diff --git a/examples/use_mfa/local/detect_oov.py b/examples/use_mfa/local/detect_oov.py
deleted file mode 100644
index f5ae728..0000000
--- a/examples/use_mfa/local/detect_oov.py
+++ /dev/null
@@ -1,48 +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 argparse
-from collections import OrderedDict
-from pathlib import Path
-import logging
-
-
-def detect_oov(corpus_dir, lexicon_path, transcription_pattern="*.lab"):
-    corpus_dir = Path(corpus_dir)
-
-    lexicon = OrderedDict()
-    with open(lexicon_path, 'rt') as f:
-        for line in f:
-            syllable, phonemes = line.split(maxsplit=1)
-            lexicon[syllable] = phonemes
-
-    for fp in corpus_dir.glob(transcription_pattern):
-        syllables = fp.read_text().strip().split()
-        for s in syllables:
-            if s not in lexicon:
-                logging.warning(f"{fp.relative_to(corpus_dir)} has OOV {s} .")
-
-
-if __name__ == "__main__":
-    parser = argparse.ArgumentParser(
-        description="detect oov in a corpus given a lexicon")
-    parser.add_argument(
-        "corpus_dir", type=str, help="corpus dir for MFA alignment.")
-    parser.add_argument("lexicon_path", type=str, help="dictionary to use.")
-    parser.add_argument(
-        "--pattern", type=str, default="*.lab", help="dictionary to use.")
-    args = parser.parse_args()
-    print(args)
-
-    detect_oov(args.corpus_dir, args.lexicon_path, args.pattern)
diff --git a/examples/use_mfa/local/generate_lexicon.py b/examples/use_mfa/local/generate_lexicon.py
deleted file mode 100644
index 1791e7b..0000000
--- a/examples/use_mfa/local/generate_lexicon.py
+++ /dev/null
@@ -1,199 +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.
-"""Generate lexicon and symbols for Mandarin Chinese phonology.
-The lexicon is used for Montreal Force Aligner.
-
-Note that syllables are used as word in this lexicon. Since syllables rather 
-than words are used in transcriptions produced by `reorganize_baker.py`.
-
-We make this choice to better leverage other software for chinese text to 
-pinyin tools like pypinyin. This is the convention for G2P in Chinese.
-"""
-
-import re
-import argparse
-from collections import OrderedDict
-
-INITIALS = [
-    'b', 'p', 'm', 'f', 'd', 't', 'n', 'l', 'g', 'k', 'h', 'zh', 'ch', 'sh',
-    'r', 'z', 'c', 's', 'j', 'q', 'x'
-]
-
-FINALS = [
-    'a', 'ai', 'ao', 'an', 'ang', 'e', 'er', 'ei', 'en', 'eng', 'o', 'ou',
-    'ong', 'ii', 'iii', 'i', 'ia', 'iao', 'ian', 'iang', 'ie', 'io', 'iou',
-    'iong', 'in', 'ing', 'u', 'ua', 'uai', 'uan', 'uang', 'uei', 'uo', 'uen',
-    'ueng', 'v', 've', 'van', 'vn'
-]
-
-SPECIALS = ['sil', 'sp']
-
-
-def rule(C, V, R, T):
-    """Generate a syllable given the initial, the final, erhua indicator, and tone.
-    Orthographical rules for pinyin are applied. (special case for y, w, ui, un, iu)
-    
-    Note that in this system, 'ü' is alway written as 'v' when appeared in phoneme, but converted to 
-    'u' in syllables when certain conditions are satisfied.
-    
-    'i' is distinguished when appeared in phonemes, and separated into 3 categories, 'i', 'ii' and 'iii'.
-
-    Erhua is is possibly applied to every finals, except for finals that already ends with 'r'.
-
-    When a syllable is impossible or does not have any characters with this pronunciation, return None
-    to filter it out.
-    """
-
-    # 不可拼的音节, ii 只能和 z, c, s 拼
-    if V in ["ii"] and (C not in ['z', 'c', 's']):
-        return None
-    # iii 只能和 zh, ch, sh, r 拼
-    if V in ['iii'] and (C not in ['zh', 'ch', 'sh', 'r']):
-        return None
-
-    # 齐齿呼或者撮口呼不能和 f, g, k, h, zh, ch, sh, r, z, c, s
-    if (V not in ['ii', 'iii']) and V[0] in ['i', 'v'] and (
-            C in ['f', 'g', 'k', 'h', 'zh', 'ch', 'sh', 'r', 'z', 'c', 's']):
-        return None
-
-    # 撮口呼只能和 j, q, x l, n 拼
-    if V.startswith("v"):
-        # v, ve 只能和 j ,q , x, n, l 拼
-        if V in ['v', 've']:
-            if C not in ['j', 'q', 'x', 'n', 'l', '']:
-                return None
-        # 其他只能和 j, q, x 拼
-        else:
-            if C not in ['j', 'q', 'x', '']:
-                return None
-
-    # j, q, x 只能和齐齿呼或者撮口呼拼
-    if (C in ['j', 'q', 'x']) and not (
-        (V not in ['ii', 'iii']) and V[0] in ['i', 'v']):
-        return None
-
-    # b, p ,m, f 不能和合口呼拼，除了 u 之外
-    # bm p, m, f 不能和撮口呼拼
-    if (C in ['b', 'p', 'm', 'f']) and ((V[0] in ['u', 'v'] and V != "u") or
-                                        V == 'ong'):
-        return None
-
-    # ua, uai, uang 不能和 d, t, n, l, r, z, c, s 拼
-    if V in ['ua', 'uai', 'uang'
-             ] and C in ['d', 't', 'n', 'l', 'r', 'z', 'c', 's']:
-        return None
-
-    # sh 和 ong 不能拼
-    if V == 'ong' and C in ['sh']:
-        return None
-
-    # o 和 gkh, zh ch sh r z c s 不能拼
-    if V == "o" and C in [
-            'd', 't', 'n', 'g', 'k', 'h', 'zh', 'ch', 'sh', 'r', 'z', 'c', 's'
-    ]:
-        return None
-
-    # ueng 只是 weng 这个 ad-hoc 其他情况下都是 ong
-    if V == 'ueng' and C != '':
-        return
-
-    # 非儿化的 er 只能单独存在
-    if V == 'er' and C != '':
-        return None
-
-    if C == '':
-        if V in ["i", "in", "ing"]:
-            C = 'y'
-        elif V == 'u':
-            C = 'w'
-        elif V.startswith('i') and V not in ["ii", "iii"]:
-            C = 'y'
-            V = V[1:]
-        elif V.startswith('u'):
-            C = 'w'
-            V = V[1:]
-        elif V.startswith('v'):
-            C = 'yu'
-            V = V[1:]
-    else:
-        if C in ['j', 'q', 'x']:
-            if V.startswith('v'):
-                V = re.sub('v', 'u', V)
-        if V == 'iou':
-            V = 'iu'
-        elif V == 'uei':
-            V = 'ui'
-        elif V == 'uen':
-            V = 'un'
-    result = C + V
-
-    # Filter  er 不能再儿化
-    if result.endswith('r') and R == 'r':
-        return None
-
-    # ii and iii, change back to i
-    result = re.sub(r'i+', 'i', result)
-
-    result = result + R + T
-    return result
-
-
-def generate_lexicon(with_tone=False, with_erhua=False):
-    """Generate lexicon for Mandarin Chinese."""
-    syllables = OrderedDict()
-
-    for C in [''] + INITIALS:
-        for V in FINALS:
-            for R in [''] if not with_erhua else ['', 'r']:
-                for T in [''] if not with_tone else ['1', '2', '3', '4', '5']:
-                    result = rule(C, V, R, T)
-                    if result:
-                        syllables[result] = f'{C} {V}{R}{T}'
-    return syllables
-
-
-def generate_symbols(lexicon):
-    """Generate phoneme list for a lexicon."""
-    symbols = set()
-    for p in SPECIALS:
-        symbols.add(p)
-    for syllable, phonemes in lexicon.items():
-        phonemes = phonemes.split()
-        for p in phonemes:
-            symbols.add(p)
-    return sorted(list(symbols))
-
-
-if __name__ == "__main__":
-    parser = argparse.ArgumentParser(
-        description="Generate lexicon for Chinese pinyin to phoneme for MFA")
-    parser.add_argument("output", type=str, help="Path to save lexicon.")
-    parser.add_argument(
-        "--with-tone", action="store_true", help="whether to consider tone.")
-    parser.add_argument(
-        "--with-r", action="store_true", help="whether to consider erhua.")
-    args = parser.parse_args()
-
-    lexicon = generate_lexicon(args.with_tone, args.with_r)
-    symbols = generate_symbols(lexicon)
-
-    with open(args.output + ".lexicon", 'wt') as f:
-        for k, v in lexicon.items():
-            f.write(f"{k} {v}\n")
-
-    with open(args.output + ".symbols", 'wt') as f:
-        for s in symbols:
-            f.write(s + "\n")
-
-    print("Done!")
diff --git a/examples/use_mfa/local/reorganize_baker.py b/examples/use_mfa/local/reorganize_baker.py
deleted file mode 100644
index fb41751..0000000
--- a/examples/use_mfa/local/reorganize_baker.py
+++ /dev/null
@@ -1,113 +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.
-"""Script to reorganize Baker dataset so as to use Montreal Force
-Aligner to align transcription and audio.
-
-Please refer to https://montreal-forced-aligner.readthedocs.io/en/latest/data_prep.html
-for more details about Montreal Force Aligner's requirements on cotpus.
-
-For scripts to reorganize other corpus, please refer to 
- https://github.com/MontrealCorpusTools/MFA-reorganization-scripts
-for more details.
-"""
-
-import os
-import shutil
-import argparse
-from typing import Union
-from pathlib import Path
-from concurrent.futures import ThreadPoolExecutor
-
-import librosa
-import soundfile as sf
-from tqdm import tqdm
-
-
-def get_transcripts(path: Union[str, Path]):
-    transcripts = {}
-
-    with open(path) as f:
-        lines = f.readlines()
-
-    for i in range(0, len(lines), 2):
-        sentence_id = lines[i].split()[0]
-        transcription = lines[i + 1].strip()
-        # tones are dropped here
-        # since the lexicon does not consider tones, too
-        transcription = " ".join([item[:-1] for item in transcription.split()])
-        transcripts[sentence_id] = transcription
-
-    return transcripts
-
-
-def resample_and_save(source, target, sr=16000):
-    wav, _ = librosa.load(str(source), sr=sr)
-    sf.write(str(target), wav, samplerate=sr, subtype='PCM_16')
-    return target
-
-
-def reorganize_baker(root_dir: Union[str, Path],
-                     output_dir: Union[str, Path]=None,
-                     resample_audio=False):
-    root_dir = Path(root_dir).expanduser()
-    transcript_path = root_dir / "ProsodyLabeling" / "000001-010000.txt"
-    transcriptions = get_transcripts(transcript_path)
-
-    wave_dir = root_dir / "Wave"
-    wav_paths = sorted(list(wave_dir.glob("*.wav")))
-    output_dir = Path(output_dir).expanduser()
-    assert wave_dir != output_dir, "Don't use an the original wav's directory as output_dir"
-
-    output_dir.mkdir(parents=True, exist_ok=True)
-
-    if resample_audio:
-        with ThreadPoolExecutor(os.cpu_count()) as pool:
-            with tqdm(total=len(wav_paths), desc="resampling") as pbar:
-                futures = []
-                for wav_path in wav_paths:
-                    future = pool.submit(resample_and_save, wav_path,
-                                         output_dir / wav_path.name)
-                    future.add_done_callback(lambda p: pbar.update())
-                    futures.append(future)
-
-                results = []
-                for ft in futures:
-                    results.append(ft.result())
-    else:
-        for wav_path in tqdm(wav_paths, desc="copying"):
-            shutil.copyfile(wav_path, output_dir / wav_path.name)
-
-    for sentence_id, transcript in tqdm(
-            transcriptions.items(), desc="transcription process"):
-        with open(output_dir / (sentence_id + ".lab"), 'wt') as f:
-            f.write(transcript)
-            f.write('\n')
-    print("Done!")
-
-
-if __name__ == "__main__":
-    parser = argparse.ArgumentParser(
-        description="Reorganize Baker dataset for MFA")
-    parser.add_argument("--root-dir", type=str, help="path to baker dataset.")
-    parser.add_argument(
-        "--output-dir",
-        type=str,
-        help="path to save outputs(audio and transcriptions)")
-    parser.add_argument(
-        "--resample-audio",
-        action="store_true",
-        help="To resample audio files or just copy them")
-    args = parser.parse_args()
-
-    reorganize_baker(args.root_dir, args.output_dir, args.resample_audio)
diff --git a/examples/use_mfa/run.sh b/examples/use_mfa/run.sh
deleted file mode 100644
index c339408..0000000
--- a/examples/use_mfa/run.sh
+++ /dev/null
@@ -1,49 +0,0 @@
-EXP_DIR=exp
-
-mkdir -p $EXP_DIR
-LEXICON_NAME='simple'
-if [ ! -f "$EXP_DIR/$LEXICON_NAME.lexicon" ]; then
-    echo "generating lexicon..."
-    python local/generate_lexicon.py "$EXP_DIR/$LEXICON_NAME" --with-r
-    echo "lexicon done"
-fi
-
-if [ ! -d $EXP_DIR/baker_corpus ]; then
-    echo "reorganizing baker corpus..."
-    python local/recorganize_baker.py --root-dir=~/datasets/BZNSYP --output-dir=$EXP_DIR/baker_corpus --resample-audio
-    echo "reorganization done. Check output in $EXP_DIR/baker_corpus."
-    echo "audio files are resampled to 16kHz"
-    echo "transcription for each audio file is saved with the same namd in $EXP_DIR/baker_corpus "
-fi
-
-echo "detecting oov..."
-python local/detect_oov.py $EXP_DIR/baker_corpus $EXP_DIR/"$LEXICON_NAME.lexicon"
-echo "detecting oov done. you may consider regenerate lexicon if there is unexpected OOVs."
-
-
-MFA_DOWNLOAD_DIR=local/
-
-if [ ! -f "$MFA_DOWNLOAD_DIR/montreal-forced-aligner_linux.tar.gz" ]; then
-    echo "downloading mfa..."
-    (cd $MFA_DOWNLOAD_DIR && wget https://github.com/MontrealCorpusTools/Montreal-Forced-Aligner/releases/download/v1.0.1/montreal-forced-aligner_linux.tar.gz)
-    echo "download mfa done!"
-fi
-
-if [ ! -d "$MFA_DOWNLOAD_DIR/montreal-forced-aligner" ]; then
-    echo "extracting mfa..."
-    (cd $MFA_DOWNLOAD_DIR && tar xvf "montreal-forced-aligner_linux.tar.gz")
-    echo "extraction done!"
-fi
-
-export PATH="$MFA_DOWNLOAD_DIR/montreal-forced-aligner/bin"
-if [ ! -d "$EXP_DIR/baker_alignment" ]; then
-    echo "Start MFA training..."
-    mfa_train_and_align $EXP_DIR/baker_corpus "$EXP_DIR/$LEXICON_NAME.lexicon" $EXP_DIR/baker_alignment -o $EXP_DIR/baker_model --clean --verbose --temp_directory exp/.mfa_train_and_align
-    echo "training done!"
-    echo "results: $EXP_DIR/baker_alignment"
-    echo "model: $EXP_DIR/baker_model"
-fi
-
-
-
-