diff --git a/egs/ksponspeech/ASR/local/__init__.py b/egs/ksponspeech/ASR/local/__init__.py
deleted file mode 100644
index e69de29bb2..0000000000
diff --git a/egs/ksponspeech/ASR/local/compute_fbank_musan.py b/egs/ksponspeech/ASR/local/compute_fbank_musan.py
deleted file mode 100755
index c0bdacfe51..0000000000
--- a/egs/ksponspeech/ASR/local/compute_fbank_musan.py
+++ /dev/null
@@ -1,158 +0,0 @@
-#!/usr/bin/env python3
-# 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 file computes fbank features of the musan dataset.
-It looks for manifests in the directory `src_dir` (default is data/manifests).
-
-The generated fbank features are saved in data/fbank.
-"""
-import argparse
-import logging
-import os
-from pathlib import Path
-
-import torch
-from lhotse import (
-    CutSet,
-    Fbank,
-    FbankConfig,
-    LilcomChunkyWriter,
-    MonoCut,
-    WhisperFbank,
-    WhisperFbankConfig,
-    combine,
-)
-from lhotse.recipes.utils import read_manifests_if_cached
-
-from icefall.utils import get_executor, str2bool
-
-# Torch's multithreaded behavior needs to be disabled or
-# it wastes a lot of CPU and slow things down.
-# Do this outside of main() in case it needs to take effect
-# even when we are not invoking the main (e.g. when spawning subprocesses).
-torch.set_num_threads(1)
-torch.set_num_interop_threads(1)
-
-
-def is_cut_long(c: MonoCut) -> bool:
-    return c.duration > 5
-
-
-def compute_fbank_musan(
-    src_dir: str = "data/manifests",
-    num_mel_bins: int = 80,
-    whisper_fbank: bool = False,
-    output_dir: str = "data/fbank",
-):
-    src_dir = Path(src_dir)
-    output_dir = Path(output_dir)
-    num_jobs = min(15, os.cpu_count())
-
-    dataset_parts = (
-        "music",
-        "speech",
-        "noise",
-    )
-    prefix = "musan"
-    suffix = "jsonl.gz"
-    manifests = read_manifests_if_cached(
-        dataset_parts=dataset_parts,
-        output_dir=src_dir,
-        prefix=prefix,
-        suffix=suffix,
-    )
-    assert manifests is not None
-
-    assert len(manifests) == len(dataset_parts), (
-        len(manifests),
-        len(dataset_parts),
-        list(manifests.keys()),
-        dataset_parts,
-    )
-
-    musan_cuts_path = output_dir / "musan_cuts.jsonl.gz"
-
-    if musan_cuts_path.is_file():
-        logging.info(f"{musan_cuts_path} already exists - skipping")
-        return
-
-    logging.info("Extracting features for Musan")
-
-    if whisper_fbank:
-        extractor = WhisperFbank(
-            WhisperFbankConfig(num_filters=num_mel_bins, device="cuda")
-        )
-    else:
-        extractor = Fbank(FbankConfig(num_mel_bins=num_mel_bins))
-
-    with get_executor() as ex:  # Initialize the executor only once.
-        # create chunks of Musan with duration 5 - 10 seconds
-        musan_cuts = (
-            CutSet.from_manifests(
-                recordings=combine(part["recordings"] for part in manifests.values())
-            )
-            .cut_into_windows(10.0)
-            .filter(is_cut_long)
-            .compute_and_store_features(
-                extractor=extractor,
-                storage_path=f"{output_dir}/musan_feats",
-                num_jobs=num_jobs if ex is None else 80,
-                executor=ex,
-                storage_type=LilcomChunkyWriter,
-            )
-        )
-        musan_cuts.to_file(musan_cuts_path)
-
-
-def get_args():
-    parser = argparse.ArgumentParser()
-    parser.add_argument(
-        "--src-dir",
-        type=str,
-        default="data/manifests",
-        help="Source manifests directory.",
-    )
-    parser.add_argument(
-        "--num-mel-bins",
-        type=int,
-        default=80,
-        help="""The number of mel bins for Fbank""",
-    )
-    parser.add_argument(
-        "--whisper-fbank",
-        type=str2bool,
-        default=False,
-        help="Use WhisperFbank instead of Fbank. Default: False.",
-    )
-    parser.add_argument(
-        "--output-dir",
-        type=str,
-        default="data/fbank",
-        help="Output directory. Default: data/fbank.",
-    )
-    return parser.parse_args()
-
-
-if __name__ == "__main__":
-    formatter = "%(asctime)s %(levelname)s [%(filename)s:%(lineno)d] %(message)s"
-
-    logging.basicConfig(format=formatter, level=logging.INFO)
-    args = get_args()
-    compute_fbank_musan(
-        src_dir=args.src_dir,
-        num_mel_bins=args.num_mel_bins,
-        whisper_fbank=args.whisper_fbank,
-        output_dir=args.output_dir,
-    )
diff --git a/egs/ksponspeech/ASR/local/compute_fbank_musan.py b/egs/ksponspeech/ASR/local/compute_fbank_musan.py
new file mode 120000
index 0000000000..5833f2484e
--- /dev/null
+++ b/egs/ksponspeech/ASR/local/compute_fbank_musan.py
@@ -0,0 +1 @@
+../../../librispeech/ASR/local/compute_fbank_musan.py
\ No newline at end of file
diff --git a/egs/ksponspeech/ASR/local/filter_cuts.py b/egs/ksponspeech/ASR/local/filter_cuts.py
deleted file mode 100644
index f081da5dfe..0000000000
--- a/egs/ksponspeech/ASR/local/filter_cuts.py
+++ /dev/null
@@ -1,157 +0,0 @@
-#!/usr/bin/env python3
-
-# 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 script removes short and long utterances from a cutset.
-
-Caution:
-  You may need to tune the thresholds for your own dataset.
-
-Usage example:
-
-  python3 ./local/filter_cuts.py \
-    --bpe-model data/lang_bpe_5000/bpe.model \
-    --in-cuts data/fbank/speechtools_cuts_test.jsonl.gz \
-    --out-cuts data/fbank-filtered/speechtools_cuts_test.jsonl.gz
-"""
-
-import argparse
-import logging
-from pathlib import Path
-
-import sentencepiece as spm
-from lhotse import CutSet, load_manifest_lazy
-from lhotse.cut import Cut
-
-
-def get_args():
-    parser = argparse.ArgumentParser()
-
-    parser.add_argument(
-        "--bpe-model",
-        type=Path,
-        help="Path to the bpe.model",
-    )
-
-    parser.add_argument(
-        "--in-cuts",
-        type=Path,
-        help="Path to the input cutset",
-    )
-
-    parser.add_argument(
-        "--out-cuts",
-        type=Path,
-        help="Path to the output cutset",
-    )
-
-    return parser.parse_args()
-
-
-def filter_cuts(cut_set: CutSet, sp: spm.SentencePieceProcessor):
-    total = 0  # number of total utterances before removal
-    removed = 0  # number of removed utterances
-
-    def remove_short_and_long_utterances(c: Cut):
-        """Return False to exclude the input cut"""
-        nonlocal removed, total
-        # Keep only utterances with duration between 1 second and 20 seconds
-        #
-        # Caution: There is a reason to select 20.0 here. Please see
-        # ./display_manifest_statistics.py
-        #
-        # You should use ./display_manifest_statistics.py to get
-        # an utterance duration distribution for your dataset to select
-        # the threshold
-        total += 1
-        if c.duration < 1.0 or c.duration > 20.0:
-            logging.warning(
-                f"Exclude cut with ID {c.id} from training. Duration: {c.duration}"
-            )
-            removed += 1
-            return False
-
-        # In pruned RNN-T, we require that T >= S
-        # where T is the number of feature frames after subsampling
-        # and S is the number of tokens in the utterance
-
-        # In ./pruned_transducer_stateless2/conformer.py, the
-        # conv module uses the following expression
-        # for subsampling
-        if c.num_frames is None:
-            num_frames = c.duration * 100  # approximate
-        else:
-            num_frames = c.num_frames
-
-        T = ((num_frames - 1) // 2 - 1) // 2
-        # Note: for ./lstm_transducer_stateless/lstm.py, the formula is
-        #  T = ((num_frames - 3) // 2 - 1) // 2
-
-        # Note: for ./pruned_transducer_stateless7/zipformer.py, the formula is
-        # T = ((num_frames - 7) // 2 + 1) // 2
-
-        tokens = sp.encode(c.supervisions[0].text, out_type=str)
-
-        if T < len(tokens):
-            logging.warning(
-                f"Exclude cut with ID {c.id} from training. "
-                f"Number of frames (before subsampling): {c.num_frames}. "
-                f"Number of frames (after subsampling): {T}. "
-                f"Text: {c.supervisions[0].text}. "
-                f"Tokens: {tokens}. "
-                f"Number of tokens: {len(tokens)}"
-            )
-            removed += 1
-            return False
-
-        return True
-
-    # We use to_eager() here so that we can print out the value of total
-    # and removed below.
-    ans = cut_set.filter(remove_short_and_long_utterances).to_eager()
-    ratio = removed / total * 100
-    logging.info(
-        f"Removed {removed} cuts from {total} cuts. {ratio:.3f}% data is removed."
-    )
-    return ans
-
-
-def main():
-    args = get_args()
-    logging.info(vars(args))
-
-    if args.out_cuts.is_file():
-        logging.info(f"{args.out_cuts} already exists - skipping")
-        return
-
-    assert args.in_cuts.is_file(), f"{args.in_cuts} does not exist"
-    assert args.bpe_model.is_file(), f"{args.bpe_model} does not exist"
-
-    sp = spm.SentencePieceProcessor()
-    sp.load(str(args.bpe_model))
-
-    cut_set = load_manifest_lazy(args.in_cuts)
-    assert isinstance(cut_set, CutSet)
-
-    cut_set = filter_cuts(cut_set, sp)
-    logging.info(f"Saving to {args.out_cuts}")
-    args.out_cuts.parent.mkdir(parents=True, exist_ok=True)
-    cut_set.to_file(args.out_cuts)
-
-
-if __name__ == "__main__":
-    formatter = "%(asctime)s %(levelname)s [%(filename)s:%(lineno)d] %(message)s"
-
-    logging.basicConfig(format=formatter, level=logging.INFO)
-
-    main()
diff --git a/egs/ksponspeech/ASR/local/filter_cuts.py b/egs/ksponspeech/ASR/local/filter_cuts.py
new file mode 120000
index 0000000000..27aca17293
--- /dev/null
+++ b/egs/ksponspeech/ASR/local/filter_cuts.py
@@ -0,0 +1 @@
+../../../librispeech/ASR/local/filter_cuts.py
\ No newline at end of file
diff --git a/egs/ksponspeech/ASR/local/train_bpe_model.py b/egs/ksponspeech/ASR/local/train_bpe_model.py
deleted file mode 100755
index 5979d5b986..0000000000
--- a/egs/ksponspeech/ASR/local/train_bpe_model.py
+++ /dev/null
@@ -1,115 +0,0 @@
-#!/usr/bin/env python3
-# Copyright    2021  Xiaomi Corp.        (authors: Fangjun Kuang)
-#
-# See ../../../../LICENSE for clarification regarding multiple authors
-#
-# 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.
-
-
-# You can install sentencepiece via:
-#
-#  pip install sentencepiece
-#
-# Due to an issue reported in
-# https://github.com/google/sentencepiece/pull/642#issuecomment-857972030
-#
-# Please install a version >=0.1.96
-
-import argparse
-import shutil
-from pathlib import Path
-from typing import Dict
-
-import sentencepiece as spm
-
-
-def get_args():
-    parser = argparse.ArgumentParser()
-    parser.add_argument(
-        "--lang-dir",
-        type=str,
-        help="""Input and output directory.
-        The generated bpe.model is saved to this directory.
-        """,
-    )
-
-    parser.add_argument(
-        "--transcript",
-        type=str,
-        help="Training transcript.",
-    )
-
-    parser.add_argument(
-        "--vocab-size",
-        type=int,
-        help="Vocabulary size for BPE training",
-    )
-
-    return parser.parse_args()
-
-
-def generate_tokens(lang_dir: Path):
-    """
-    Generate the tokens.txt from a bpe model.
-    """
-    sp = spm.SentencePieceProcessor()
-    sp.load(str(lang_dir / "bpe.model"))
-    token2id: Dict[str, int] = {sp.id_to_piece(i): i for i in range(sp.vocab_size())}
-    with open(lang_dir / "tokens.txt", "w", encoding="utf-8") as f:
-        for sym, i in token2id.items():
-            f.write(f"{sym} {i}\n")
-
-
-def main():
-    args = get_args()
-    vocab_size = args.vocab_size
-    lang_dir = Path(args.lang_dir)
-
-    model_type = "unigram"
-
-    model_prefix = f"{lang_dir}/{model_type}_{vocab_size}"
-    train_text = args.transcript
-    character_coverage = 1.0
-    input_sentence_size = 100000000
-
-    user_defined_symbols = ["<blk>", "<sos/eos>"]
-    unk_id = len(user_defined_symbols)
-    # Note: unk_id is fixed to 2.
-    # If you change it, you should also change other
-    # places that are using it.
-
-    model_file = Path(model_prefix + ".model")
-    if not model_file.is_file():
-        spm.SentencePieceTrainer.train(
-            input=train_text,
-            vocab_size=vocab_size,
-            model_type=model_type,
-            model_prefix=model_prefix,
-            input_sentence_size=input_sentence_size,
-            character_coverage=character_coverage,
-            user_defined_symbols=user_defined_symbols,
-            unk_id=unk_id,
-            bos_id=-1,
-            eos_id=-1,
-        )
-    else:
-        print(f"{model_file} exists - skipping")
-        return
-
-    shutil.copyfile(model_file, f"{lang_dir}/bpe.model")
-
-    generate_tokens(lang_dir)
-
-
-if __name__ == "__main__":
-    main()
diff --git a/egs/ksponspeech/ASR/local/train_bpe_model.py b/egs/ksponspeech/ASR/local/train_bpe_model.py
new file mode 120000
index 0000000000..6fad36421e
--- /dev/null
+++ b/egs/ksponspeech/ASR/local/train_bpe_model.py
@@ -0,0 +1 @@
+../../../librispeech/ASR/local/train_bpe_model.py
\ No newline at end of file
diff --git a/egs/ksponspeech/ASR/local/validate_manifest.py b/egs/ksponspeech/ASR/local/validate_manifest.py
deleted file mode 100755
index 98f2734196..0000000000
--- a/egs/ksponspeech/ASR/local/validate_manifest.py
+++ /dev/null
@@ -1,101 +0,0 @@
-#!/usr/bin/env python3
-# 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 script checks the following assumptions of the generated manifest:
-
-- Single supervision per cut
-- Supervision time bounds are within cut time bounds
-
-We will add more checks later if needed.
-
-Usage example:
-
-    python3 ./local/validate_manifest.py \
-            ./data/fbank/speechtools_cuts_train.jsonl.gz
-
-"""
-
-import argparse
-import logging
-from pathlib import Path
-
-from lhotse import CutSet, load_manifest_lazy
-from lhotse.cut import Cut
-from lhotse.dataset.speech_recognition import validate_for_asr
-
-
-def get_args():
-    parser = argparse.ArgumentParser()
-
-    parser.add_argument(
-        "manifest",
-        type=Path,
-        help="Path to the manifest file",
-    )
-
-    return parser.parse_args()
-
-
-def validate_one_supervision_per_cut(c: Cut):
-    if len(c.supervisions) != 1:
-        raise ValueError(f"{c.id} has {len(c.supervisions)} supervisions")
-
-
-def validate_supervision_and_cut_time_bounds(c: Cut):
-    tol = 2e-3  # same tolerance as in 'validate_for_asr()'
-    s = c.supervisions[0]
-
-    # Supervision start time is relative to Cut ...
-    # https://lhotse.readthedocs.io/en/v0.10_e/cuts.html
-    if s.start < -tol:
-        raise ValueError(
-            f"{c.id}: Supervision start time {s.start} must not be negative."
-        )
-    if s.start > tol:
-        raise ValueError(
-            f"{c.id}: Supervision start time {s.start} is not at the beginning of the Cut. Please apply `lhotse cut trim-to-supervisions`."
-        )
-    if c.start + s.end > c.end + tol:
-        raise ValueError(
-            f"{c.id}: Supervision end time {c.start+s.end} is larger "
-            f"than cut end time {c.end}"
-        )
-
-
-def main():
-    args = get_args()
-
-    manifest = args.manifest
-    logging.info(f"Validating {manifest}")
-
-    assert manifest.is_file(), f"{manifest} does not exist"
-    cut_set = load_manifest_lazy(manifest)
-    assert isinstance(cut_set, CutSet)
-
-    for c in cut_set:
-        validate_one_supervision_per_cut(c)
-        validate_supervision_and_cut_time_bounds(c)
-
-    # Validation from K2 training
-    # - checks supervision start is 0
-    # - checks supervision.duration is not longer than cut.duration
-    # - there is tolerance 2ms
-    validate_for_asr(cut_set)
-
-
-if __name__ == "__main__":
-    formatter = "%(asctime)s %(levelname)s [%(filename)s:%(lineno)d] %(message)s"
-
-    logging.basicConfig(format=formatter, level=logging.INFO)
-
-    main()
diff --git a/egs/ksponspeech/ASR/local/validate_manifest.py b/egs/ksponspeech/ASR/local/validate_manifest.py
new file mode 120000
index 0000000000..0a9725e876
--- /dev/null
+++ b/egs/ksponspeech/ASR/local/validate_manifest.py
@@ -0,0 +1 @@
+../../../librispeech/ASR/local/validate_manifest.py
\ No newline at end of file
diff --git a/egs/ksponspeech/ASR/zipformer/README.md b/egs/ksponspeech/ASR/zipformer/README.md
deleted file mode 100644
index c8c2104cdc..0000000000
--- a/egs/ksponspeech/ASR/zipformer/README.md
+++ /dev/null
@@ -1 +0,0 @@
-This recipe implements Zipformer model.