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* Init commit for recipes trained on multiple zh datasets. * fbank extraction for thchs30 * added support for aishell1 * added support for aishell-2 * fixes * fixes * fixes * added support for stcmds and primewords * fixes * added support for magicdata script for fbank computation not done yet * added script for magicdata fbank computation * file permission fixed * updated for the wenetspeech recipe * updated * Update preprocess_kespeech.py * updated * updated * updated * updated * file permission fixed * updated paths * fixes * added support for kespeech dev/test set fbank computation * fixes for file permission * refined support for KeSpeech * added scripts for BPE model training * updated * init commit for the multi_zh-cn zipformer recipe * disable speed perturbation by default * updated * updated * added necessary files for the zipformer recipe * removed redundant wenetspeech M and S sets * updates for multi dataset decoding * refined * formatting issues fixed * updated * minor fixes * this commit finalize the recipe (hopefully) * fixed formatting issues * minor fixes * updated * using soft links to reduce redundancy * minor updates * using soft links to reduce redundancy * minor updates * minor updates * using soft links to reduce redundancy * minor updates * Update README.md * minor updates * Update egs/multi_zh-hans/ASR/local/compute_fbank_magicdata.py Co-authored-by: Fangjun Kuang <csukuangfj@gmail.com> * Update egs/multi_zh-hans/ASR/local/compute_fbank_magicdata.py Co-authored-by: Fangjun Kuang <csukuangfj@gmail.com> * Update egs/multi_zh-hans/ASR/local/compute_fbank_stcmds.py Co-authored-by: Fangjun Kuang <csukuangfj@gmail.com> * Update egs/multi_zh-hans/ASR/local/compute_fbank_stcmds.py Co-authored-by: Fangjun Kuang <csukuangfj@gmail.com> * Update egs/multi_zh-hans/ASR/local/compute_fbank_primewords.py Co-authored-by: Fangjun Kuang <csukuangfj@gmail.com> * Update egs/multi_zh-hans/ASR/local/compute_fbank_primewords.py Co-authored-by: Fangjun Kuang <csukuangfj@gmail.com> * minor updates * minor fixes * fixed a formatting issue * Update preprocess_kespeech.py * Update prepare.sh * Update egs/multi_zh-hans/ASR/local/compute_fbank_kespeech_splits.py Co-authored-by: Fangjun Kuang <csukuangfj@gmail.com> * Update egs/multi_zh-hans/ASR/local/preprocess_kespeech.py Co-authored-by: Fangjun Kuang <csukuangfj@gmail.com> * removed redundant files * symlinks added * minor updates * added CI tests for `multi_zh-hans` * minor fixes * Update run-multi-zh_hans-zipformer.sh * Update run-multi-zh_hans-zipformer.sh * Update run-multi-zh_hans-zipformer.sh * Update run-multi-zh_hans-zipformer.sh * Update run-multi-zh_hans-zipformer.sh * Update run-multi-zh_hans-zipformer.sh * Update run-multi-zh_hans-zipformer.sh --------- Co-authored-by: Fangjun Kuang <csukuangfj@gmail.com>
Introduction
Please refer to https://icefall.readthedocs.io/en/latest/recipes/Non-streaming-ASR/librispeech/index.html for how to run models in this recipe.
./RESULTS.md contains the latest results.
Transducers
There are various folders containing the name transducer
in this folder.
The following table lists the differences among them.
Encoder | Decoder | Comment | |
---|---|---|---|
transducer |
Conformer | LSTM | |
transducer_stateless |
Conformer | Embedding + Conv1d | Using optimized_transducer from computing RNN-T loss |
transducer_stateless2 |
Conformer | Embedding + Conv1d | Using torchaudio for computing RNN-T loss |
transducer_lstm |
LSTM | LSTM | |
transducer_stateless_multi_datasets |
Conformer | Embedding + Conv1d | Using data from GigaSpeech as extra training data |
pruned_transducer_stateless |
Conformer | Embedding + Conv1d | Using k2 pruned RNN-T loss |
pruned_transducer_stateless2 |
Conformer(modified) | Embedding + Conv1d | Using k2 pruned RNN-T loss |
pruned_transducer_stateless3 |
Conformer(modified) | Embedding + Conv1d | Using k2 pruned RNN-T loss + using GigaSpeech as extra training data |
pruned_transducer_stateless4 |
Conformer(modified) | Embedding + Conv1d | same as pruned_transducer_stateless2 + save averaged models periodically during training + delay penalty |
pruned_transducer_stateless5 |
Conformer(modified) | Embedding + Conv1d | same as pruned_transducer_stateless4 + more layers + random combiner |
pruned_transducer_stateless6 |
Conformer(modified) | Embedding + Conv1d | same as pruned_transducer_stateless4 + distillation with hubert |
pruned_transducer_stateless7 |
Zipformer | Embedding + Conv1d | First experiment with Zipformer from Dan |
pruned_transducer_stateless7_ctc |
Zipformer | Embedding + Conv1d | Same as pruned_transducer_stateless7, but with extra CTC head |
pruned_transducer_stateless7_ctc_bs |
Zipformer | Embedding + Conv1d | pruned_transducer_stateless7_ctc + blank skip |
pruned_transducer_stateless7_streaming |
Streaming Zipformer | Embedding + Conv1d | streaming version of pruned_transducer_stateless7 |
pruned_transducer_stateless7_streaming_multi |
Streaming Zipformer | Embedding + Conv1d | same as pruned_transducer_stateless7_streaming, trained on LibriSpeech + GigaSpeech |
pruned_transducer_stateless8 |
Zipformer | Embedding + Conv1d | Same as pruned_transducer_stateless7, but using extra data from GigaSpeech |
pruned_stateless_emformer_rnnt2 |
Emformer(from torchaudio) | Embedding + Conv1d | Using Emformer from torchaudio for streaming ASR |
conv_emformer_transducer_stateless |
ConvEmformer | Embedding + Conv1d | Using ConvEmformer for streaming ASR + mechanisms in reworked model |
conv_emformer_transducer_stateless2 |
ConvEmformer | Embedding + Conv1d | Using ConvEmformer with simplified memory for streaming ASR + mechanisms in reworked model |
lstm_transducer_stateless |
LSTM | Embedding + Conv1d | Using LSTM with mechanisms in reworked model |
lstm_transducer_stateless2 |
LSTM | Embedding + Conv1d | Using LSTM with mechanisms in reworked model + gigaspeech (multi-dataset setup) |
lstm_transducer_stateless3 |
LSTM | Embedding + Conv1d | Using LSTM with mechanisms in reworked model + gradient filter + delay penalty |
zipformer |
Upgraded Zipformer | Embedding + Conv1d | The latest recipe |
The decoder in transducer_stateless
is modified from the paper
Rnn-Transducer with Stateless Prediction Network.
We place an additional Conv1d layer right after the input embedding layer.
CTC
Encoder | Comment | |
---|---|---|
conformer-ctc |
Conformer | Use auxiliary attention head |
conformer-ctc2 |
Reworked Conformer | Use auxiliary attention head |
conformer-ctc3 |
Reworked Conformer | Streaming version + delay penalty |
zipformer |
Upgraded Zipformer | Use auxiliary transducer head |
MMI
Encoder | Comment | |
---|---|---|
conformer-mmi |
Conformer | |
zipformer-mmi |
Zipformer | CTC warmup + use HP as decoding graph for decoding |