dir"] = "./data"
+ params["batch_bins"] = 2000
+ params["dataset_type"] = "small"
+ params["max_epoch"] = 50
+ params["lr"] = 0.00005
+ params["model"] = "damo/speech_UniASR_asr_2pass-de-16k-common-vocab3690-tensorflow1-offline"
+ params["model_revision"] = None
+ modelscope_finetune(params)
diff --git a/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-de-16k-common-vocab3690-tensorflow1-offline/infer.py b/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-de-16k-common-vocab3690-tensorflow1-offline/infer.py
new file mode 100644
index 0000000..d23c7f4
--- /dev/null
+++ b/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-de-16k-common-vocab3690-tensorflow1-offline/infer.py
@@ -0,0 +1,13 @@
+from modelscope.pipelines import pipeline
+from modelscope.utils.constant import Tasks
+
+if __name__ == "__main__":
+ audio_in = "https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/asr_example_de.wav"
+ output_dir = "./results"
+ inference_pipline = pipeline(
+ task=Tasks.auto_speech_recognition,
+ model="damo/speech_UniASR_asr_2pass-de-16k-common-vocab3690-tensorflow1-offline",
+ output_dir=output_dir,
+ )
+ rec_result = inference_pipline(audio_in=audio_in)
+ print(rec_result)
diff --git a/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-de-16k-common-vocab3690-tensorflow1-online/finetune.py b/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-de-16k-common-vocab3690-tensorflow1-online/finetune.py
new file mode 100644
index 0000000..462f266
--- /dev/null
+++ b/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-de-16k-common-vocab3690-tensorflow1-online/finetune.py
@@ -0,0 +1,35 @@
+import os
+from modelscope.metainfo import Trainers
+from modelscope.trainers import build_trainer
+from funasr.datasets.ms_dataset import MsDataset
+
+
+def modelscope_finetune(params):
+ if not os.path.exists(params["output_dir"]):
+ os.makedirs(params["output_dir"], exist_ok=True)
+ # dataset split ["train", "validation"]
+ ds_dict = MsDataset.load(params["data_dir"])
+ kwargs = dict(
+ model=params["model"],
+ model_revision=params["model_revision"],
+ data_dir=ds_dict,
+ dataset_type=params["dataset_type"],
+ work_dir=params["output_dir"],
+ batch_bins=params["batch_bins"],
+ max_epoch=params["max_epoch"],
+ lr=params["lr"])
+ trainer = build_trainer(Trainers.speech_asr_trainer, default_args=kwargs)
+ trainer.train()
+
+
+if __name__ == '__main__':
+ params = {}
+ params["output_dir"] = "./checkpoint"
+ params["data_dir"] = "./data"
+ params["batch_bins"] = 2000
+ params["dataset_type"] = "small"
+ params["max_epoch"] = 50
+ params["lr"] = 0.00005
+ params["model"] = "damo/speech_UniASR_asr_2pass-de-16k-common-vocab3690-tensorflow1-online"
+ params["model_revision"] = None
+ modelscope_finetune(params)
diff --git a/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-de-16k-common-vocab3690-tensorflow1-online/infer.py b/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-de-16k-common-vocab3690-tensorflow1-online/infer.py
new file mode 100644
index 0000000..d7840c2
--- /dev/null
+++ b/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-de-16k-common-vocab3690-tensorflow1-online/infer.py
@@ -0,0 +1,13 @@
+from modelscope.pipelines import pipeline
+from modelscope.utils.constant import Tasks
+
+if __name__ == "__main__":
+ audio_in = "https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/asr_example_de.wav"
+ output_dir = "./results"
+ inference_pipline = pipeline(
+ task=Tasks.auto_speech_recognition,
+ model="damo/speech_UniASR_asr_2pass-de-16k-common-vocab3690-tensorflow1-online",
+ output_dir=output_dir,
+ )
+ rec_result = inference_pipline(audio_in=audio_in)
+ print(rec_result)
diff --git a/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-en-16k-common-vocab1080-tensorflow1-offline/finetune.py b/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-en-16k-common-vocab1080-tensorflow1-offline/finetune.py
index 6998f0c..397b7ff 100644
--- a/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-en-16k-common-vocab1080-tensorflow1-offline/finetune.py
+++ b/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-en-16k-common-vocab1080-tensorflow1-offline/finetune.py
@@ -30,6 +30,6 @@
params["dataset_type"] = "small"
params["max_epoch"] = 50
params["lr"] = 0.00005
- params["model"] = "damo/speech_UniASR_asr_2pass-en-16k-common-vocab1080-tensorflow1-online"
+ params["model"] = "damo/speech_UniASR_asr_2pass-en-16k-common-vocab1080-tensorflow1-offline"
params["model_revision"] = None
modelscope_finetune(params)
diff --git a/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-en-16k-common-vocab1080-tensorflow1-offline/infer.py b/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-en-16k-common-vocab1080-tensorflow1-offline/infer.py
index 201f794..0cfe939 100644
--- a/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-en-16k-common-vocab1080-tensorflow1-offline/infer.py
+++ b/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-en-16k-common-vocab1080-tensorflow1-offline/infer.py
@@ -6,7 +6,7 @@
output_dir = "./results"
inference_pipline = pipeline(
task=Tasks.auto_speech_recognition,
- model="damo/speech_UniASR_asr_2pass-en-16k-common-vocab1080-tensorflow1-online",
+ model="damo/speech_UniASR_asr_2pass-en-16k-common-vocab1080-tensorflow1-offline",
output_dir=output_dir,
)
rec_result = inference_pipline(audio_in=audio_in)
diff --git a/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-es-16k-common-vocab3445-tensorflow1-offline/finetune.py b/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-es-16k-common-vocab3445-tensorflow1-offline/finetune.py
index 79ef4b6..3846ff6 100644
--- a/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-es-16k-common-vocab3445-tensorflow1-offline/finetune.py
+++ b/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-es-16k-common-vocab3445-tensorflow1-offline/finetune.py
@@ -30,6 +30,6 @@
params["dataset_type"] = "small"
params["max_epoch"] = 50
params["lr"] = 0.00005
- params["model"] = "damo/speech_UniASR_asr_2pass-es-16k-common-vocab3445-tensorflow1-online"
+ params["model"] = "damo/speech_UniASR_asr_2pass-es-16k-common-vocab3445-tensorflow1-offline"
params["model_revision"] = None
modelscope_finetune(params)
diff --git a/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-es-16k-common-vocab3445-tensorflow1-offline/infer.py b/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-es-16k-common-vocab3445-tensorflow1-offline/infer.py
index cfd9e9d..6c416b2 100644
--- a/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-es-16k-common-vocab3445-tensorflow1-offline/infer.py
+++ b/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-es-16k-common-vocab3445-tensorflow1-offline/infer.py
@@ -6,7 +6,7 @@
output_dir = "./results"
inference_pipline = pipeline(
task=Tasks.auto_speech_recognition,
- model="damo/speech_UniASR_asr_2pass-es-16k-common-vocab3445-tensorflow1-online",
+ model="damo/speech_UniASR_asr_2pass-es-16k-common-vocab3445-tensorflow1-offline",
output_dir=output_dir,
)
rec_result = inference_pipline(audio_in=audio_in)
diff --git a/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-fa-16k-common-vocab1257-pytorch-offline/finetune.py b/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-fa-16k-common-vocab1257-pytorch-offline/finetune.py
new file mode 100644
index 0000000..1aef9c6
--- /dev/null
+++ b/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-fa-16k-common-vocab1257-pytorch-offline/finetune.py
@@ -0,0 +1,35 @@
+import os
+from modelscope.metainfo import Trainers
+from modelscope.trainers import build_trainer
+from funasr.datasets.ms_dataset import MsDataset
+
+
+def modelscope_finetune(params):
+ if not os.path.exists(params["output_dir"]):
+ os.makedirs(params["output_dir"], exist_ok=True)
+ # dataset split ["train", "validation"]
+ ds_dict = MsDataset.load(params["data_dir"])
+ kwargs = dict(
+ model=params["model"],
+ model_revision=params["model_revision"],
+ data_dir=ds_dict,
+ dataset_type=params["dataset_type"],
+ work_dir=params["output_dir"],
+ batch_bins=params["batch_bins"],
+ max_epoch=params["max_epoch"],
+ lr=params["lr"])
+ trainer = build_trainer(Trainers.speech_asr_trainer, default_args=kwargs)
+ trainer.train()
+
+
+if __name__ == '__main__':
+ params = {}
+ params["output_dir"] = "./checkpoint"
+ params["data_dir"] = "./data"
+ params["batch_bins"] = 2000
+ params["dataset_type"] = "small"
+ params["max_epoch"] = 50
+ params["lr"] = 0.00005
+ params["model"] = "damo/speech_UniASR_asr_2pass-fa-16k-common-vocab1257-pytorch-offline"
+ params["model_revision"] = None
+ modelscope_finetune(params)
diff --git a/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-fa-16k-common-vocab1257-pytorch-offline/infer.py b/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-fa-16k-common-vocab1257-pytorch-offline/infer.py
new file mode 100644
index 0000000..85ddeee
--- /dev/null
+++ b/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-fa-16k-common-vocab1257-pytorch-offline/infer.py
@@ -0,0 +1,13 @@
+from modelscope.pipelines import pipeline
+from modelscope.utils.constant import Tasks
+
+if __name__ == "__main__":
+ audio_in = "https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/asr_example_fa.wav"
+ output_dir = "./results"
+ inference_pipline = pipeline(
+ task=Tasks.auto_speech_recognition,
+ model="damo/speech_UniASR_asr_2pass-fa-16k-common-vocab1257-pytorch-offline",
+ output_dir=output_dir,
+ )
+ rec_result = inference_pipline(audio_in=audio_in)
+ print(rec_result)
diff --git a/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-fa-16k-common-vocab1257-pytorch-online/finetune.py b/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-fa-16k-common-vocab1257-pytorch-online/finetune.py
new file mode 100644
index 0000000..3bdf1cc
--- /dev/null
+++ b/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-fa-16k-common-vocab1257-pytorch-online/finetune.py
@@ -0,0 +1,35 @@
+import os
+from modelscope.metainfo import Trainers
+from modelscope.trainers import build_trainer
+from funasr.datasets.ms_dataset import MsDataset
+
+
+def modelscope_finetune(params):
+ if not os.path.exists(params["output_dir"]):
+ os.makedirs(params["output_dir"], exist_ok=True)
+ # dataset split ["train", "validation"]
+ ds_dict = MsDataset.load(params["data_dir"])
+ kwargs = dict(
+ model=params["model"],
+ model_revision=params["model_revision"],
+ data_dir=ds_dict,
+ dataset_type=params["dataset_type"],
+ work_dir=params["output_dir"],
+ batch_bins=params["batch_bins"],
+ max_epoch=params["max_epoch"],
+ lr=params["lr"])
+ trainer = build_trainer(Trainers.speech_asr_trainer, default_args=kwargs)
+ trainer.train()
+
+
+if __name__ == '__main__':
+ params = {}
+ params["output_dir"] = "./checkpoint"
+ params["data_dir"] = "./data"
+ params["batch_bins"] = 2000
+ params["dataset_type"] = "small"
+ params["max_epoch"] = 50
+ params["lr"] = 0.00005
+ params["model"] = "damo/speech_UniASR_asr_2pass-fa-16k-common-vocab1257-pytorch-online"
+ params["model_revision"] = None
+ modelscope_finetune(params)
diff --git a/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-fa-16k-common-vocab1257-pytorch-online/infer.py b/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-fa-16k-common-vocab1257-pytorch-online/infer.py
new file mode 100644
index 0000000..960c393
--- /dev/null
+++ b/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-fa-16k-common-vocab1257-pytorch-online/infer.py
@@ -0,0 +1,13 @@
+from modelscope.pipelines import pipeline
+from modelscope.utils.constant import Tasks
+
+if __name__ == "__main__":
+ audio_in = "https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/asr_example_fa.wav"
+ output_dir = "./results"
+ inference_pipline = pipeline(
+ task=Tasks.auto_speech_recognition,
+ model="damo/speech_UniASR_asr_2pass-fa-16k-common-vocab1257-pytorch-online",
+ output_dir=output_dir,
+ )
+ rec_result = inference_pipline(audio_in=audio_in)
+ print(rec_result)
diff --git a/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-fr-16k-common-vocab3472-tensorflow1-offline/finetune.py b/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-fr-16k-common-vocab3472-tensorflow1-offline/finetune.py
new file mode 100644
index 0000000..4746cc2
--- /dev/null
+++ b/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-fr-16k-common-vocab3472-tensorflow1-offline/finetune.py
@@ -0,0 +1,35 @@
+import os
+from modelscope.metainfo import Trainers
+from modelscope.trainers import build_trainer
+from funasr.datasets.ms_dataset import MsDataset
+
+
+def modelscope_finetune(params):
+ if not os.path.exists(params["output_dir"]):
+ os.makedirs(params["output_dir"], exist_ok=True)
+ # dataset split ["train", "validation"]
+ ds_dict = MsDataset.load(params["data_dir"])
+ kwargs = dict(
+ model=params["model"],
+ model_revision=params["model_revision"],
+ data_dir=ds_dict,
+ dataset_type=params["dataset_type"],
+ work_dir=params["output_dir"],
+ batch_bins=params["batch_bins"],
+ max_epoch=params["max_epoch"],
+ lr=params["lr"])
+ trainer = build_trainer(Trainers.speech_asr_trainer, default_args=kwargs)
+ trainer.train()
+
+
+if __name__ == '__main__':
+ params = {}
+ params["output_dir"] = "./checkpoint"
+ params["data_dir"] = "./data"
+ params["batch_bins"] = 2000
+ params["dataset_type"] = "small"
+ params["max_epoch"] = 50
+ params["lr"] = 0.00005
+ params["model"] = "damo/speech_UniASR_asr_2pass-fr-16k-common-vocab3472-tensorflow1-offline"
+ params["model_revision"] = None
+ modelscope_finetune(params)
diff --git a/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-fr-16k-common-vocab3472-tensorflow1-offline/infer.py b/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-fr-16k-common-vocab3472-tensorflow1-offline/infer.py
new file mode 100644
index 0000000..e541f27
--- /dev/null
+++ b/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-fr-16k-common-vocab3472-tensorflow1-offline/infer.py
@@ -0,0 +1,13 @@
+from modelscope.pipelines import pipeline
+from modelscope.utils.constant import Tasks
+
+if __name__ == "__main__":
+ audio_in = "https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/asr_example_fr.wav"
+ output_dir = "./results"
+ inference_pipline = pipeline(
+ task=Tasks.auto_speech_recognition,
+ model="damo/speech_UniASR_asr_2pass-fr-16k-common-vocab3472-tensorflow1-offline",
+ output_dir=output_dir,
+ )
+ rec_result = inference_pipline(audio_in=audio_in)
+ print(rec_result)
diff --git a/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-fr-16k-common-vocab3472-tensorflow1-online/finetune.py b/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-fr-16k-common-vocab3472-tensorflow1-online/finetune.py
new file mode 100644
index 0000000..75901db
--- /dev/null
+++ b/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-fr-16k-common-vocab3472-tensorflow1-online/finetune.py
@@ -0,0 +1,35 @@
+import os
+from modelscope.metainfo import Trainers
+from modelscope.trainers import build_trainer
+from funasr.datasets.ms_dataset import MsDataset
+
+
+def modelscope_finetune(params):
+ if not os.path.exists(params["output_dir"]):
+ os.makedirs(params["output_dir"], exist_ok=True)
+ # dataset split ["train", "validation"]
+ ds_dict = MsDataset.load(params["data_dir"])
+ kwargs = dict(
+ model=params["model"],
+ model_revision=params["model_revision"],
+ data_dir=ds_dict,
+ dataset_type=params["dataset_type"],
+ work_dir=params["output_dir"],
+ batch_bins=params["batch_bins"],
+ max_epoch=params["max_epoch"],
+ lr=params["lr"])
+ trainer = build_trainer(Trainers.speech_asr_trainer, default_args=kwargs)
+ trainer.train()
+
+
+if __name__ == '__main__':
+ params = {}
+ params["output_dir"] = "./checkpoint"
+ params["data_dir"] = "./data"
+ params["batch_bins"] = 2000
+ params["dataset_type"] = "small"
+ params["max_epoch"] = 50
+ params["lr"] = 0.00005
+ params["model"] = "damo/speech_UniASR_asr_2pass-fr-16k-common-vocab3472-tensorflow1-online"
+ params["model_revision"] = None
+ modelscope_finetune(params)
diff --git a/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-fr-16k-common-vocab3472-tensorflow1-online/infer.py b/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-fr-16k-common-vocab3472-tensorflow1-online/infer.py
new file mode 100644
index 0000000..f871665
--- /dev/null
+++ b/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-fr-16k-common-vocab3472-tensorflow1-online/infer.py
@@ -0,0 +1,13 @@
+from modelscope.pipelines import pipeline
+from modelscope.utils.constant import Tasks
+
+if __name__ == "__main__":
+ audio_in = "https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/asr_example_fr.wav"
+ output_dir = "./results"
+ inference_pipline = pipeline(
+ task=Tasks.auto_speech_recognition,
+ model="damo/speech_UniASR_asr_2pass-fr-16k-common-vocab3472-tensorflow1-online",
+ output_dir=output_dir,
+ )
+ rec_result = inference_pipline(audio_in=audio_in)
+ print(rec_result)
diff --git a/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-ko-16k-common-vocab6400-tensorflow1-offline/finetune.py b/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-ko-16k-common-vocab6400-tensorflow1-offline/finetune.py
index 249aa28..fd9c442 100644
--- a/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-ko-16k-common-vocab6400-tensorflow1-offline/finetune.py
+++ b/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-ko-16k-common-vocab6400-tensorflow1-offline/finetune.py
@@ -30,6 +30,6 @@
params["dataset_type"] = "small"
params["max_epoch"] = 50
params["lr"] = 0.00005
- params["model"] = "damo/speech_UniASR_asr_2pass-ko-16k-common-vocab6400-tensorflow1-online"
+ params["model"] = "damo/speech_UniASR_asr_2pass-ko-16k-common-vocab6400-tensorflow1-offline"
params["model_revision"] = None
modelscope_finetune(params)
diff --git a/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-ko-16k-common-vocab6400-tensorflow1-offline/infer.py b/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-ko-16k-common-vocab6400-tensorflow1-offline/infer.py
index 5fbfdbb..7aba7ee 100644
--- a/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-ko-16k-common-vocab6400-tensorflow1-offline/infer.py
+++ b/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-ko-16k-common-vocab6400-tensorflow1-offline/infer.py
@@ -6,7 +6,7 @@
output_dir = "./results"
inference_pipline = pipeline(
task=Tasks.auto_speech_recognition,
- model="damo/speech_UniASR_asr_2pass-ko-16k-common-vocab6400-tensorflow1-online",
+ model="damo/speech_UniASR_asr_2pass-ko-16k-common-vocab6400-tensorflow1-offline",
output_dir=output_dir,
)
rec_result = inference_pipline(audio_in=audio_in)
diff --git a/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-ru-16k-common-vocab1664-tensorflow1-offline/finetune.py b/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-ru-16k-common-vocab1664-tensorflow1-offline/finetune.py
index e8d61d9..432266d 100644
--- a/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-ru-16k-common-vocab1664-tensorflow1-offline/finetune.py
+++ b/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-ru-16k-common-vocab1664-tensorflow1-offline/finetune.py
@@ -30,6 +30,6 @@
params["dataset_type"] = "small"
params["max_epoch"] = 50
params["lr"] = 0.00005
- params["model"] = "damo/speech_UniASR_asr_2pass-ru-16k-common-vocab1664-tensorflow1-online"
+ params["model"] = "damo/speech_UniASR_asr_2pass-ru-16k-common-vocab1664-tensorflow1-offline"
params["model_revision"] = None
modelscope_finetune(params)
diff --git a/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-ru-16k-common-vocab1664-tensorflow1-offline/infer.py b/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-ru-16k-common-vocab1664-tensorflow1-offline/infer.py
index 1051b1f..8b96ffb 100644
--- a/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-ru-16k-common-vocab1664-tensorflow1-offline/infer.py
+++ b/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-ru-16k-common-vocab1664-tensorflow1-offline/infer.py
@@ -6,7 +6,7 @@
output_dir = "./results"
inference_pipline = pipeline(
task=Tasks.auto_speech_recognition,
- model="damo/speech_UniASR_asr_2pass-ru-16k-common-vocab1664-tensorflow1-online",
+ model="damo/speech_UniASR_asr_2pass-ru-16k-common-vocab1664-tensorflow1-offline",
output_dir=output_dir,
)
rec_result = inference_pipline(audio_in=audio_in)
diff --git a/funasr/bin/vad_inference_launch.py b/funasr/bin/vad_inference_launch.py
new file mode 100644
index 0000000..54bf319
--- /dev/null
+++ b/funasr/bin/vad_inference_launch.py
@@ -0,0 +1,149 @@
+#!/usr/bin/env python3
+# Copyright ESPnet (https://github.com/espnet/espnet). All Rights Reserved.
+# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
+
+import argparse
+import logging
+import os
+import sys
+from typing import Union, Dict, Any
+
+from funasr.utils import config_argparse
+from funasr.utils.cli_utils import get_commandline_args
+from funasr.utils.types import str2bool
+from funasr.utils.types import str2triple_str
+from funasr.utils.types import str_or_none
+
+
+def get_parser():
+ parser = config_argparse.ArgumentParser(
+ description="VAD Decoding",
+ formatter_class=argparse.ArgumentDefaultsHelpFormatter,
+ )
+
+ # Note(kamo): Use '_' instead of '-' as separator.
+ # '-' is confusing if written in yaml.
+ parser.add_argument(
+ "--log_level",
+ type=lambda x: x.upper(),
+ default="INFO",
+ choices=("CRITICAL", "ERROR", "WARNING", "INFO", "DEBUG", "NOTSET"),
+ help="The verbose level of logging",
+ )
+
+ parser.add_argument("--output_dir", type=str, required=True)
+ parser.add_argument(
+ "--ngpu",
+ type=int,
+ default=0,
+ help="The number of gpus. 0 indicates CPU mode",
+ )
+ parser.add_argument(
+ "--njob",
+ type=int,
+ default=1,
+ help="The number of jobs for each gpu",
+ )
+ parser.add_argument(
+ "--gpuid_list",
+ type=str,
+ default="",
+ help="The visible gpus",
+ )
+ parser.add_argument("--seed", type=int, default=0, help="Random seed")
+ parser.add_argument(
+ "--dtype",
+ default="float32",
+ choices=["float16", "float32", "float64"],
+ help="Data type",
+ )
+ parser.add_argument(
+ "--num_workers",
+ type=int,
+ default=1,
+ help="The number of workers used for DataLoader",
+ )
+
+ group = parser.add_argument_group("Input data related")
+ group.add_argument(
+ "--data_path_and_name_and_type",
+ type=str2triple_str,
+ required=True,
+ action="append",
+ )
+ group.add_argument("--key_file", type=str_or_none)
+ group.add_argument("--allow_variable_data_keys", type=str2bool, default=False)
+
+ group = parser.add_argument_group("The model configuration related")
+ group.add_argument(
+ "--vad_infer_config",
+ type=str,
+ help="VAD infer configuration",
+ )
+ group.add_argument(
+ "--vad_model_file",
+ type=str,
+ help="VAD model parameter file",
+ )
+ group.add_argument(
+ "--vad_cmvn_file",
+ type=str,
+ help="Global CMVN file",
+ )
+ group.add_argument(
+ "--vad_train_config",
+ type=str,
+ help="VAD training configuration",
+ )
+
+ group = parser.add_argument_group("The inference configuration related")
+ group.add_argument(
+ "--batch_size",
+ type=int,
+ default=1,
+ help="The batch size for inference",
+ )
+ return parser
+
+
+def inference_launch(mode, **kwargs):
+ if mode == "vad":
+ from funasr.bin.vad_inference import inference_modelscope
+ return inference_modelscope(**kwargs)
+ else:
+ logging.info("Unknown decoding mode: {}".format(mode))
+ return None
+
+
+def main(cmd=None):
+ print(get_commandline_args(), file=sys.stderr)
+ parser = get_parser()
+ parser.add_argument(
+ "--mode",
+ type=str,
+ default="vad",
+ help="The decoding mode",
+ )
+ args = parser.parse_args(cmd)
+ kwargs = vars(args)
+ kwargs.pop("config", None)
+
+ # set logging messages
+ logging.basicConfig(
+ level=args.log_level,
+ format="%(asctime)s (%(module)s:%(lineno)d) %(levelname)s: %(message)s",
+ )
+ logging.info("Decoding args: {}".format(kwargs))
+
+ # gpu setting
+ if args.ngpu > 0:
+ jobid = int(args.output_dir.split(".")[-1])
+ gpuid = args.gpuid_list.split(",")[(jobid - 1) // args.njob]
+ os.environ["CUDA_DEVICE_ORDER"] = "PCI_BUS_ID"
+ os.environ["CUDA_VISIBLE_DEVICES"] = gpuid
+
+ inference_launch(**kwargs)
+
+
+if __name__ == "__main__":
+ main()
--
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