CSJ Data Preparation #617

teowenshen · 2022-10-13T10:48:52Z

Related to Lhotse #851, this pull request contains the data preparation codes for CSJ.

I have a pruned_transducer_stateless5 in another branch. If you prefer that the data preparation codes are merged together with the codes for the first model, I can send in another pull request.

Thanks!

Csj prepare

Change compute_fbank_musan.py to soft link

csukuangfj · 2022-10-13T11:51:34Z

@teowenshen

I think it is fine to first merge the data preparation part. It simplifies the review process (less code to review).

egs/csj/ASR/.vscode/launch.json

csukuangfj · 2022-10-13T11:52:40Z

egs/csj/ASR/local/compute_fbank_csj.py

@@ -0,0 +1,140 @@
+import argparse


Could you follow
https://k2-fsa.github.io/icefall/contributing/code-style.html
to fix your code style issues?

Thanks for the link. I have just done that.

There is one file where I declared a long list of variables. It seems black and flake8 can't agree on whether to add a newline.

To by-pass the check for some line, you can append # noqa at the end of that line. For instance

this_is_a_very_long_name = 1 # noqa

The above one is for flake8.

To also ignore that line for black, you can use

# fmt: off this_is_a_very_long_name = 1 # noqa # fmt: on

teowenshen · 2022-10-13T12:44:49Z

Before the commit, can I modify the existing license header from other codes to be placed on top of these codes?

csukuangfj · 2022-10-13T12:49:35Z

Before the commit, can I modify the existing license header from other codes to be placed on top of these codes?

If it is for the WSJ recipe, please feel free to do so.

If it is for other recipes, please do it in a separate PR to keep the changes of this PR minimum.

teowenshen · 2022-10-13T13:14:11Z

Great. I have added the headers.

I was thinking to put this pull request on hold until the Lhotse portion of the recipe is merged, since, if people clone it now the recipe will break at the Lhotse command. Would that be okay?

csukuangfj · 2022-10-13T13:30:40Z

Sounds good.

We can wait until it is merged on the lhotse side.

teowenshen · 2022-10-18T00:26:43Z

Hi, sorry for the long wait!

My last changes in Lhotse have passed and been merged.
I have changed the Icefall recipe to fit the changes in Lhotse too, so this branch should be ready to be considered to merge.

csukuangfj · 2022-10-18T02:10:27Z

egs/csj/ASR/local/compute_fbank_csj.py

+
+import torch
+from lhotse import (
+    ChunkedLilcomHdf5Writer,


Could you switch to LilcomChunkyWriter like the following one in librispeech?

icefall/egs/librispeech/ASR/local/compute_fbank_librispeech.py

Line 31 in d1f16a0

from lhotse import CutSet, Fbank, FbankConfig, LilcomChunkyWriter

Yes sure. Is there a reason why LilcomChunkyWriter is preferred?

I was thinking of including that in a comment.

From #404 (comment)

HDF5 unfortunately will cause issues to ‚big data’ users…

Also, please see lhotse-speech/lhotse#527

LilcomChunkyWriter does not depend on hdf5 -> one fewer dependency.

csukuangfj · 2022-10-18T02:12:08Z

egs/csj/ASR/local/compute_fbank_csj.py

+utterances into valid and train cutsets at an index which is by default 4000.
+
+In other words, the core+noncore utterances are shuffled, where 4000 utterances
+of the shuffled set go to the `valid` cutset and are not subjected to speed


Suggested change

of the shuffled set go to the `valid` cutset and are not subjected to speed

of the shuffled set go to the `valid` cutset and are not subject to speed

csukuangfj · 2022-10-18T02:17:03Z

egs/csj/ASR/local/compute_fbank_csj.py

+    else:
+        cut_sets = make_cutset_blueprints(args.manifest_dir, args.split)
+        for part, cut_set in cut_sets:
+            cut_set = cut_set.compute_and_store_features(


I suggest that we use

logging.info(f"Processing {part}")

to show some progress information.

csukuangfj · 2022-10-18T02:17:47Z

egs/csj/ASR/local/display_manifest_statistics.py

+    main()
+
+"""
+## train-clean-100


Could you update it for this dataset?

csukuangfj · 2022-10-18T02:22:27Z

egs/csj/ASR/local/prepare_lang_char.py

+"""
+
+
+def get_parser():


Suggested change

def get_parser():

def get_args():

I suggest using get_args as we return args from this function.

csukuangfj · 2022-10-18T02:25:42Z

egs/csj/ASR/local/prepare_lang_char.py

+        ),
+    )
+
+    parser.add_argument("--train-cut", type=Path, help="Path to the train cut")


Shall we add --required=True to it?

csukuangfj · 2022-10-18T02:30:49Z

egs/csj/ASR/local/prepare_lang_char.py

+    words = sorted(words)
+    words = ["<blk>"] + words + ["<unk>", "<sos/eos>"]
+
+    args.userdef_string += ["<blk>", "<unk>", "<sos/eos>"]


Should we put this assignment before we process the transcript?

Yes. I've moved the assignment of args.userdef_string up before processing the transcript.

csukuangfj · 2022-10-18T02:31:24Z

egs/csj/ASR/local/prepare_lang_char.py

+        args.lang_dir = Path(p)
+
+    if args.userdef_string:
+        args.userdef_string = args.userdef_string.read_text().split()


Using a set instead of a list for args.userdef_string is more efficient.

csukuangfj · 2022-10-18T02:36:27Z

egs/csj/ASR/prepare.sh

+    # Example: lhotse prepare csj $csj_dir $trans_dir $csj_manifest_dir -c local/conf/disfluent.ini
+    # NOTE: In case multiple config files are supplied, the second config file and onwards will inherit
+    #       the segment boundaries of the first config file. 
+    lhotse prepare csj $csj_dir $trans_dir $csj_manifest_dir -j 4


Shall we place a .done file inside $csj_manifest_dir/, like line 73 in this file?

csukuangfj · 2022-10-18T02:46:27Z

egs/csj/ASR/local/compute_fbank_csj.py

+
+import torch
+from lhotse import (
+    ChunkedLilcomHdf5Writer,


From #404 (comment)

HDF5 unfortunately will cause issues to ‚big data’ users…

csukuangfj · 2022-10-18T02:47:53Z

egs/csj/ASR/local/compute_fbank_csj.py

+
+import torch
+from lhotse import (
+    ChunkedLilcomHdf5Writer,


Also, please see lhotse-speech/lhotse#527

LilcomChunkyWriter does not depend on hdf5 -> one fewer dependency.

csukuangfj · 2022-10-18T02:53:47Z

Thanks! Left some minor comments.

Looks good to me.

csukuangfj · 2022-10-18T05:56:58Z

By the way, you can append # noqa to a line to ignore that line for style check.

teowenshen · 2022-10-18T06:43:51Z

Sorry, I met with this issue with my flake8 and was figuring out what went wrong.

black....................................................................Passed
flake8...................................................................Failed

hook id: flake8

exit code: 1

Traceback (most recent call last):
File "/root/.cache/pre-commit/repob48lv5kc/py_env-python3/bin/flake8", line 8, in
sys.exit(main())
File "/root/.cache/pre-commit/repob48lv5kc/py_env-python3/lib/python3.7/site-packages/flake8/main/cli.py", line 22, in main
app.run(argv)
File "/root/.cache/pre-commit/repob48lv5kc/py_env-python3/lib/python3.7/site-packages/flake8/main/application.py", line 363, in run
self._run(argv)
File "/root/.cache/pre-commit/repob48lv5kc/py_env-python3/lib/python3.7/site-packages/flake8/main/application.py", line 350, in _run
self.initialize(argv)
File "/root/.cache/pre-commit/repob48lv5kc/py_env-python3/lib/python3.7/site-packages/flake8/main/application.py", line 330, in initialize
self.find_plugins(config_finder)
File "/root/.cache/pre-commit/repob48lv5kc/py_env-python3/lib/python3.7/site-packages/flake8/main/application.py", line 153, in find_plugins
self.check_plugins = plugin_manager.Checkers(local_plugins.extension)
File "/root/.cache/pre-commit/repob48lv5kc/py_env-python3/lib/python3.7/site-packages/flake8/plugins/manager.py", line 357, in init
self.namespace, local_plugins=local_plugins
File "/root/.cache/pre-commit/repob48lv5kc/py_env-python3/lib/python3.7/site-packages/flake8/plugins/manager.py", line 238, in init
self._load_entrypoint_plugins()
File "/root/.cache/pre-commit/repob48lv5kc/py_env-python3/lib/python3.7/site-packages/flake8/plugins/manager.py", line 254, in _load_entrypoint_plugins
eps = importlib_metadata.entry_points().get(self.namespace, ())
AttributeError: 'EntryPoints' object has no attribute 'get'

Anyhow, I've passed the checks. Sorry for the multiple commits it took!

csukuangfj · 2022-10-18T07:56:08Z

Sorry, I met with this issue with my flake8 and was figuring out what went wrong.

I think this has something to do with Python 3.7. It should work for Python >= 3.8

Thanks! Merging.

teowenshen · 2022-10-18T08:29:39Z

Great. I will send in the codes for pruned_transducer_stateless5 soon.

) * Support running icefall outside of a git tracked directory. (k2-fsa#470) * Support running icefall outside of a git tracked directory. * Minor fixes. * Rand combine update result (k2-fsa#467) * update RESULTS.md * fix test code in pruned_transducer_stateless5/conformer.py * minor fix * delete doc * fix style * Simplified memory bank for Emformer (k2-fsa#440) * init files * use average value as memory vector for each chunk * change tail padding length from right_context_length to chunk_length * correct the files, ln -> cp * fix bug in conv_emformer_transducer_stateless2/emformer.py * fix doc in conv_emformer_transducer_stateless/emformer.py * refactor init states for stream * modify .flake8 * fix bug about memory mask when memory_size==0 * add @torch.jit.export for init_states function * update RESULTS.md * minor change * update README.md * modify doc * replace torch.div() with << * fix bug, >> -> << * use i&i-1 to judge if it is a power of 2 * minor fix * fix error in RESULTS.md * update multi_quantization installation (k2-fsa#469) * update multi_quantization installation * Update egs/librispeech/ASR/pruned_transducer_stateless6/train.py Co-authored-by: Fangjun Kuang <[email protected]> Co-authored-by: Fangjun Kuang <[email protected]> * [Ready] [Recipes] add aishell2 (k2-fsa#465) * add aishell2 * fix aishell2 * add manifest stats * update prepare char dict * fix lint * setting max duration * lint * change context size to 1 * update result * update hf link * fix decoding comment * add more decoding methods * update result * change context-size 2 default * [WIP] Rnn-T LM nbest rescoring (k2-fsa#471) * add compile_lg.py for aishell2 recipe (k2-fsa#481) * Add RNN-LM rescoring in fast beam search (k2-fsa#475) * fix for case of None stats * Update conformer.py for aishell4 (k2-fsa#484) * update conformer.py for aishell4 * update conformer.py * add strict=False when model.load_state_dict * CTC attention model with reworked Conformer encoder and reworked Transformer decoder (k2-fsa#462) * ctc attention model with reworked conformer encoder and reworked transformer decoder * remove unnecessary func * resolve flake8 conflicts * fix typos and modify the expr of ScaledEmbedding * use original beam size * minor changes to the scripts * add rnn lm decoding * minor changes * check whether q k v weight is None * check whether q k v weight is None * check whether q k v weight is None * style correction * update results * update results * upload the decoding results of rnn-lm to the RESULTS * upload the decoding results of rnn-lm to the RESULTS * Update egs/librispeech/ASR/RESULTS.md Co-authored-by: Fangjun Kuang <[email protected]> * Update egs/librispeech/ASR/RESULTS.md Co-authored-by: Fangjun Kuang <[email protected]> * Update egs/librispeech/ASR/RESULTS.md Co-authored-by: Fangjun Kuang <[email protected]> Co-authored-by: Fangjun Kuang <[email protected]> * Update doc to add a link to Nadira Povey's YouTube channel. (k2-fsa#492) * Update doc to add a link to Nadira Povey's YouTube channel. * fix a typo * Add stats about duration and padding proportion (k2-fsa#485) * add stats about duration and padding proportion * add for utt_duration * add stats for other recipes * add stats for other 2 recipes * modify doc * minor change * Add modified_beam_search for streaming decode (k2-fsa#489) * Add modified_beam_search for pruned_transducer_stateless/streaming_decode.py * refactor * modified beam search for stateless3,4 * Fix comments * Add real streamng ci * Fix using G before assignment in pruned_transducer_stateless/decode.py (k2-fsa#494) * Support using aidatatang_200zh optionally in aishell training (k2-fsa#495) * Use aidatatang_200zh optionally in aishell training. * Fix get_transducer_model() for aishell. (k2-fsa#497) PR k2-fsa#495 introduces an error. This commit fixes it. * [WIP] Pruned-transducer-stateless5-for-WenetSpeech (offline and streaming) (k2-fsa#447) * pruned-rnnt5-for-wenetspeech * style check * style check * add streaming conformer * add streaming decode * changes codes for fast_beam_search and export cpu jit * add modified-beam-search for streaming decoding * add modified-beam-search for streaming decoding * change for streaming_beam_search.py * add README.md and RESULTS.md * change for style_check.yml * do some changes * do some changes for export.py * add some decode commands for usage * add streaming results on README.md * [debug] raise remind when git-lfs not available (k2-fsa#504) * [debug] raise remind when git-lfs not available * modify comment * correction for prepare.sh (k2-fsa#506) * Set overwrite=True when extracting features in batches. (k2-fsa#487) * correction for get rank id. (k2-fsa#507) * Fix no attribute 'data' error. * minor fixes * correction for get rank id. * Add other decoding methods (nbest, nbest oracle, nbest LG) for wenetspeech pruned rnnt2 (k2-fsa#482) * add other decoding methods for wenetspeech * changes for RESULTS.md * add ngram-lm-scale=0.35 results * set ngram-lm-scale=0.35 as default * Update README.md * add nbest-scale for flie name * Support dynamic chunk streaming training in pruned_transcuder_stateless5 (k2-fsa#454) * support dynamic chunk streaming training * Add simulate streaming decoding * Support streaming decoding * fix causal * Minor fixes * fix streaming decode; add results * liear_fst_with_self_loops (k2-fsa#512) * Support exporting to ONNX format (k2-fsa#501) * WIP: Support exporting to ONNX format * Minor fixes. * Combine encoder/decoder/joiner into a single file. * Revert merging three onnx models into a single one. It's quite time consuming to extract a sub-graph from the combined model. For instance, it takes more than one hour to extract the encoder model. * Update CI to test ONNX models. * Decode with exported models. * Fix typos. * Add more doc. * Remove ncnn as it is not fully tested yet. * Fix as_strided for streaming conformer. * Convert ScaledEmbedding to nn.Embedding for inference. (k2-fsa#517) * Convert ScaledEmbedding to nn.Embedding for inference. * Fix CI style issues. * Fix preparing char based lang and add multiprocessing for wenetspeech text segmentation (k2-fsa#513) * add multiprocessing for wenetspeech text segmentation * Fix preparing char based lang for wenetspeech * fix style Co-authored-by: WeijiZhuang <[email protected]> * change for pruned rnnt5 train.py (k2-fsa#519) * fix about tensorboard (k2-fsa#516) * fix metricstracker * fix style * Merging onnx models (k2-fsa#518) * add export function of onnx-all-in-one to export.py * add onnx_check script for all-in-one onnx model * minor fix * remove unused arguments * add onnx-all-in-one test * fix style * fix style * fix requirements * fix input/output names * fix installing onnx_graphsurgeon * fix instaliing onnx_graphsurgeon * revert to previous requirements.txt * fix minor * Fix loading sampler state dict. (k2-fsa#421) * Fix loading sampler state dict. * skip scan_pessimistic_batches_for_oom if params.start_batch > 0 * fix torchaudio version (k2-fsa#524) * fix torchaudio version * fix torchaudio version * Fix computing averaged loss in the aishell recipe. (k2-fsa#523) * Fix computing averaged loss in the aishell recipe. * Set find_unused_parameters optionally. * Sort results to make it more convenient to compare decoding results (k2-fsa#522) * Sort result to make it more convenient to compare decoding results * Add cut_id to recognition results * add cut_id to results for all recipes * Fix torch.jit.script * Fix comments * Minor fixes * Fix torch.jit.tracing for Pytorch version before v1.9.0 * Add function display_and_save_batch in wenetspeech/pruned_transducer_stateless2/train.py (k2-fsa#528) * Add function display_and_save_batch in egs/wenetspeech/ASR/pruned_transducer_stateless2/train.py * Modify function: display_and_save_batch * Delete empty line in pruned_transducer_stateless2/train.py * Modify code format * Filter non-finite losses (k2-fsa#525) * Filter non-finite losses * Fixes after review * propagate changes from k2-fsa#525 to other librispeech recipes (k2-fsa#531) * propaga changes from k2-fsa#525 to other librispeech recipes * refactor display_and_save_batch to utils * fixed typo * reformat code style * Fix not enough values to unpack error . (k2-fsa#533) * Use ScaledLSTM as streaming encoder (k2-fsa#479) * add ScaledLSTM * add RNNEncoderLayer and RNNEncoder classes in lstm.py * add RNN and Conv2dSubsampling classes in lstm.py * hardcode bidirectional=False * link from pruned_transducer_stateless2 * link scaling.py pruned_transducer_stateless2 * copy from pruned_transducer_stateless2 * modify decode.py pretrained.py test_model.py train.py * copy streaming decoding files from pruned_transducer_stateless2 * modify streaming decoding files * simplified code in ScaledLSTM * flat weights after scaling * pruned2 -> pruned4 * link __init__.py * fix style * remove add_model_arguments * modify .flake8 * fix style * fix scale value in scaling.py * add random combiner for training deeper model * add using proj_size * add scaling converter for ScaledLSTM * support jit trace * add using averaged model in export.py * modify test_model.py, test if the model can be successfully exported by jit.trace * modify pretrained.py * support streaming decoding * fix model.py * Add cut_id to recognition results * Add cut_id to recognition results * do not pad in Conv subsampling module; add tail padding during decoding. * update RESULTS.md * minor fix * fix doc * update README.md * minor change, filter infinite loss * remove the condition of raise error * modify type hint for the return value in model.py * minor change * modify RESULTS.md Co-authored-by: pkufool <[email protected]> * Update asr_datamodule.py (k2-fsa#538) minor file names correction * minor fixes to LSTM streaming model (k2-fsa#537) * Pruned transducer stateless2 for AISHELL-1 (k2-fsa#536) * Fix not enough values to unpack error . * [WIP] Pruned transducer stateless2 for AISHELL-1 * fix the style issue * code format for black * add pruned-transducer-stateless2 results for AISHELL-1 * simplify result * consider case of empty tensor (k2-fsa#540) * fixed import quantization is none (k2-fsa#541) Signed-off-by: shanguanma <[email protected]> Signed-off-by: shanguanma <[email protected]> Co-authored-by: shanguanma <[email protected]> * fix typo for export jit script (k2-fsa#544) * some small changes for aidatatang_200zh (k2-fsa#542) * Update prepare.sh * Update compute_fbank_aidatatang_200zh.py * fixed no cut_id error in decode_dataset (k2-fsa#549) * fixed import quantization is none Signed-off-by: shanguanma <[email protected]> * fixed no cut_id error in decode_dataset Signed-off-by: shanguanma <[email protected]> * fixed more than one "#" Signed-off-by: shanguanma <[email protected]> * fixed code style Signed-off-by: shanguanma <[email protected]> Signed-off-by: shanguanma <[email protected]> Co-authored-by: shanguanma <[email protected]> * Add clamping operation in Eve optimizer for all scalar weights to avoid (k2-fsa#550) non stable training in some scenarios. The clamping range is set to (-10,2). Note that this change may cause unexpected effect if you resume training from a model that is trained without clamping. * minor changes for correct path names && import module text2segments.py (k2-fsa#552) * Update asr_datamodule.py minor file names correction * minor changes for correct path names && import module text2segments.py * fix scaling converter test for decoder(predictor). (k2-fsa#553) * Disable CUDA_LAUNCH_BLOCKING in wenetspeech recipes. (k2-fsa#554) * Disable CUDA_LAUNCH_BLOCKING in wenetspeech recipes. * minor fixes * Check that read_manifests_if_cached returns a non-empty dict. (k2-fsa#555) * Modified prepare_transcripts.py and preprare_lexicon.py of tedlium3 recipe (k2-fsa#567) * Use modified ctc topo when vocab size is > 500 (k2-fsa#568) * Add LSTM for the multi-dataset setup. (k2-fsa#558) * Add LSTM for the multi-dataset setup. * Add results * fix style issues * add missing file * Adding Dockerfile for Ubuntu18.04-pytorch1.12.1-cuda11.3-cudnn8 (k2-fsa#572) * Changed Dockerfile * Update Dockerfile * Dockerfile * Update README.md * Add Dockerfiles * Update README.md Removed misleading CUDA version, as the Ubuntu18.04-pytorch1.7.1-cuda11.0-cudnn8 Dockerfile can only support CUDA versions >11.0. * support exporting to ncnn format via PNNX (k2-fsa#571) * Small fixes to the transducer training doc (k2-fsa#575) * Update kaldifeat in CI tests (k2-fsa#583) * padding zeros (k2-fsa#591) * Gradient filter for training lstm model (k2-fsa#564) * init files * add gradient filter module * refact getting median value * add cutoff for grad filter * delete comments * apply gradient filter in LSTM module, to filter both input and params * fix typing and refactor * filter with soft mask * rename lstm_transducer_stateless2 to lstm_transducer_stateless3 * fix typos, and update RESULTS.md * minor fix * fix return typing * fix typo * Modified train.py of tedlium3 models (k2-fsa#597) * Add dill to requirements.txt (k2-fsa#613) * Add dill to requirements.txt * Disable style check for python 3.7 * update docs (k2-fsa#611) * update docs Co-authored-by: unknown <[email protected]> Co-authored-by: KajiMaCN <[email protected]> * exporting projection layers of joiner separately for onnx (k2-fsa#584) * exporting projection layers of joiner separately for onnx * Remove all-in-one for onnx export (k2-fsa#614) * Remove all-in-one for onnx export * Exit on error for CI * Modify ActivationBalancer for speed (k2-fsa#612) * add a probability to apply ActivationBalancer * minor fix * minor fix * Support exporting to ONNX for the wenetspeech recipe (k2-fsa#615) * Support exporting to ONNX for the wenetspeech recipe * Add doc about model export (k2-fsa#618) * Add doc about model export * fix typos * Fix links in the doc (k2-fsa#619) * fix type hints for decode.py (k2-fsa#623) * Support exporting LSTM with projection to ONNX (k2-fsa#621) * Support exporting LSTM with projection to ONNX * Add missing files * small fixes * CSJ Data Preparation (k2-fsa#617) * workspace setup * csj prepare done * Change compute_fbank_musan.py t soft link * add description * change lhotse prepare csj command * split train-dev here * Add header * remove debug * save manifest_statistics * generate transcript in Lhotse * update comments in config file * fix number of parameters in RESULTS.md (k2-fsa#627) * Add Shallow fusion in modified_beam_search (k2-fsa#630) * Add utility for shallow fusion * test batch size == 1 without shallow fusion * Use shallow fusion for modified-beam-search * Modified beam search with ngram rescoring * Fix code according to review Co-authored-by: Fangjun Kuang <[email protected]> * Add kaldifst to requirements.txt (k2-fsa#631) * Install kaldifst for GitHub actions (k2-fsa#632) * Install kaldifst for GitHub actions * Update train.py (k2-fsa#635) Add the missing step to add the arguments to the parser. * Fix type hints for decode.py (k2-fsa#638) * Fix type hints for decode.py * Fix flake8 * fix typos (k2-fsa#639) * Remove onnx and onnxruntime from requirements.txt (k2-fsa#640) * Remove onnx and onnxruntime from requirements.txt * Checkout the LM for aishell explicitly (k2-fsa#642) * Get timestamps during decoding (k2-fsa#598) * print out timestamps during decoding * add word-level alignments * support to compute mean symbol delay with word-level alignments * print variance of symbol delay * update doc * support to compute delay for pruned_transducer_stateless4 * fix bug * add doc * remove tail padding for non-streaming models (k2-fsa#625) * support RNNLM shallow fusion for LSTM transducer * support RNNLM shallow fusion in stateless5 * update results * update decoding commands * update author info * update * include previous added decoding method * minor fixes * remove redundant test lines * Update egs/librispeech/ASR/lstm_transducer_stateless2/decode.py Co-authored-by: Fangjun Kuang <[email protected]> * Update tdnn_lstm_ctc.rst (k2-fsa#647) * Update README.md (k2-fsa#649) * Update tdnn_lstm_ctc.rst (k2-fsa#648) * fix torchaudio version in dockerfile (k2-fsa#653) * fix torchaudio version in dockerfile * remove kaldiio * update docs * Add fast_beam_search_LG (k2-fsa#622) * Add fast_beam_search_LG * add fast_beam_search_LG to commonly used recipes * fix ci * fix ci * Fix error * Fix LG log file name (k2-fsa#657) * resolve conflict with timestamp feature * resolve conflicts * minor fixes * remove testing file * Apply delay penalty on transducer (k2-fsa#654) * add delay penalty * fix CI * fix CI * Refactor getting timestamps in fsa-based decoding (k2-fsa#660) * refactor getting timestamps for fsa-based decoding * fix doc * fix bug * add ctc_decode.py * fix doc Signed-off-by: shanguanma <[email protected]> Co-authored-by: Fangjun Kuang <[email protected]> Co-authored-by: LIyong.Guo <[email protected]> Co-authored-by: Yuekai Zhang <[email protected]> Co-authored-by: ezerhouni <[email protected]> Co-authored-by: Mingshuang Luo <[email protected]> Co-authored-by: Daniel Povey <[email protected]> Co-authored-by: Quandwang <[email protected]> Co-authored-by: Wei Kang <[email protected]> Co-authored-by: boji123 <[email protected]> Co-authored-by: Lucky Wong <[email protected]> Co-authored-by: LIyong.Guo <[email protected]> Co-authored-by: Weiji Zhuang <[email protected]> Co-authored-by: WeijiZhuang <[email protected]> Co-authored-by: Yunusemre <[email protected]> Co-authored-by: FNLPprojects <[email protected]> Co-authored-by: yangsuxia <[email protected]> Co-authored-by: marcoyang1998 <[email protected]> Co-authored-by: rickychanhoyin <[email protected]> Co-authored-by: Duo Ma <[email protected]> Co-authored-by: shanguanma <[email protected]> Co-authored-by: rxhmdia <[email protected]> Co-authored-by: kobenaxie <[email protected]> Co-authored-by: shcxlee <[email protected]> Co-authored-by: Teo Wen Shen <[email protected]> Co-authored-by: KajiMaCN <[email protected]> Co-authored-by: unknown <[email protected]> Co-authored-by: KajiMaCN <[email protected]> Co-authored-by: Yunusemre <[email protected]> Co-authored-by: Nagendra Goel <[email protected]> Co-authored-by: marcoyang <[email protected]> Co-authored-by: zr_jin <[email protected]>

teowenshen and others added 8 commits October 8, 2022 19:42

workspace setup

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csj prepare done

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Merge pull request #1 from Minami-Lab-UEC/csj_prepare

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Csj prepare

Change compute_fbank_musan.py t soft link

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Merge pull request #2 from Minami-Lab-UEC/csj_prepare

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Change compute_fbank_musan.py to soft link

add description

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change lhotse prepare csj command

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split train-dev here

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teowenshen changed the title ~~Data preparation stage~~ CSJ Data Preparation Oct 13, 2022

check lint

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csukuangfj reviewed Oct 13, 2022

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Fix style

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teowenshen added 3 commits October 14, 2022 15:56

remove debug

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save manifest_statistics

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generate transcript in Lhotse

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update comments in config file

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csukuangfj reviewed Oct 18, 2022

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teowenshen added 2 commits October 18, 2022 14:04

minor fixes

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csukuangfj merged commit 15c1a4a into k2-fsa:master Oct 18, 2022

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CSJ Data Preparation #617

CSJ Data Preparation #617

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	of the shuffled set go to the `valid` cutset and are not subjected to speed
	of the shuffled set go to the `valid` cutset and are not subject to speed

CSJ Data Preparation #617

CSJ Data Preparation #617

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csukuangfj commented Oct 18, 2022

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