Merge pull request #2032 from PaddlePaddle/audio_refactoring

[audio] Audio refactoring

.mergify.yml

@@ -52,7 +52,7 @@ pull_request_rules:
         add: ["T2S"]
   - name: "auto add label=Audio"
     conditions:
-      - files~=^paddleaudio/
+      - files~=^paddlespeech/audio/
     actions:
       label:
         add: ["Audio"]
@@ -100,7 +100,7 @@ pull_request_rules:
         add: ["README"]
   - name: "auto add label=Documentation"
     conditions:
-      - files~=^(docs/|CHANGELOG.md|paddleaudio/CHANGELOG.md)
+      - files~=^(docs/|CHANGELOG.md)
     actions:
       label:
         add: ["Documentation"]

audio/.gitignore

@@ -1,2 +0,0 @@
-.eggs
-*.wav

audio/CHANGELOG.md

@@ -1,9 +0,0 @@
-# Changelog
-
-Date: 2022-3-15, Author: Xiaojie Chen.
-  - kaldi and librosa mfcc, fbank, spectrogram.
-  - unit test and benchmark.
-
-Date: 2022-2-25, Author: Hui Zhang.
-  - Refactor architecture.
-  - dtw distance and mcd style dtw.

audio/README.md

@@ -1,7 +0,0 @@
-# PaddleAudio
-
-PaddleAudio is an audio library for PaddlePaddle.
-
-## Install
-
-`pip install .`

audio/docs/Makefile

@@ -1,19 +0,0 @@
-# Minimal makefile for Sphinx documentation
-#
-
-# You can set these variables from the command line.
-SPHINXOPTS    =
-SPHINXBUILD   = sphinx-build
-SOURCEDIR     = source
-BUILDDIR      = build
-
-# Put it first so that "make" without argument is like "make help".
-help:
-	@$(SPHINXBUILD) -M help "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)
-
-.PHONY: help Makefile
-
-# Catch-all target: route all unknown targets to Sphinx using the new
-# "make mode" option.  $(O) is meant as a shortcut for $(SPHINXOPTS).
-%: Makefile
-	@$(SPHINXBUILD) -M $@ "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)

audio/docs/README.md

@@ -1,24 +0,0 @@
-# Build docs for PaddleAudio
-
-Execute the following steps in **current directory**.
-
-## 1. Install
-
-`pip install Sphinx sphinx_rtd_theme`
-
-
-## 2. Generate API docs
-
-Generate API docs from doc string.
-
-`sphinx-apidoc -fMeT -o source ../paddleaudio ../paddleaudio/utils --templatedir source/_templates`
-
-
-## 3. Build
-
-`sphinx-build source _html`
-
-
-## 4. Preview
-
-Open `_html/index.html` for page preview.

audio/docs/make.bat

@@ -1,35 +0,0 @@
-@ECHO OFF
-
-pushd %~dp0
-
-REM Command file for Sphinx documentation
-
-if "%SPHINXBUILD%" == "" (
-	set SPHINXBUILD=sphinx-build
-)
-set SOURCEDIR=source
-set BUILDDIR=build
-
-if "%1" == "" goto help
-
-%SPHINXBUILD% >NUL 2>NUL
-if errorlevel 9009 (
-	echo.
-	echo.The 'sphinx-build' command was not found. Make sure you have Sphinx
-	echo.installed, then set the SPHINXBUILD environment variable to point
-	echo.to the full path of the 'sphinx-build' executable. Alternatively you
-	echo.may add the Sphinx directory to PATH.
-	echo.
-	echo.If you don't have Sphinx installed, grab it from
-	echo.http://sphinx-doc.org/
-	exit /b 1
-)
-
-%SPHINXBUILD% -M %1 %SOURCEDIR% %BUILDDIR% %SPHINXOPTS%
-goto end
-
-:help
-%SPHINXBUILD% -M help %SOURCEDIR% %BUILDDIR% %SPHINXOPTS%
-
-:end
-popd

audio/paddleaudio/utils/env.py

@@ -1,60 +0,0 @@
-# Copyright (c) 2021  PaddlePaddle Authors. All Rights Reserved.
-#
-# Licensed under the Apache License, Version 2.0 (the "License"
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-#     http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-'''
-This module is used to store environmental variables in PaddleAudio.
-PPAUDIO_HOME     -->  the root directory for storing PaddleAudio related data. Default to ~/.paddleaudio. Users can change the
-├                            default value through the PPAUDIO_HOME environment variable.
-├─ MODEL_HOME    -->  Store model files.
-└─ DATA_HOME     -->  Store automatically downloaded datasets.
-'''
-import os
-
-__all__ = [
-    'USER_HOME',
-    'PPAUDIO_HOME',
-    'MODEL_HOME',
-    'DATA_HOME',
-]
-
-
-def _get_user_home():
-    return os.path.expanduser('~')
-
-
-def _get_ppaudio_home():
-    if 'PPAUDIO_HOME' in os.environ:
-        home_path = os.environ['PPAUDIO_HOME']
-        if os.path.exists(home_path):
-            if os.path.isdir(home_path):
-                return home_path
-            else:
-                raise RuntimeError(
-                    'The environment variable PPAUDIO_HOME {} is not a directory.'.
-                    format(home_path))
-        else:
-            return home_path
-    return os.path.join(_get_user_home(), '.paddleaudio')
-
-
-def _get_sub_home(directory):
-    home = os.path.join(_get_ppaudio_home(), directory)
-    if not os.path.exists(home):
-        os.makedirs(home)
-    return home
-
-
-USER_HOME = _get_user_home()
-PPAUDIO_HOME = _get_ppaudio_home()
-MODEL_HOME = _get_sub_home('models')
-DATA_HOME = _get_sub_home('datasets')

audio/setup.py

@@ -1,99 +0,0 @@
-# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-#     http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-import glob
-import os
-
-import setuptools
-from setuptools.command.install import install
-from setuptools.command.test import test
-
-# set the version here
-VERSION = '0.0.0'
-
-
-# Inspired by the example at https://pytest.org/latest/goodpractises.html
-class TestCommand(test):
-    def finalize_options(self):
-        test.finalize_options(self)
-        self.test_args = []
-        self.test_suite = True
-
-    def run(self):
-        self.run_benchmark()
-        super(TestCommand, self).run()
-
-    def run_tests(self):
-        # Run nose ensuring that argv simulates running nosetests directly
-        import nose
-        nose.run_exit(argv=['nosetests', '-w', 'tests'])
-
-    def run_benchmark(self):
-        for benchmark_item in glob.glob('tests/benchmark/*py'):
-            os.system(f'pytest {benchmark_item}')
-
-
-class InstallCommand(install):
-    def run(self):
-        install.run(self)
-
-
-def write_version_py(filename='paddleaudio/__init__.py'):
-    with open(filename, "a") as f:
-        f.write(f"__version__ = '{VERSION}'")
-
-
-def remove_version_py(filename='paddleaudio/__init__.py'):
-    with open(filename, "r") as f:
-        lines = f.readlines()
-    with open(filename, "w") as f:
-        for line in lines:
-            if "__version__" not in line:
-                f.write(line)
-
-
-remove_version_py()
-write_version_py()
-
-setuptools.setup(
-    name="paddleaudio",
-    version=VERSION,
-    author="",
-    author_email="",
-    description="PaddleAudio, in development",
-    long_description="",
-    long_description_content_type="text/markdown",
-    url="",
-    packages=setuptools.find_packages(include=['paddleaudio*']),
-    classifiers=[
-        "Programming Language :: Python :: 3",
-        "License :: OSI Approved :: MIT License",
-        "Operating System :: OS Independent",
-    ],
-    python_requires='>=3.6',
-    install_requires=[
-        'numpy >= 1.15.0', 'scipy >= 1.0.0', 'resampy >= 0.2.2',
-        'soundfile >= 0.9.0', 'colorlog', 'pathos == 0.2.8'
-    ],
-    extras_require={
-        'test': [
-            'nose', 'librosa==0.8.1', 'soundfile==0.10.3.post1',
-            'torchaudio==0.10.2', 'pytest-benchmark'
-        ],
-    },
-    cmdclass={
-        'install': InstallCommand,
-        'test': TestCommand,
-    }, )
-
-remove_version_py()

demos/audio_searching/README.md

@@ -89,7 +89,7 @@ Then to start the system server, and it provides HTTP backend services.
   Then start the server with Fastapi.
 
   ```bash
-  export PYTHONPATH=$PYTHONPATH:./src:../../paddleaudio
+  export PYTHONPATH=$PYTHONPATH:./src
   python src/audio_search.py
   ```
 

demos/audio_searching/README_cn.md

@@ -91,7 +91,7 @@ ffce340b3790  minio/minio:RELEASE.2020-12-03T00-03-10Z  "/usr/bin/docker-ent…"
   启动用 Fastapi 构建的服务
 
   ```bash
-  export PYTHONPATH=$PYTHONPATH:./src:../../paddleaudio
+  export PYTHONPATH=$PYTHONPATH:./src
   python src/audio_search.py
   ```
 

docs/source/cls/custom_dataset.md

@@ -1,8 +1,8 @@
 # Customize Dataset for Audio Classification
 
-Following this tutorial you can customize your dataset for audio classification task by using `paddlespeech` and `paddleaudio`.
+Following this tutorial you can customize your dataset for audio classification task by using `paddlespeech`.
 
-A base class of classification dataset is `paddleaudio.dataset.AudioClassificationDataset`. To customize your dataset you should write a dataset class derived from `AudioClassificationDataset`. 
+A base class of classification dataset is `paddlespeech.audio.dataset.AudioClassificationDataset`. To customize your dataset you should write a dataset class derived from `AudioClassificationDataset`. 
 
 Assuming you have some wave files that stored in your own directory. You should prepare a meta file with the information of filepaths and labels. For example the absolute path of it is `/PATH/TO/META_FILE.txt`:
 ```
@@ -14,7 +14,7 @@ Assuming you have some wave files that stored in your own directory. You should
 Here is an example to build your custom dataset in `custom_dataset.py`:
 
 ```python
-from paddleaudio.datasets.dataset import AudioClassificationDataset
+from paddlespeech.audio.datasets.dataset import AudioClassificationDataset
 
 class CustomDataset(AudioClassificationDataset):
     meta_file = '/PATH/TO/META_FILE.txt'
@@ -48,7 +48,7 @@ class CustomDataset(AudioClassificationDataset):
 Then you can build dataset and data loader from `CustomDataset`:
 ```python
 import paddle
-from paddleaudio.features import LogMelSpectrogram
+from paddlespeech.audio.features import LogMelSpectrogram
 
 from custom_dataset import CustomDataset
 

examples/esc50/cls0/conf/panns.yaml

@@ -1,5 +1,5 @@
 data:
-  dataset: 'paddleaudio.datasets:ESC50'
+  dataset: 'paddlespeech.audio.datasets:ESC50'
   num_classes: 50
   train:
     mode: 'train'

examples/hey_snips/kws0/conf/mdtc.yaml

@@ -2,7 +2,7 @@
 ###########################################
 #                   Data                  #
 ###########################################
-dataset: 'paddleaudio.datasets:HeySnips'
+dataset: 'paddlespeech.audio.datasets:HeySnips'
 data_dir: '/PATH/TO/DATA/hey_snips_research_6k_en_train_eval_clean_ter'
 
 ############################################

examples/voxceleb/sv0/local/data_prepare.py

@@ -14,9 +14,9 @@
 import argparse
 
 import paddle
-from paddleaudio.datasets.voxceleb import VoxCeleb
 from yacs.config import CfgNode
 
+from paddlespeech.audio.datasets.voxceleb import VoxCeleb
 from paddlespeech.s2t.utils.log import Log
 from paddlespeech.vector.io.augment import build_augment_pipeline
 from paddlespeech.vector.training.seeding import seed_everything

examples/voxceleb/sv0/local/make_rirs_noise_csv_dataset_from_json.py

@@ -21,9 +21,9 @@ import os
 from typing import List
 
 import tqdm
-from paddleaudio import load as load_audio
 from yacs.config import CfgNode
 
+from paddlespeech.audio import load as load_audio
 from paddlespeech.s2t.utils.log import Log
 from paddlespeech.vector.utils.vector_utils import get_chunks
 

examples/voxceleb/sv0/local/make_vox_csv_dataset_from_json.py

@@ -22,9 +22,9 @@ import os
 import random
 
 import tqdm
-from paddleaudio import load as load_audio
 from yacs.config import CfgNode
 
+from paddlespeech.audio import load as load_audio
 from paddlespeech.s2t.utils.log import Log
 from paddlespeech.vector.utils.vector_utils import get_chunks
 

paddlespeech/audio/datasets/esc50.py

@@ -16,8 +16,8 @@ import os
 from typing import List
 from typing import Tuple
 
+from ..utils import DATA_HOME
 from ..utils.download import download_and_decompress
-from ..utils.env import DATA_HOME
 from .dataset import AudioClassificationDataset
 
 __all__ = ['ESC50']

paddlespeech/audio/datasets/gtzan.py

@@ -17,8 +17,8 @@ import random
 from typing import List
 from typing import Tuple
 
+from ..utils import DATA_HOME
 from ..utils.download import download_and_decompress
-from ..utils.env import DATA_HOME
 from .dataset import AudioClassificationDataset
 
 __all__ = ['GTZAN']

paddlespeech/audio/datasets/tess.py

@@ -17,8 +17,8 @@ import random
 from typing import List
 from typing import Tuple
 
+from ..utils import DATA_HOME
 from ..utils.download import download_and_decompress
-from ..utils.env import DATA_HOME
 from .dataset import AudioClassificationDataset
 
 __all__ = ['TESS']

paddlespeech/audio/datasets/urban_sound.py

@@ -16,8 +16,8 @@ import os
 from typing import List
 from typing import Tuple
 
+from ..utils import DATA_HOME
 from ..utils.download import download_and_decompress
-from ..utils.env import DATA_HOME
 from .dataset import AudioClassificationDataset
 
 __all__ = ['UrbanSound8K']

paddlespeech/audio/utils/__init__.py

@@ -11,13 +11,11 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
+from ...cli.utils import DATA_HOME
+from ...cli.utils import MODEL_HOME
 from .download import decompress
 from .download import download_and_decompress
 from .download import load_state_dict_from_url
-from .env import DATA_HOME
-from .env import MODEL_HOME
-from .env import PPAUDIO_HOME
-from .env import USER_HOME
 from .error import ParameterError
 from .log import Logger
 from .log import logger

paddlespeech/cli/cls/infer.py

@@ -21,12 +21,12 @@ from typing import Union
 import numpy as np
 import paddle
 import yaml
-from paddleaudio import load
-from paddleaudio.features import LogMelSpectrogram
 
 from ..executor import BaseExecutor
 from ..log import logger
 from ..utils import stats_wrapper
+from paddlespeech.audio import load
+from paddlespeech.audio.features import LogMelSpectrogram
 
 __all__ = ['CLSExecutor']
 

paddlespeech/cli/utils.py

@@ -24,11 +24,11 @@ from typing import Any
 from typing import Dict
 
 import paddle
-import paddleaudio
 import requests
 import yaml
 from paddle.framework import load
 
+import paddlespeech.audio
 from . import download
 from .entry import commands
 try:
@@ -190,6 +190,7 @@ def _get_sub_home(directory):
 PPSPEECH_HOME = _get_paddlespcceh_home()
 MODEL_HOME = _get_sub_home('models')
 CONF_HOME = _get_sub_home('conf')
+DATA_HOME = _get_sub_home('datasets')
 
 
 def _md5(text: str):
@@ -281,7 +282,7 @@ def _note_one_stat(cls_name, params={}):
 
     if 'audio_file' in params:
         try:
-            _, sr = paddleaudio.load(params['audio_file'])
+            _, sr = paddlespeech.audio.load(params['audio_file'])
         except Exception:
             sr = -1
 

paddlespeech/cli/vector/infer.py

@@ -22,13 +22,13 @@ from typing import Union
 
 import paddle
 import soundfile
-from paddleaudio.backends import load as load_audio
-from paddleaudio.compliance.librosa import melspectrogram
 from yacs.config import CfgNode
 
 from ..executor import BaseExecutor
 from ..log import logger
 from ..utils import stats_wrapper
+from paddlespeech.audio.backends import load as load_audio
+from paddlespeech.audio.compliance.librosa import melspectrogram
 from paddlespeech.vector.io.batch import feature_normalize
 from paddlespeech.vector.modules.sid_model import SpeakerIdetification
 

paddlespeech/cls/exps/panns/deploy/predict.py

@@ -16,11 +16,12 @@ import os
 
 import numpy as np
 from paddle import inference
-from paddleaudio.backends import load as load_audio
-from paddleaudio.datasets import ESC50
-from paddleaudio.features import melspectrogram
 from scipy.special import softmax
 
+from paddlespeech.audio.backends import load as load_audio
+from paddlespeech.audio.datasets import ESC50
+from paddlespeech.audio.features import melspectrogram
+
 # yapf: disable
 parser = argparse.ArgumentParser()
 parser.add_argument("--model_dir", type=str, required=True, default="./export", help="The directory to static model.")

paddlespeech/cls/exps/panns/export_model.py

@@ -15,8 +15,8 @@ import argparse
 import os
 
 import paddle
-from paddleaudio.datasets import ESC50
 
+from paddlespeech.audio.datasets import ESC50
 from paddlespeech.cls.models import cnn14
 from paddlespeech.cls.models import SoundClassifier
 

paddlespeech/cls/exps/panns/predict.py

@@ -17,10 +17,10 @@ import os
 import paddle
 import paddle.nn.functional as F
 import yaml
-from paddleaudio.backends import load as load_audio
-from paddleaudio.features import LogMelSpectrogram
-from paddleaudio.utils import logger
 
+from paddlespeech.audio.backends import load as load_audio
+from paddlespeech.audio.features import LogMelSpectrogram
+from paddlespeech.audio.utils import logger
 from paddlespeech.cls.models import SoundClassifier
 from paddlespeech.utils.dynamic_import import dynamic_import
 

paddlespeech/cls/exps/panns/train.py

@@ -16,10 +16,10 @@ import os
 
 import paddle
 import yaml
-from paddleaudio.features import LogMelSpectrogram
-from paddleaudio.utils import logger
-from paddleaudio.utils import Timer
 
+from paddlespeech.audio.features import LogMelSpectrogram
+from paddlespeech.audio.utils import logger
+from paddlespeech.audio.utils import Timer
 from paddlespeech.cls.models import SoundClassifier
 from paddlespeech.utils.dynamic_import import dynamic_import
 

paddlespeech/cls/models/panns/panns.py

@@ -15,8 +15,9 @@ import os
 
 import paddle.nn as nn
 import paddle.nn.functional as F
-from paddleaudio.utils.download import load_state_dict_from_url
+
-from paddleaudio.utils.env import MODEL_HOME
+from paddlespeech.audio.utils import MODEL_HOME
+from paddlespeech.audio.utils.download import load_state_dict_from_url
 
 __all__ = ['CNN14', 'CNN10', 'CNN6', 'cnn14', 'cnn10', 'cnn6']
 

paddlespeech/kws/exps/mdtc/train.py

@@ -14,10 +14,10 @@
 import os
 
 import paddle
-from paddleaudio.utils import logger
-from paddleaudio.utils import Timer
 from yacs.config import CfgNode
 
+from paddlespeech.audio.utils import logger
+from paddlespeech.audio.utils import Timer
 from paddlespeech.kws.exps.mdtc.collate import collate_features
 from paddlespeech.kws.models.loss import max_pooling_loss
 from paddlespeech.kws.models.mdtc import KWSModel

paddlespeech/s2t/frontend/featurizer/audio_featurizer.py

@@ -14,10 +14,11 @@
 """Contains the audio featurizer class."""
 import numpy as np
 import paddle
-import paddleaudio.compliance.kaldi as kaldi
 from python_speech_features import delta
 from python_speech_features import mfcc
 
+import paddlespeech.audio.compliance.kaldi as kaldi
+
 
 class AudioFeaturizer():
     """Audio featurizer, for extracting features from audio contents of

paddlespeech/s2t/transform/spectrogram.py

@@ -15,9 +15,10 @@
 import librosa
 import numpy as np
 import paddle
-import paddleaudio.compliance.kaldi as kaldi
 from python_speech_features import logfbank
 
+import paddlespeech.audio.compliance.kaldi as kaldi
+
 
 def stft(x,
          n_fft,

paddlespeech/server/engine/vector/python/vector_engine.py

@@ -16,9 +16,9 @@ from collections import OrderedDict
 
 import numpy as np
 import paddle
-from paddleaudio.backends import load as load_audio
-from paddleaudio.compliance.librosa import melspectrogram
 
+from paddlespeech.audio.backends import load as load_audio
+from paddlespeech.audio.compliance.librosa import melspectrogram
 from paddlespeech.cli.log import logger
 from paddlespeech.cli.vector.infer import VectorExecutor
 from paddlespeech.server.engine.base_engine import BaseEngine

paddlespeech/server/util.py

@@ -24,11 +24,11 @@ from typing import Any
 from typing import Dict
 
 import paddle
-import paddleaudio
 import requests
 import yaml
 from paddle.framework import load
 
+import paddlespeech.audio
 from .entry import client_commands
 from .entry import server_commands
 from paddlespeech.cli import download
@@ -289,7 +289,7 @@ def _note_one_stat(cls_name, params={}):
 
     if 'audio_file' in params:
         try:
-            _, sr = paddleaudio.load(params['audio_file'])
+            _, sr = paddlespeech.audio.load(params['audio_file'])
         except Exception:
             sr = -1
 

paddlespeech/vector/exps/ecapa_tdnn/extract_emb.py

@@ -16,10 +16,10 @@ import os
 import time
 
 import paddle
-from paddleaudio.backends import load as load_audio
-from paddleaudio.compliance.librosa import melspectrogram
 from yacs.config import CfgNode
 
+from paddlespeech.audio.backends import load as load_audio
+from paddlespeech.audio.compliance.librosa import melspectrogram
 from paddlespeech.s2t.utils.log import Log
 from paddlespeech.vector.io.batch import feature_normalize
 from paddlespeech.vector.models.ecapa_tdnn import EcapaTdnn

paddlespeech/vector/exps/ecapa_tdnn/test.py

@@ -18,10 +18,10 @@ import numpy as np
 import paddle
 from paddle.io import BatchSampler
 from paddle.io import DataLoader
-from paddleaudio.metric import compute_eer
 from tqdm import tqdm
 from yacs.config import CfgNode
 
+from paddlespeech.audio.metric import compute_eer
 from paddlespeech.s2t.utils.log import Log
 from paddlespeech.vector.io.batch import batch_feature_normalize
 from paddlespeech.vector.io.dataset import CSVDataset

paddlespeech/vector/exps/ecapa_tdnn/train.py

@@ -20,9 +20,9 @@ import paddle
 from paddle.io import BatchSampler
 from paddle.io import DataLoader
 from paddle.io import DistributedBatchSampler
-from paddleaudio.compliance.librosa import melspectrogram
 from yacs.config import CfgNode
 
+from paddlespeech.audio.compliance.librosa import melspectrogram
 from paddlespeech.s2t.utils.log import Log
 from paddlespeech.vector.io.augment import build_augment_pipeline
 from paddlespeech.vector.io.augment import waveform_augment

paddlespeech/vector/io/dataset.py

@@ -15,9 +15,9 @@ from dataclasses import dataclass
 from dataclasses import fields
 
 from paddle.io import Dataset
-from paddleaudio import load as load_audio
-from paddleaudio.compliance.librosa import melspectrogram
 
+from paddlespeech.audio import load as load_audio
+from paddlespeech.audio.compliance.librosa import melspectrogram
 from paddlespeech.s2t.utils.log import Log
 logger = Log(__name__).getlog()
 

paddlespeech/vector/io/dataset_from_json.py

@@ -16,9 +16,10 @@ from dataclasses import dataclass
 from dataclasses import fields
 
 from paddle.io import Dataset
-from paddleaudio import load as load_audio
+
-from paddleaudio.compliance.librosa import melspectrogram
+from paddlespeech.audio import load as load_audio
-from paddleaudio.compliance.librosa import mfcc
+from paddlespeech.audio.compliance.librosa import melspectrogram
+from paddlespeech.audio.compliance.librosa import mfcc
 
 
 @dataclass

setup.py

@@ -24,6 +24,7 @@ from setuptools import find_packages
 from setuptools import setup
 from setuptools.command.develop import develop
 from setuptools.command.install import install
+from setuptools.command.test import test
 
 HERE = Path(os.path.abspath(os.path.dirname(__file__)))
 
@@ -31,42 +32,13 @@ VERSION = '0.0.0'
 COMMITID = 'none'
 
 base = [
-    "editdistance",
+    "editdistance", "g2p_en", "g2pM", "h5py", "inflect", "jieba", "jsonlines",
-    "g2p_en",
+    "kaldiio", "librosa==0.8.1", "loguru", "matplotlib", "nara_wpe",
-    "g2pM",
+    "onnxruntime", "pandas", "paddlenlp", "paddlespeech_feat", "praatio==5.0.0",
-    "h5py",
+    "pypinyin", "pypinyin-dict", "python-dateutil", "pyworld", "resampy==0.2.2",
-    "inflect",
+    "sacrebleu", "scipy", "sentencepiece~=0.1.96", "soundfile~=0.10",
-    "jieba",
+    "textgrid", "timer", "tqdm", "typeguard", "visualdl", "webrtcvad",
-    "jsonlines",
+    "yacs~=0.1.8", "prettytable", "zhon", 'colorlog', 'pathos == 0.2.8'
-    "kaldiio",
-    "librosa==0.8.1",
-    "loguru",
-    "matplotlib",
-    "nara_wpe",
-    "onnxruntime",
-    "pandas",
-    "paddleaudio",
-    "paddlenlp",
-    "paddlespeech_feat",
-    "praatio==5.0.0",
-    "pypinyin",
-    "pypinyin-dict",
-    "python-dateutil",
-    "pyworld",
-    "resampy==0.2.2",
-    "sacrebleu",
-    "scipy",
-    "sentencepiece~=0.1.96",
-    "soundfile~=0.10",
-    "textgrid",
-    "timer",
-    "tqdm",
-    "typeguard",
-    "visualdl",
-    "webrtcvad",
-    "yacs~=0.1.8",
-    "prettytable",
-    "zhon",
 ]
 
 server = [
@@ -177,7 +149,19 @@ class InstallCommand(install):
         install.run(self)
 
 
-    # cmd: python setup.py upload
+class TestCommand(test):
+    def finalize_options(self):
+        test.finalize_options(self)
+        self.test_args = []
+        self.test_suite = True
+
+    def run_tests(self):
+        # Run nose ensuring that argv simulates running nosetests directly
+        import nose
+        nose.run_exit(argv=['nosetests', '-w', 'tests'])
+
+
+# cmd: python setup.py upload
 class UploadCommand(Command):
     description = "Build and publish the package."
     user_options = []
@@ -279,11 +263,13 @@ setup_info = dict(
             "sphinx", "sphinx-rtd-theme", "numpydoc", "myst_parser",
             "recommonmark>=0.5.0", "sphinx-markdown-tables", "sphinx-autobuild"
         ],
+        'test': ['nose', 'torchaudio==0.10.2'],
     },
     cmdclass={
         'develop': DevelopCommand,
         'install': InstallCommand,
         'upload': UploadCommand,
+        'test': TestCommand,
     },
 
     # Package info

tests/benchmark/audio/README.md

@@ -15,7 +15,6 @@ Result:
 ========================================================================== test session starts ==========================================================================
 platform linux -- Python 3.7.7, pytest-7.0.1, pluggy-1.0.0
 benchmark: 3.4.1 (defaults: timer=time.perf_counter disable_gc=False min_rounds=5 min_time=0.000005 max_time=1.0 calibration_precision=10 warmup=False warmup_iterations=100000)
-rootdir: /ssd3/chenxiaojie06/PaddleSpeech/DeepSpeech/paddleaudio
 plugins: typeguard-2.12.1, benchmark-3.4.1, anyio-3.5.0
 collected 4 items
 

tests/benchmark/audio/log_melspectrogram.py

@@ -17,15 +17,17 @@ import urllib.request
 import librosa
 import numpy as np
 import paddle
-import paddleaudio
 import torch
 import torchaudio
 
+import paddlespeech.audio
+
 wav_url = 'https://paddlespeech.bj.bcebos.com/PaddleAudio/zh.wav'
 if not os.path.isfile(os.path.basename(wav_url)):
     urllib.request.urlretrieve(wav_url, os.path.basename(wav_url))
 
-waveform, sr = paddleaudio.load(os.path.abspath(os.path.basename(wav_url)))
+waveform, sr = paddlespeech.audio.load(
+    os.path.abspath(os.path.basename(wav_url)))
 waveform_tensor = paddle.to_tensor(waveform).unsqueeze(0)
 waveform_tensor_torch = torch.from_numpy(waveform).unsqueeze(0)
 
@@ -55,7 +57,7 @@ def enable_gpu_device():
     paddle.set_device('gpu')
 
 
-log_mel_extractor = paddleaudio.features.LogMelSpectrogram(
+log_mel_extractor = paddlespeech.audio.features.LogMelSpectrogram(
     **mel_conf, f_min=0.0, top_db=80.0, dtype=waveform_tensor.dtype)
 
 
@@ -65,20 +67,20 @@ def log_melspectrogram():
 
 def test_log_melspect_cpu(benchmark):
     enable_cpu_device()
-    feature_paddleaudio = benchmark(log_melspectrogram)
+    feature_audio = benchmark(log_melspectrogram)
     feature_librosa = librosa.feature.melspectrogram(waveform, **mel_conf)
     feature_librosa = librosa.power_to_db(feature_librosa, top_db=80.0)
     np.testing.assert_array_almost_equal(
-        feature_librosa, feature_paddleaudio, decimal=3)
+        feature_librosa, feature_audio, decimal=3)
 
 
 def test_log_melspect_gpu(benchmark):
     enable_gpu_device()
-    feature_paddleaudio = benchmark(log_melspectrogram)
+    feature_audio = benchmark(log_melspectrogram)
     feature_librosa = librosa.feature.melspectrogram(waveform, **mel_conf)
     feature_librosa = librosa.power_to_db(feature_librosa, top_db=80.0)
     np.testing.assert_array_almost_equal(
-        feature_librosa, feature_paddleaudio, decimal=2)
+        feature_librosa, feature_audio, decimal=2)
 
 
 mel_extractor_torchaudio = torchaudio.transforms.MelSpectrogram(
@@ -102,11 +104,11 @@ def test_log_melspect_cpu_torchaudio(benchmark):
     waveform_tensor_torch = waveform_tensor_torch.to('cpu')
     amplitude_to_DB = amplitude_to_DB.to('cpu')
 
-    feature_paddleaudio = benchmark(log_melspectrogram_torchaudio)
+    feature_audio = benchmark(log_melspectrogram_torchaudio)
     feature_librosa = librosa.feature.melspectrogram(waveform, **mel_conf)
     feature_librosa = librosa.power_to_db(feature_librosa, top_db=80.0)
     np.testing.assert_array_almost_equal(
-        feature_librosa, feature_paddleaudio, decimal=3)
+        feature_librosa, feature_audio, decimal=3)
 
 
 def test_log_melspect_gpu_torchaudio(benchmark):

tests/benchmark/audio/melspectrogram.py

@@ -17,15 +17,17 @@ import urllib.request
 import librosa
 import numpy as np
 import paddle
-import paddleaudio
 import torch
 import torchaudio
 
+import paddlespeech.audio
+
 wav_url = 'https://paddlespeech.bj.bcebos.com/PaddleAudio/zh.wav'
 if not os.path.isfile(os.path.basename(wav_url)):
     urllib.request.urlretrieve(wav_url, os.path.basename(wav_url))
 
-waveform, sr = paddleaudio.load(os.path.abspath(os.path.basename(wav_url)))
+waveform, sr = paddlespeech.audio.load(
+    os.path.abspath(os.path.basename(wav_url)))
 waveform_tensor = paddle.to_tensor(waveform).unsqueeze(0)
 waveform_tensor_torch = torch.from_numpy(waveform).unsqueeze(0)
 
@@ -55,7 +57,7 @@ def enable_gpu_device():
     paddle.set_device('gpu')
 
 
-mel_extractor = paddleaudio.features.MelSpectrogram(
+mel_extractor = paddlespeech.audio.features.MelSpectrogram(
     **mel_conf, f_min=0.0, dtype=waveform_tensor.dtype)
 
 
@@ -65,18 +67,18 @@ def melspectrogram():
 
 def test_melspect_cpu(benchmark):
     enable_cpu_device()
-    feature_paddleaudio = benchmark(melspectrogram)
+    feature_audio = benchmark(melspectrogram)
     feature_librosa = librosa.feature.melspectrogram(waveform, **mel_conf)
     np.testing.assert_array_almost_equal(
-        feature_librosa, feature_paddleaudio, decimal=3)
+        feature_librosa, feature_audio, decimal=3)
 
 
 def test_melspect_gpu(benchmark):
     enable_gpu_device()
-    feature_paddleaudio = benchmark(melspectrogram)
+    feature_audio = benchmark(melspectrogram)
     feature_librosa = librosa.feature.melspectrogram(waveform, **mel_conf)
     np.testing.assert_array_almost_equal(
-        feature_librosa, feature_paddleaudio, decimal=3)
+        feature_librosa, feature_audio, decimal=3)
 
 
 mel_extractor_torchaudio = torchaudio.transforms.MelSpectrogram(
@@ -91,10 +93,10 @@ def test_melspect_cpu_torchaudio(benchmark):
     global waveform_tensor_torch, mel_extractor_torchaudio
     mel_extractor_torchaudio = mel_extractor_torchaudio.to('cpu')
     waveform_tensor_torch = waveform_tensor_torch.to('cpu')
-    feature_paddleaudio = benchmark(melspectrogram_torchaudio)
+    feature_audio = benchmark(melspectrogram_torchaudio)
     feature_librosa = librosa.feature.melspectrogram(waveform, **mel_conf)
     np.testing.assert_array_almost_equal(
-        feature_librosa, feature_paddleaudio, decimal=3)
+        feature_librosa, feature_audio, decimal=3)
 
 
 def test_melspect_gpu_torchaudio(benchmark):

tests/benchmark/audio/mfcc.py

@@ -17,15 +17,17 @@ import urllib.request
 import librosa
 import numpy as np
 import paddle
-import paddleaudio
 import torch
 import torchaudio
 
+import paddlespeech.audio
+
 wav_url = 'https://paddlespeech.bj.bcebos.com/PaddleAudio/zh.wav'
 if not os.path.isfile(os.path.basename(wav_url)):
     urllib.request.urlretrieve(wav_url, os.path.basename(wav_url))
 
-waveform, sr = paddleaudio.load(os.path.abspath(os.path.basename(wav_url)))
+waveform, sr = paddlespeech.audio.load(
+    os.path.abspath(os.path.basename(wav_url)))
 waveform_tensor = paddle.to_tensor(waveform).unsqueeze(0)
 waveform_tensor_torch = torch.from_numpy(waveform).unsqueeze(0)
 
@@ -64,7 +66,7 @@ def enable_gpu_device():
     paddle.set_device('gpu')
 
 
-mfcc_extractor = paddleaudio.features.MFCC(
+mfcc_extractor = paddlespeech.audio.features.MFCC(
     **mfcc_conf, f_min=0.0, dtype=waveform_tensor.dtype)
 
 
@@ -74,18 +76,18 @@ def mfcc():
 
 def test_mfcc_cpu(benchmark):
     enable_cpu_device()
-    feature_paddleaudio = benchmark(mfcc)
+    feature_audio = benchmark(mfcc)
     feature_librosa = librosa.feature.mfcc(waveform, **mel_conf)
     np.testing.assert_array_almost_equal(
-        feature_librosa, feature_paddleaudio, decimal=3)
+        feature_librosa, feature_audio, decimal=3)
 
 
 def test_mfcc_gpu(benchmark):
     enable_gpu_device()
-    feature_paddleaudio = benchmark(mfcc)
+    feature_audio = benchmark(mfcc)
     feature_librosa = librosa.feature.mfcc(waveform, **mel_conf)
     np.testing.assert_array_almost_equal(
-        feature_librosa, feature_paddleaudio, decimal=3)
+        feature_librosa, feature_audio, decimal=3)
 
 
 del mel_conf_torchaudio['sample_rate']
@@ -103,10 +105,10 @@ def test_mfcc_cpu_torchaudio(benchmark):
     mel_extractor_torchaudio = mfcc_extractor_torchaudio.to('cpu')
     waveform_tensor_torch = waveform_tensor_torch.to('cpu')
 
-    feature_paddleaudio = benchmark(mfcc_torchaudio)
+    feature_audio = benchmark(mfcc_torchaudio)
     feature_librosa = librosa.feature.mfcc(waveform, **mel_conf)
     np.testing.assert_array_almost_equal(
-        feature_librosa, feature_paddleaudio, decimal=3)
+        feature_librosa, feature_audio, decimal=3)
 
 
 def test_mfcc_gpu_torchaudio(benchmark):

tests/unit/audio/backends/soundfile/test_io.py

@@ -16,16 +16,16 @@ import os
 import unittest
 
 import numpy as np
-import paddleaudio
 import soundfile as sf
 
+import paddlespeech.audio
 from ..base import BackendTest
 
 
 class TestIO(BackendTest):
     def test_load_mono_channel(self):
         sf_data, sf_sr = sf.read(self.files[0])
-        pa_data, pa_sr = paddleaudio.load(
+        pa_data, pa_sr = paddlespeech.audio.load(
             self.files[0], normal=False, dtype='float64')
 
         self.assertEqual(sf_data.dtype, pa_data.dtype)
@@ -35,7 +35,7 @@ class TestIO(BackendTest):
     def test_load_multi_channels(self):
         sf_data, sf_sr = sf.read(self.files[1])
         sf_data = sf_data.T  # Channel dim first
-        pa_data, pa_sr = paddleaudio.load(
+        pa_data, pa_sr = paddlespeech.audio.load(
             self.files[1], mono=False, normal=False, dtype='float64')
 
         self.assertEqual(sf_data.dtype, pa_data.dtype)
@@ -49,7 +49,7 @@ class TestIO(BackendTest):
         pa_tmp_file = 'pa_tmp.wav'
 
         sf.write(sf_tmp_file, waveform, sr)
-        paddleaudio.save(waveform, sr, pa_tmp_file)
+        paddlespeech.audio.save(waveform, sr, pa_tmp_file)
 
         self.assertTrue(filecmp.cmp(sf_tmp_file, pa_tmp_file))
         for file in [sf_tmp_file, pa_tmp_file]:
@@ -62,7 +62,7 @@ class TestIO(BackendTest):
         pa_tmp_file = 'pa_tmp.wav'
 
         sf.write(sf_tmp_file, waveform.T, sr)
-        paddleaudio.save(waveform.T, sr, pa_tmp_file)
+        paddlespeech.audio.save(waveform.T, sr, pa_tmp_file)
 
         self.assertTrue(filecmp.cmp(sf_tmp_file, pa_tmp_file))
         for file in [sf_tmp_file, pa_tmp_file]:

tests/unit/audio/features/base.py

@@ -17,7 +17,8 @@ import urllib.request
 
 import numpy as np
 import paddle
-from paddleaudio import load
+
+from paddlespeech.audio import load
 
 wav_url = 'https://paddlespeech.bj.bcebos.com/PaddleAudio/zh.wav'
 

tests/unit/audio/features/test_istft.py

@@ -15,9 +15,9 @@ import unittest
 
 import numpy as np
 import paddle
-from paddleaudio.functional.window import get_window
 
 from .base import FeatTest
+from paddlespeech.audio.functional.window import get_window
 from paddlespeech.s2t.transform.spectrogram import IStft
 from paddlespeech.s2t.transform.spectrogram import Stft
 

tests/unit/audio/features/test_kaldi.py

@@ -15,10 +15,10 @@ import unittest
 
 import numpy as np
 import paddle
-import paddleaudio
 import torch
 import torchaudio
 
+import paddlespeech.audio
 from .base import FeatTest
 
 
@@ -40,17 +40,17 @@ class TestKaldi(FeatTest):
             self.window_size, periodic=False,
             dtype=eval(f'torch.{self.dtype}')).pow(0.85)
 
-        p_hann_window = paddleaudio.functional.window.get_window(
+        p_hann_window = paddlespeech.audio.functional.window.get_window(
             'hann',
             self.window_size,
             fftbins=False,
             dtype=eval(f'paddle.{self.dtype}'))
-        p_hamm_window = paddleaudio.functional.window.get_window(
+        p_hamm_window = paddlespeech.audio.functional.window.get_window(
             'hamming',
             self.window_size,
             fftbins=False,
             dtype=eval(f'paddle.{self.dtype}'))
-        p_povey_window = paddleaudio.functional.window.get_window(
+        p_povey_window = paddlespeech.audio.functional.window.get_window(
             'hann',
             self.window_size,
             fftbins=False,
@@ -63,7 +63,7 @@ class TestKaldi(FeatTest):
     def test_fbank(self):
         ta_features = torchaudio.compliance.kaldi.fbank(
             torch.from_numpy(self.waveform.astype(self.dtype)))
-        pa_features = paddleaudio.compliance.kaldi.fbank(
+        pa_features = paddlespeech.audio.compliance.kaldi.fbank(
             paddle.to_tensor(self.waveform.astype(self.dtype)))
         np.testing.assert_array_almost_equal(
             ta_features, pa_features, decimal=4)
@@ -71,7 +71,7 @@ class TestKaldi(FeatTest):
     def test_mfcc(self):
         ta_features = torchaudio.compliance.kaldi.mfcc(
             torch.from_numpy(self.waveform.astype(self.dtype)))
-        pa_features = paddleaudio.compliance.kaldi.mfcc(
+        pa_features = paddlespeech.audio.compliance.kaldi.mfcc(
             paddle.to_tensor(self.waveform.astype(self.dtype)))
         np.testing.assert_array_almost_equal(
             ta_features, pa_features, decimal=4)

tests/unit/audio/features/test_librosa.py

@@ -16,10 +16,10 @@ import unittest
 import librosa
 import numpy as np
 import paddle
-import paddleaudio
-from paddleaudio.functional.window import get_window
 
+import paddlespeech.audio
 from .base import FeatTest
+from paddlespeech.audio.functional.window import get_window
 
 
 class TestLibrosa(FeatTest):
@@ -117,7 +117,7 @@ class TestLibrosa(FeatTest):
             htk=False,
             norm='slaney',
             dtype=self.waveform.dtype, )
-        feature_compliance = paddleaudio.compliance.librosa.compute_fbank_matrix(
+        feature_compliance = paddlespeech.audio.compliance.librosa.compute_fbank_matrix(
             sr=self.sr,
             n_fft=self.n_fft,
             n_mels=self.n_mels,
@@ -127,7 +127,7 @@ class TestLibrosa(FeatTest):
             norm='slaney',
             dtype=self.waveform.dtype, )
         x = paddle.to_tensor(self.waveform)
-        feature_functional = paddleaudio.functional.compute_fbank_matrix(
+        feature_functional = paddlespeech.audio.functional.compute_fbank_matrix(
             sr=self.sr,
             n_fft=self.n_fft,
             n_mels=self.n_mels,
@@ -156,8 +156,8 @@ class TestLibrosa(FeatTest):
             n_mels=self.n_mels,
             fmin=self.fmin)
 
-        # paddleaudio.compliance.librosa:
+        # paddlespeech.audio.compliance.librosa:
-        feature_compliance = paddleaudio.compliance.librosa.melspectrogram(
+        feature_compliance = paddlespeech.audio.compliance.librosa.melspectrogram(
             x=self.waveform,
             sr=self.sr,
             window_size=self.n_fft,
@@ -166,10 +166,10 @@ class TestLibrosa(FeatTest):
             fmin=self.fmin,
             to_db=False)
 
-        # paddleaudio.features.layer
+        # paddlespeech.audio.features.layer
         x = paddle.to_tensor(
             self.waveform, dtype=paddle.float64).unsqueeze(0)  # Add batch dim.
-        feature_extractor = paddleaudio.features.MelSpectrogram(
+        feature_extractor = paddlespeech.audio.features.MelSpectrogram(
             sr=self.sr,
             n_fft=self.n_fft,
             hop_length=self.hop_length,
@@ -198,8 +198,8 @@ class TestLibrosa(FeatTest):
             fmin=self.fmin)
         feature_librosa = librosa.power_to_db(feature_librosa, top_db=None)
 
-        # paddleaudio.compliance.librosa:
+        # paddlespeech.audio.compliance.librosa:
-        feature_compliance = paddleaudio.compliance.librosa.melspectrogram(
+        feature_compliance = paddlespeech.audio.compliance.librosa.melspectrogram(
             x=self.waveform,
             sr=self.sr,
             window_size=self.n_fft,
@@ -207,10 +207,10 @@ class TestLibrosa(FeatTest):
             n_mels=self.n_mels,
             fmin=self.fmin)
 
-        # paddleaudio.features.layer
+        # paddlespeech.audio.features.layer
         x = paddle.to_tensor(
             self.waveform, dtype=paddle.float64).unsqueeze(0)  # Add batch dim.
-        feature_extractor = paddleaudio.features.LogMelSpectrogram(
+        feature_extractor = paddlespeech.audio.features.LogMelSpectrogram(
             sr=self.sr,
             n_fft=self.n_fft,
             hop_length=self.hop_length,
@@ -243,8 +243,8 @@ class TestLibrosa(FeatTest):
             n_mels=self.n_mels,
             fmin=self.fmin)
 
-        # paddleaudio.compliance.librosa:
+        # paddlespeech.audio.compliance.librosa:
-        feature_compliance = paddleaudio.compliance.librosa.mfcc(
+        feature_compliance = paddlespeech.audio.compliance.librosa.mfcc(
             x=self.waveform,
             sr=self.sr,
             n_mfcc=self.n_mfcc,
@@ -257,10 +257,10 @@ class TestLibrosa(FeatTest):
             fmin=self.fmin,
             top_db=self.top_db)
 
-        # paddleaudio.features.layer
+        # paddlespeech.audio.features.layer
         x = paddle.to_tensor(
             self.waveform, dtype=paddle.float64).unsqueeze(0)  # Add batch dim.
-        feature_extractor = paddleaudio.features.MFCC(
+        feature_extractor = paddlespeech.audio.features.MFCC(
             sr=self.sr,
             n_mfcc=self.n_mfcc,
             n_fft=self.n_fft,

tests/unit/audio/features/test_log_melspectrogram.py

@@ -15,8 +15,8 @@ import unittest
 
 import numpy as np
 import paddle
-import paddleaudio
 
+import paddlespeech.audio
 from .base import FeatTest
 from paddlespeech.s2t.transform.spectrogram import LogMelSpectrogram
 
@@ -33,8 +33,7 @@ class TestLogMelSpectrogram(FeatTest):
         ps_res = ps_melspect(self.waveform.T).squeeze(1).T
 
         x = paddle.to_tensor(self.waveform)
-        # paddlespeech.s2t的特征存在幅度谱和功率谱滥用的情况
+        ps_melspect = paddlespeech.audio.features.LogMelSpectrogram(
-        ps_melspect = paddleaudio.features.LogMelSpectrogram(
             self.sr,
             self.n_fft,
             self.hop_length,

tests/unit/audio/features/test_spectrogram.py

@@ -15,8 +15,8 @@ import unittest
 
 import numpy as np
 import paddle
-import paddleaudio
 
+import paddlespeech.audio
 from .base import FeatTest
 from paddlespeech.s2t.transform.spectrogram import Spectrogram
 
@@ -31,7 +31,7 @@ class TestSpectrogram(FeatTest):
         ps_res = ps_spect(self.waveform.T).squeeze(1).T  # Magnitude
 
         x = paddle.to_tensor(self.waveform)
-        pa_spect = paddleaudio.features.Spectrogram(
+        pa_spect = paddlespeech.audio.features.Spectrogram(
             self.n_fft, self.hop_length, power=1.0)
         pa_res = pa_spect(x).squeeze(0).numpy()
 

tests/unit/audio/features/test_stft.py

@@ -15,9 +15,9 @@ import unittest
 
 import numpy as np
 import paddle
-from paddleaudio.functional.window import get_window
 
 from .base import FeatTest
+from paddlespeech.audio.functional.window import get_window
 from paddlespeech.s2t.transform.spectrogram import Stft