Update results for libri+giga multi dataset setup. (#363)

* Update results for libri+giga multi dataset setup.

.github/scripts/run-librispeech-pruned-transducer-stateless3-2022-05-13.sh

@@ -0,0 +1,80 @@
+#!/usr/bin/env bash
+
+log() {
+  # This function is from espnet
+  local fname=${BASH_SOURCE[1]##*/}
+  echo -e "$(date '+%Y-%m-%d %H:%M:%S') (${fname}:${BASH_LINENO[0]}:${FUNCNAME[1]}) $*"
+}
+
+cd egs/librispeech/ASR
+
+repo_url=https://huggingface.co/csukuangfj/icefall-asr-librispeech-pruned-transducer-stateless3-2022-05-13
+
+log "Downloading pre-trained model from $repo_url"
+git lfs install
+git clone $repo_url
+repo=$(basename $repo_url)
+
+log "Display test files"
+tree $repo/
+soxi $repo/test_wavs/*.wav
+ls -lh $repo/test_wavs/*.wav
+
+pushd $repo/exp
+ln -s pretrained-iter-1224000-avg-14.pt pretrained.pt
+popd
+
+for sym in 1 2 3; do
+  log "Greedy search with --max-sym-per-frame $sym"
+
+  ./pruned_transducer_stateless3/pretrained.py \
+    --method greedy_search \
+    --max-sym-per-frame $sym \
+    --checkpoint $repo/exp/pretrained.pt \
+    --bpe-model $repo/data/lang_bpe_500/bpe.model \
+    $repo/test_wavs/1089-134686-0001.wav \
+    $repo/test_wavs/1221-135766-0001.wav \
+    $repo/test_wavs/1221-135766-0002.wav
+done
+
+for method in modified_beam_search beam_search fast_beam_search; do
+  log "$method"
+
+  ./pruned_transducer_stateless3/pretrained.py \
+    --method $method \
+    --beam-size 4 \
+    --checkpoint $repo/exp/pretrained.pt \
+    --bpe-model $repo/data/lang_bpe_500/bpe.model \
+    $repo/test_wavs/1089-134686-0001.wav \
+    $repo/test_wavs/1221-135766-0001.wav \
+    $repo/test_wavs/1221-135766-0002.wav
+done
+
+echo "GITHUB_EVENT_NAME: ${GITHUB_EVENT_NAME}"
+echo "GITHUB_EVENT_LABEL_NAME: ${GITHUB_EVENT_LABEL_NAME}"
+if [[ x"${GITHUB_EVENT_NAME}" == x"schedule" || x"${GITHUB_EVENT_LABEL_NAME}" == x"run-decode"  ]]; then
+  mkdir -p pruned_transducer_stateless3/exp
+  ln -s $PWD/$repo/exp/pretrained.pt pruned_transducer_stateless3/exp/epoch-999.pt
+  ln -s $PWD/$repo/data/lang_bpe_500 data/
+
+  ls -lh data
+  ls -lh pruned_transducer_stateless3/exp
+
+  log "Decoding test-clean and test-other"
+
+  # use a small value for decoding with CPU
+  max_duration=100
+
+  for method in greedy_search fast_beam_search modified_beam_search; do
+    log "Decoding with $method"
+
+    ./pruned_transducer_stateless3/decode.py \
+      --decoding-method $method \
+      --epoch 999 \
+      --avg 1 \
+      --max-duration $max_duration \
+      --exp-dir pruned_transducer_stateless3/exp
+  done
+
+  rm pruned_transducer_stateless3/exp/*.pt
+fi

.github/workflows/run-librispeech-2022-04-29.yml

@@ -142,8 +142,8 @@ jobs:
           find fast_beam_search -name "log-*" -exec grep -n --color "best for test-other" {} + | sort -n -k2
 
           echo "===modified beam search==="
-          find exp/modified_beam_search -name "log-*" -exec grep -n --color "best for test-clean" {} + | sort -n -k2
+          find modified_beam_search -name "log-*" -exec grep -n --color "best for test-clean" {} + | sort -n -k2
-          find exp/modified_beam_search -name "log-*" -exec grep -n --color "best for test-other" {} + | sort -n -k2
+          find modified_beam_search -name "log-*" -exec grep -n --color "best for test-other" {} + | sort -n -k2
 
       - name: Display decoding results for pruned_transducer_stateless3
         if: github.event_name == 'schedule' || github.event.label.name == 'run-decode'
@@ -161,8 +161,8 @@ jobs:
           find fast_beam_search -name "log-*" -exec grep -n --color "best for test-other" {} + | sort -n -k2
 
           echo "===modified beam search==="
-          find exp/modified_beam_search -name "log-*" -exec grep -n --color "best for test-clean" {} + | sort -n -k2
+          find modified_beam_search -name "log-*" -exec grep -n --color "best for test-clean" {} + | sort -n -k2
-          find exp/modified_beam_search -name "log-*" -exec grep -n --color "best for test-other" {} + | sort -n -k2
+          find modified_beam_search -name "log-*" -exec grep -n --color "best for test-other" {} + | sort -n -k2
 
       - name: Upload decoding results for pruned_transducer_stateless2
         uses: actions/upload-artifact@v2

.github/workflows/run-librispeech-pruned-transducer-stateless3-2022-05-13.yml

@@ -0,0 +1,151 @@
+# Copyright      2021  Fangjun Kuang (csukuangfj@gmail.com)
+
+# 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.
+
+name: run-librispeech-pruned-transducer-stateless3-2022-05-13
+# stateless pruned transducer (reworked model) + giga speech
+
+on:
+  push:
+    branches:
+      - master
+  pull_request:
+    types: [labeled]
+
+  schedule:
+    # minute (0-59)
+    # hour (0-23)
+    # day of the month (1-31)
+    # month (1-12)
+    # day of the week (0-6)
+    # nightly build at 15:50 UTC time every day
+    - cron: "50 15 * * *"
+
+jobs:
+  run_librispeech_pruned_transducer_stateless3_2022_05_13:
+    if: github.event.label.name == 'ready' || github.event.label.name == 'run-decode' || github.event_name == 'push' || github.event_name == 'schedule'
+    runs-on: ${{ matrix.os }}
+    strategy:
+      matrix:
+        os: [ubuntu-18.04]
+        python-version: [3.7, 3.8, 3.9]
+
+      fail-fast: false
+
+    steps:
+      - uses: actions/checkout@v2
+        with:
+          fetch-depth: 0
+
+      - name: Setup Python ${{ matrix.python-version }}
+        uses: actions/setup-python@v2
+        with:
+          python-version: ${{ matrix.python-version }}
+          cache: 'pip'
+          cache-dependency-path: '**/requirements-ci.txt'
+
+      - name: Install Python dependencies
+        run: |
+          grep -v '^#' ./requirements-ci.txt  | xargs -n 1 -L 1 pip install
+
+      - name: Cache kaldifeat
+        id: my-cache
+        uses: actions/cache@v2
+        with:
+          path: |
+            ~/tmp/kaldifeat
+          key: cache-tmp-${{ matrix.python-version }}
+
+      - name: Install kaldifeat
+        if: steps.my-cache.outputs.cache-hit != 'true'
+        shell: bash
+        run: |
+          .github/scripts/install-kaldifeat.sh
+
+      - name: Cache LibriSpeech test-clean and test-other datasets
+        id: libri-test-clean-and-test-other-data
+        uses: actions/cache@v2
+        with:
+          path: |
+            ~/tmp/download
+          key: cache-libri-test-clean-and-test-other
+
+      - name: Download LibriSpeech test-clean and test-other
+        if: steps.libri-test-clean-and-test-other-data.outputs.cache-hit != 'true'
+        shell: bash
+        run: |
+          .github/scripts/download-librispeech-test-clean-and-test-other-dataset.sh
+
+      - name: Prepare manifests for LibriSpeech test-clean and test-other
+        shell: bash
+        run: |
+          .github/scripts/prepare-librispeech-test-clean-and-test-other-manifests.sh
+
+      - name: Cache LibriSpeech test-clean and test-other fbank features
+        id: libri-test-clean-and-test-other-fbank
+        uses: actions/cache@v2
+        with:
+          path: |
+            ~/tmp/fbank-libri
+          key: cache-libri-fbank-test-clean-and-test-other
+
+      - name: Compute fbank for LibriSpeech test-clean and test-other
+        if: steps.libri-test-clean-and-test-other-fbank.outputs.cache-hit != 'true'
+        shell: bash
+        run: |
+          .github/scripts/compute-fbank-librispeech-test-clean-and-test-other.sh
+
+      - name: Inference with pre-trained model
+        shell: bash
+        env:
+          GITHUB_EVENT_NAME: ${{ github.event_name }}
+          GITHUB_EVENT_LABEL_NAME: ${{ github.event.label.name }}
+        run: |
+          mkdir -p egs/librispeech/ASR/data
+          ln -sfv ~/tmp/fbank-libri egs/librispeech/ASR/data/fbank
+          ls -lh egs/librispeech/ASR/data/*
+
+          sudo apt-get -qq install git-lfs tree sox
+          export PYTHONPATH=$PWD:$PYTHONPATH
+          export PYTHONPATH=~/tmp/kaldifeat/kaldifeat/python:$PYTHONPATH
+          export PYTHONPATH=~/tmp/kaldifeat/build/lib:$PYTHONPATH
+
+          .github/scripts/run-librispeech-pruned-transducer-stateless3-2022-05-13.sh
+
+      - name: Display decoding results for pruned_transducer_stateless3
+        if: github.event_name == 'schedule' || github.event.label.name == 'run-decode'
+        shell: bash
+        run: |
+          cd egs/librispeech/ASR
+          tree pruned_transducer_stateless3/exp
+          cd pruned_transducer_stateless3/exp
+          echo "===greedy search==="
+          find greedy_search -name "log-*" -exec grep -n --color "best for test-clean" {} + | sort -n -k2
+          find greedy_search -name "log-*" -exec grep -n --color "best for test-other" {} + | sort -n -k2
+
+          echo "===fast_beam_search==="
+          find fast_beam_search -name "log-*" -exec grep -n --color "best for test-clean" {} + | sort -n -k2
+          find fast_beam_search -name "log-*" -exec grep -n --color "best for test-other" {} + | sort -n -k2
+
+          echo "===modified beam search==="
+          find modified_beam_search -name "log-*" -exec grep -n --color "best for test-clean" {} + | sort -n -k2
+          find modified_beam_search -name "log-*" -exec grep -n --color "best for test-other" {} + | sort -n -k2
+
+      - name: Upload decoding results for pruned_transducer_stateless3
+        uses: actions/upload-artifact@v2
+        if: github.event_name == 'schedule' || github.event.label.name == 'run-decode'
+        with:
+          name: torch-${{ matrix.torch }}-python-${{ matrix.python-version }}-ubuntu-18.04-cpu-pruned_transducer_stateless3-2022-04-29
+          path: egs/librispeech/ASR/pruned_transducer_stateless3/exp/

README.md

@@ -107,7 +107,7 @@ We provide a Colab notebook to run a pre-trained transducer conformer + stateles
 
 |     | test-clean | test-other |
 |-----|------------|------------|
-| WER | 2.19       | 4.97       |
+| WER | 2.00       | 4.63       |
 
 
 ### Aishell

egs/librispeech/ASR/RESULTS.md

@@ -1,6 +1,6 @@
 ## Results
 
-### LibriSpeech BPE training results (Pruned Transducer 3)
+### LibriSpeech BPE training results (Pruned Transducer 3, 2022-04-29)
 
 [pruned_transducer_stateless3](./pruned_transducer_stateless3)
 Same as `Pruned Transducer 2` but using the XL subset from
@@ -152,6 +152,67 @@ for epoch in 27; do
 done
 ```
 
+### LibriSpeech BPE training results (Pruned Transducer 3, 2022-05-13)
+
+Same setup as [pruned_transducer_stateless3](./pruned_transducer_stateless3) (2022-04-29)
+but change `--giga-prob` from 0.8 to 0.9. Also use `repeat` on gigaspeech XL
+subset so that the gigaspeech dataloader never exhausts.
+
+|                                     | test-clean | test-other | comment                                                                       |
+|-------------------------------------|------------|------------|---------------------------------------------|
+| greedy search (max sym per frame 1) | 2.03       | 4.70       | --iter 1224000 --avg 14  --max-duration 600 |
+| modified beam search                | 2.00       | 4.63       | --iter 1224000 --avg 14  --max-duration 600 |
+| fast beam search                    | 2.10       | 4.68       | --iter 1224000 --avg 14 --max-duration 600 |
+
+The training commands are:
+
+```bash
+export CUDA_VISIBLE_DEVICES="0,1,2,3,4,5,6,7"
+
+./prepare.sh
+./prepare_giga_speech.sh
+
+./pruned_transducer_stateless3/train.py \
+  --world-size 8 \
+  --num-epochs 30 \
+  --start-epoch 0 \
+  --full-libri 1 \
+  --exp-dir pruned_transducer_stateless3/exp-0.9 \
+  --max-duration 300 \
+  --use-fp16 1 \
+  --lr-epochs 4 \
+  --num-workers 2 \
+  --giga-prob 0.9
+```
+
+The tensorboard log is available at
+<https://tensorboard.dev/experiment/HpocR7dKS9KCQkJeYxfXug/>
+
+Decoding commands:
+
+```bash
+for iter in 1224000; do
+  for avg in 14; do
+    for method in greedy_search modified_beam_search fast_beam_search ; do
+      ./pruned_transducer_stateless3/decode.py \
+        --iter $iter \
+        --avg $avg \
+        --exp-dir ./pruned_transducer_stateless3/exp-0.9/ \
+        --max-duration 600 \
+        --decoding-method $method \
+        --max-sym-per-frame 1 \
+        --beam 4 \
+        --max-contexts 32
+    done
+  done
+done
+```
+
+The pretrained models, training logs, decoding logs, and decoding results
+can be found at
+<https://huggingface.co/csukuangfj/icefall-asr-librispeech-pruned-transducer-stateless3-2022-05-13>
+
+
 ### LibriSpeech BPE training results (Pruned Transducer 2)
 
 [pruned_transducer_stateless2](./pruned_transducer_stateless2)

egs/librispeech/ASR/pruned_transducer_stateless/pretrained.py

@@ -23,7 +23,7 @@ Usage:
     --bpe-model ./data/lang_bpe_500/bpe.model \
     --method greedy_search \
     /path/to/foo.wav \
-        /path/to/bar.wav \
+    /path/to/bar.wav
 
 (2) beam search
 ./pruned_transducer_stateless/pretrained.py \
@@ -32,7 +32,7 @@ Usage:
     --method beam_search \
     --beam-size 4 \
     /path/to/foo.wav \
-        /path/to/bar.wav \
+    /path/to/bar.wav
 
 (3) modified beam search
 ./pruned_transducer_stateless/pretrained.py \
@@ -41,7 +41,7 @@ Usage:
     --method modified_beam_search \
     --beam-size 4 \
     /path/to/foo.wav \
-        /path/to/bar.wav \
+    /path/to/bar.wav
 
 (4) fast beam search
 ./pruned_transducer_stateless/pretrained.py \
@@ -50,7 +50,7 @@ Usage:
     --method fast_beam_search \
     --beam-size 4 \
     /path/to/foo.wav \
-        /path/to/bar.wav \
+    /path/to/bar.wav
 
 You can also use `./pruned_transducer_stateless/exp/epoch-xx.pt`.
 
@@ -233,6 +233,9 @@ def main():
     logging.info("Creating model")
     model = get_transducer_model(params)
 
+    num_param = sum([p.numel() for p in model.parameters()])
+    logging.info(f"Number of model parameters: {num_param}")
+
     checkpoint = torch.load(args.checkpoint, map_location="cpu")
     model.load_state_dict(checkpoint["model"], strict=False)
     model.to(device)

egs/librispeech/ASR/pruned_transducer_stateless2/pretrained.py

@@ -23,16 +23,34 @@ Usage:
     --bpe-model ./data/lang_bpe_500/bpe.model \
     --method greedy_search \
     /path/to/foo.wav \
-        /path/to/bar.wav \
+    /path/to/bar.wav
 
-(1) beam search
+(2) beam search
 ./pruned_transducer_stateless2/pretrained.py \
     --checkpoint ./pruned_transducer_stateless2/exp/pretrained.pt \
     --bpe-model ./data/lang_bpe_500/bpe.model \
     --method beam_search \
     --beam-size 4 \
     /path/to/foo.wav \
-        /path/to/bar.wav \
+    /path/to/bar.wav
+
+(3) modified beam search
+./pruned_transducer_stateless2/pretrained.py \
+    --checkpoint ./pruned_transducer_stateless2/exp/pretrained.pt \
+    --bpe-model ./data/lang_bpe_500/bpe.model \
+    --method modified_beam_search \
+    --beam-size 4 \
+    /path/to/foo.wav \
+    /path/to/bar.wav
+
+(4) fast beam search
+./pruned_transducer_stateless2/pretrained.py \
+    --checkpoint ./pruned_transducer_stateless2/exp/pretrained.pt \
+    --bpe-model ./data/lang_bpe_500/bpe.model \
+    --method fast_beam_search \
+    --beam-size 4 \
+    /path/to/foo.wav \
+    /path/to/bar.wav
 
 You can also use `./pruned_transducer_stateless2/exp/epoch-xx.pt`.
 
@@ -79,9 +97,7 @@ def get_parser():
     parser.add_argument(
         "--bpe-model",
         type=str,
-        help="""Path to bpe.model.
+        help="""Path to bpe.model.""",
-        Used only when method is ctc-decoding.
-        """,
     )
 
     parser.add_argument(
@@ -117,7 +133,33 @@ def get_parser():
         "--beam-size",
         type=int,
         default=4,
-        help="Used only when --method is beam_search and modified_beam_search",
+        help="""An integer indicating how many candidates we will keep for each
+        frame. Used only when --method is beam_search or
+        modified_beam_search.""",
+    )
+
+    parser.add_argument(
+        "--beam",
+        type=float,
+        default=4,
+        help="""A floating point value to calculate the cutoff score during beam
+        search (i.e., `cutoff = max-score - beam`), which is the same as the
+        `beam` in Kaldi.
+        Used only when --method is fast_beam_search""",
+    )
+
+    parser.add_argument(
+        "--max-contexts",
+        type=int,
+        default=4,
+        help="""Used only when --method is fast_beam_search""",
+    )
+
+    parser.add_argument(
+        "--max-states",
+        type=int,
+        default=8,
+        help="""Used only when --method is fast_beam_search""",
     )
 
     parser.add_argument(
@@ -244,9 +286,9 @@ def main():
             decoding_graph=decoding_graph,
             encoder_out=encoder_out,
             encoder_out_lens=encoder_out_lens,
-            beam=8.0,
+            beam=params.beam,
-            max_contexts=32,
+            max_contexts=params.max_contexts,
-            max_states=8,
+            max_states=params.max_states,
         )
         for hyp in sp.decode(hyp_tokens):
             hyps.append(hyp.split())
@@ -254,6 +296,7 @@ def main():
         hyp_tokens = modified_beam_search(
             model=model,
             encoder_out=encoder_out,
+            encoder_out_lens=encoder_out_lens,
             beam=params.beam_size,
         )
 
@@ -263,6 +306,7 @@ def main():
         hyp_tokens = greedy_search_batch(
             model=model,
             encoder_out=encoder_out,
+            encoder_out_lens=encoder_out_lens,
         )
         for hyp in sp.decode(hyp_tokens):
             hyps.append(hyp.split())

egs/librispeech/ASR/pruned_transducer_stateless3/pretrained.py

@@ -23,16 +23,34 @@ Usage:
     --bpe-model ./data/lang_bpe_500/bpe.model \
     --method greedy_search \
     /path/to/foo.wav \
-        /path/to/bar.wav \
+    /path/to/bar.wav
 
-(1) beam search
+(2) beam search
 ./pruned_transducer_stateless3/pretrained.py \
     --checkpoint ./pruned_transducer_stateless3/exp/pretrained.pt \
     --bpe-model ./data/lang_bpe_500/bpe.model \
     --method beam_search \
     --beam-size 4 \
     /path/to/foo.wav \
-        /path/to/bar.wav \
+    /path/to/bar.wav
+
+(3) modified beam search
+./pruned_transducer_stateless3/pretrained.py \
+    --checkpoint ./pruned_transducer_stateless3/exp/pretrained.pt \
+    --bpe-model ./data/lang_bpe_500/bpe.model \
+    --method modified_beam_search \
+    --beam-size 4 \
+    /path/to/foo.wav \
+    /path/to/bar.wav
+
+(4) fast beam search
+./pruned_transducer_stateless3/pretrained.py \
+    --checkpoint ./pruned_transducer_stateless3/exp/pretrained.pt \
+    --bpe-model ./data/lang_bpe_500/bpe.model \
+    --method fast_beam_search \
+    --beam-size 4 \
+    /path/to/foo.wav \
+    /path/to/bar.wav
 
 You can also use `./pruned_transducer_stateless3/exp/epoch-xx.pt`.
 
@@ -79,9 +97,7 @@ def get_parser():
     parser.add_argument(
         "--bpe-model",
         type=str,
-        help="""Path to bpe.model.
+        help="""Path to bpe.model.""",
-        Used only when method is ctc-decoding.
-        """,
     )
 
     parser.add_argument(
@@ -117,7 +133,33 @@ def get_parser():
         "--beam-size",
         type=int,
         default=4,
-        help="Used only when --method is beam_search and modified_beam_search",
+        help="""An integer indicating how many candidates we will keep for each
+        frame. Used only when --method is beam_search or
+        modified_beam_search.""",
+    )
+
+    parser.add_argument(
+        "--beam",
+        type=float,
+        default=4,
+        help="""A floating point value to calculate the cutoff score during beam
+        search (i.e., `cutoff = max-score - beam`), which is the same as the
+        `beam` in Kaldi.
+        Used only when --method is fast_beam_search""",
+    )
+
+    parser.add_argument(
+        "--max-contexts",
+        type=int,
+        default=4,
+        help="""Used only when --method is fast_beam_search""",
+    )
+
+    parser.add_argument(
+        "--max-states",
+        type=int,
+        default=8,
+        help="""Used only when --method is fast_beam_search""",
     )
 
     parser.add_argument(
@@ -244,9 +286,9 @@ def main():
             decoding_graph=decoding_graph,
             encoder_out=encoder_out,
             encoder_out_lens=encoder_out_lens,
-            beam=8.0,
+            beam=params.beam,
-            max_contexts=32,
+            max_contexts=params.max_contexts,
-            max_states=8,
+            max_states=params.max_states,
         )
         for hyp in sp.decode(hyp_tokens):
             hyps.append(hyp.split())
@@ -254,6 +296,7 @@ def main():
         hyp_tokens = modified_beam_search(
             model=model,
             encoder_out=encoder_out,
+            encoder_out_lens=encoder_out_lens,
             beam=params.beam_size,
         )
 
@@ -263,6 +306,7 @@ def main():
         hyp_tokens = greedy_search_batch(
             model=model,
             encoder_out=encoder_out,
+            encoder_out_lens=encoder_out_lens,
         )
         for hyp in sp.decode(hyp_tokens):
             hyps.append(hyp.split())

egs/librispeech/ASR/pruned_transducer_stateless3/train.py

@@ -968,6 +968,7 @@ def run(rank, world_size, args):
         train_giga_cuts = gigaspeech.train_S_cuts()
 
     train_giga_cuts = filter_short_and_long_utterances(train_giga_cuts)
+    train_giga_cuts = train_giga_cuts.repeat(times=None)
 
     if args.enable_musan:
         cuts_musan = load_manifest(