mirror of
https://github.com/k2-fsa/icefall.git
synced 2025-09-08 16:44:20 +00:00
Merge remote-tracking branch 'dan/master' into update-giga-libri-results
This commit is contained in:
commit
ad3fb63ad6
15
.github/scripts/download-gigaspeech-dev-test-dataset.sh
vendored
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15
.github/scripts/download-gigaspeech-dev-test-dataset.sh
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#!/usr/bin/env bash
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# This script downloads the pre-computed fbank features for
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# dev and test datasets of GigaSpeech.
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#
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# You will find directories `~/tmp/giga-dev-dataset-fbank` after running
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# this script.
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mkdir -p ~/tmp
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cd ~/tmp
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git lfs install
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git clone https://huggingface.co/csukuangfj/giga-dev-dataset-fbank
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ls -lh giga-dev-dataset-fbank/data/fbank
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49
.github/scripts/run-gigaspeech-pruned-transducer-stateless2-2022-05-12.sh
vendored
Executable file
49
.github/scripts/run-gigaspeech-pruned-transducer-stateless2-2022-05-12.sh
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#!/usr/bin/env bash
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log() {
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# This function is from espnet
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local fname=${BASH_SOURCE[1]##*/}
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echo -e "$(date '+%Y-%m-%d %H:%M:%S') (${fname}:${BASH_LINENO[0]}:${FUNCNAME[1]}) $*"
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}
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cd egs/gigaspeech/ASR
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repo_url=https://huggingface.co/wgb14/icefall-asr-gigaspeech-pruned-transducer-stateless2
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log "Downloading pre-trained model from $repo_url"
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git lfs install
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git clone $repo_url
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repo=$(basename $repo_url)
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echo "GITHUB_EVENT_NAME: ${GITHUB_EVENT_NAME}"
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echo "GITHUB_EVENT_LABEL_NAME: ${GITHUB_EVENT_LABEL_NAME}"
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if [[ x"${GITHUB_EVENT_NAME}" == x"schedule" || x"${GITHUB_EVENT_LABEL_NAME}" == x"run-decode" ]]; then
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mkdir -p pruned_transducer_stateless2/exp
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ln -s $PWD/$repo/exp/pretrained-epoch-29-avg-11.pt pruned_transducer_stateless2/exp/epoch-999.pt
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ln -s $PWD/$repo/data/lang_bpe_500 data/
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ls -lh data
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ls -lh data/lang_bpe_500
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ls -lh data/fbank
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ls -lh pruned_transducer_stateless2/exp
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log "Decoding dev and test"
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# use a small value for decoding with CPU
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max_duration=100
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# Test only greedy_search to reduce CI running time
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# for method in greedy_search fast_beam_search modified_beam_search; do
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for method in greedy_search; do
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log "Decoding with $method"
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./pruned_transducer_stateless2/decode.py \
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--decoding-method $method \
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--epoch 999 \
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--avg 1 \
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--max-duration $max_duration \
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--exp-dir pruned_transducer_stateless2/exp
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done
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rm pruned_transducer_stateless2/exp/*.pt
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fi
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120
.github/workflows/run-gigaspeech-2022-05-13.yml
vendored
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120
.github/workflows/run-gigaspeech-2022-05-13.yml
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# Copyright 2021 Fangjun Kuang (csukuangfj@gmail.com)
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# See ../../LICENSE for clarification regarding multiple authors
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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name: run-gigaspeech-2022-05-13
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# stateless transducer + k2 pruned rnnt-loss + reworked conformer
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on:
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push:
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branches:
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- master
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pull_request:
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types: [labeled]
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schedule:
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# minute (0-59)
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# hour (0-23)
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# day of the month (1-31)
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# month (1-12)
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# day of the week (0-6)
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# nightly build at 15:50 UTC time every day
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- cron: "50 15 * * *"
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jobs:
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run_gigaspeech_2022_05_13:
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if: github.event.label.name == 'ready' || github.event.label.name == 'run-decode' || github.event_name == 'push' || github.event_name == 'schedule'
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runs-on: ${{ matrix.os }}
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strategy:
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matrix:
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os: [ubuntu-18.04]
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python-version: [3.7, 3.8, 3.9]
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fail-fast: false
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steps:
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- uses: actions/checkout@v2
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with:
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fetch-depth: 0
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- name: Setup Python ${{ matrix.python-version }}
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uses: actions/setup-python@v2
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with:
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python-version: ${{ matrix.python-version }}
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cache: 'pip'
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cache-dependency-path: '**/requirements-ci.txt'
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- name: Install Python dependencies
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run: |
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grep -v '^#' ./requirements-ci.txt | xargs -n 1 -L 1 pip install
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- name: Cache kaldifeat
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id: my-cache
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uses: actions/cache@v2
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with:
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path: |
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~/tmp/kaldifeat
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key: cache-tmp-${{ matrix.python-version }}
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- name: Install kaldifeat
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if: steps.my-cache.outputs.cache-hit != 'true'
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shell: bash
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run: |
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.github/scripts/install-kaldifeat.sh
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- name: Download GigaSpeech dev/test dataset
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shell: bash
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run: |
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sudo apt-get install -y -q git-lfs
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.github/scripts/download-gigaspeech-dev-test-dataset.sh
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- name: Inference with pre-trained model
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shell: bash
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env:
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GITHUB_EVENT_NAME: ${{ github.event_name }}
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GITHUB_EVENT_LABEL_NAME: ${{ github.event.label.name }}
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run: |
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ln -s ~/tmp/giga-dev-dataset-fbank/data egs/gigaspeech/ASR/
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ls -lh egs/gigaspeech/ASR/data/fbank
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export PYTHONPATH=$PWD:$PYTHONPATH
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export PYTHONPATH=~/tmp/kaldifeat/kaldifeat/python:$PYTHONPATH
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export PYTHONPATH=~/tmp/kaldifeat/build/lib:$PYTHONPATH
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.github/scripts/run-gigaspeech-pruned-transducer-stateless2-2022-05-12.sh
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- name: Display decoding results for gigaspeech pruned_transducer_stateless2
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if: github.event_name == 'schedule' || github.event.label.name == 'run-decode'
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shell: bash
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run: |
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cd egs/gigaspeech/ASR/
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tree ./pruned_transducer_stateless2/exp
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sudo apt-get -qq install tree
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cd pruned_transducer_stateless2
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echo "results for pruned_transducer_stateless2"
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echo "===greedy search==="
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find exp/greedy_search -name "log-*" -exec grep -n --color "best for dev" {} + | sort -n -k2
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find exp/greedy_search -name "log-*" -exec grep -n --color "best for test" {} + | sort -n -k2
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- name: Upload decoding results for gigaspeech pruned_transducer_stateless2
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uses: actions/upload-artifact@v2
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if: github.event_name == 'schedule' || github.event.label.name == 'run-decode'
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with:
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name: torch-${{ matrix.torch }}-python-${{ matrix.python-version }}-ubuntu-18.04-cpu-gigaspeech-pruned_transducer_stateless2-2022-05-12
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path: egs/gigaspeech/ASR/pruned_transducer_stateless2/exp/
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@ -145,7 +145,14 @@ def generate_lexicon(
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sp = spm.SentencePieceProcessor()
|
sp = spm.SentencePieceProcessor()
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sp.load(str(model_file))
|
sp.load(str(model_file))
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words_pieces: List[List[str]] = sp.encode(words, out_type=str)
|
# Convert word to word piece IDs instead of word piece strings
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# to avoid OOV tokens.
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words_pieces_ids: List[List[int]] = sp.encode(words, out_type=int)
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|
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|
# Now convert word piece IDs back to word piece strings.
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|
words_pieces: List[List[str]] = [
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sp.id_to_piece(ids) for ids in words_pieces_ids
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|
]
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|
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lexicon = []
|
lexicon = []
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for word, pieces in zip(words, words_pieces):
|
for word, pieces in zip(words, words_pieces):
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|
77
egs/librispeech/ASR/local/validate_bpe_lexicon.py
Executable file
77
egs/librispeech/ASR/local/validate_bpe_lexicon.py
Executable file
@ -0,0 +1,77 @@
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|
#!/usr/bin/env python3
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|
# Copyright 2022 Xiaomi Corp. (authors: Fangjun Kuang)
|
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|
#
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|
# See ../../../../LICENSE for clarification regarding multiple authors
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|
#
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|
# Licensed under the Apache License, Version 2.0 (the "License");
|
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|
# 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
|
||||||
|
#
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||||||
|
# Unless required by applicable law or agreed to in writing, software
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||||||
|
# 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.
|
||||||
|
"""
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||||||
|
This script checks that there are no OOV tokens in the BPE-based lexicon.
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|
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|
Usage example:
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|
|
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|
python3 ./local/validate_bpe_lexicon.py \
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|
--lexicon /path/to/lexicon.txt \
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|
--bpe-model /path/to/bpe.model
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|
"""
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|
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|
import argparse
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||||||
|
from pathlib import Path
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||||||
|
from typing import List, Tuple
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|
|
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|
import sentencepiece as spm
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|
|
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|
from icefall.lexicon import read_lexicon
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|
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|
# Map word to word pieces
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|
Lexicon = List[Tuple[str, List[str]]]
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|
|
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|
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|
def get_args():
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|
parser = argparse.ArgumentParser()
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|
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|
parser.add_argument(
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|
"--lexicon",
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|
required=True,
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|
type=Path,
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|
help="Path to lexicon.txt",
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|
)
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||||||
|
|
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|
parser.add_argument(
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|
"--bpe-model",
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|
required=True,
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||||||
|
type=Path,
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||||||
|
help="Path to bpe.model",
|
||||||
|
)
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||||||
|
|
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|
return parser.parse_args()
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|
|
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|
|
||||||
|
def main():
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||||||
|
args = get_args()
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||||||
|
assert args.lexicon.is_file(), args.lexicon
|
||||||
|
assert args.bpe_model.is_file(), args.bpe_model
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||||||
|
|
||||||
|
lexicon = read_lexicon(args.lexicon)
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||||||
|
|
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|
sp = spm.SentencePieceProcessor()
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||||||
|
sp.load(str(args.bpe_model))
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||||||
|
|
||||||
|
word_pieces = set(sp.id_to_piece(list(range(sp.vocab_size()))))
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||||||
|
for word, pieces in lexicon:
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||||||
|
for p in pieces:
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||||||
|
if p not in word_pieces:
|
||||||
|
raise ValueError(f"The word {word} contains an OOV token {p}")
|
||||||
|
|
||||||
|
|
||||||
|
if __name__ == "__main__":
|
||||||
|
main()
|
@ -184,13 +184,20 @@ if [ $stage -le 6 ] && [ $stop_stage -ge 6 ]; then
|
|||||||
done > $lang_dir/transcript_words.txt
|
done > $lang_dir/transcript_words.txt
|
||||||
fi
|
fi
|
||||||
|
|
||||||
./local/train_bpe_model.py \
|
if [ ! -f $lang_dir/bpe.model ]; then
|
||||||
--lang-dir $lang_dir \
|
./local/train_bpe_model.py \
|
||||||
--vocab-size $vocab_size \
|
--lang-dir $lang_dir \
|
||||||
--transcript $lang_dir/transcript_words.txt
|
--vocab-size $vocab_size \
|
||||||
|
--transcript $lang_dir/transcript_words.txt
|
||||||
|
fi
|
||||||
|
|
||||||
if [ ! -f $lang_dir/L_disambig.pt ]; then
|
if [ ! -f $lang_dir/L_disambig.pt ]; then
|
||||||
./local/prepare_lang_bpe.py --lang-dir $lang_dir
|
./local/prepare_lang_bpe.py --lang-dir $lang_dir
|
||||||
|
|
||||||
|
log "Validating $lang_dir/lexicon.txt"
|
||||||
|
./local/validate_bpe_lexicon.py \
|
||||||
|
--lexicon $lang_dir/lexicon.txt \
|
||||||
|
--bpe-model $lang_dir/bpe.model
|
||||||
fi
|
fi
|
||||||
done
|
done
|
||||||
fi
|
fi
|
||||||
|
Loading…
x
Reference in New Issue
Block a user