2024-12-31 14:17:20 +08:00

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#!/usr/bin/env bash
set -ex
apt-get update
apt-get install -y sox
python3 -m pip install numba conformer==0.3.2 diffusers librosa
python3 -m pip install jieba
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/baker_zh/TTS
sed -i.bak s/600/8/g ./prepare.sh
sed -i.bak s/"first 100"/"first 3"/g ./prepare.sh
sed -i.bak s/500/5/g ./prepare.sh
git diff
function prepare_data() {
# We have created a subset of the data for testing
#
mkdir -p download
pushd download
wget -q https://huggingface.co/csukuangfj/tmp-files/resolve/main/BZNSYP-samples.tar.bz2
tar xvf BZNSYP-samples.tar.bz2
mv BZNSYP-samples BZNSYP
rm BZNSYP-samples.tar.bz2
popd
./prepare.sh
tree .
}
function train() {
pushd ./matcha
sed -i.bak s/1500/3/g ./train.py
git diff .
popd
./matcha/train.py \
--exp-dir matcha/exp \
--num-epochs 1 \
--save-every-n 1 \
--num-buckets 2 \
--tokens data/tokens.txt \
--max-duration 20
ls -lh matcha/exp
}
function infer() {
curl -SL -O https://github.com/csukuangfj/models/raw/refs/heads/master/hifigan/generator_v2
./matcha/infer.py \
--num-buckets 2 \
--epoch 1 \
--exp-dir ./matcha/exp \
--tokens data/tokens.txt \
--cmvn ./data/fbank/cmvn.json \
--vocoder ./generator_v2 \
--input-text "当夜幕降临,星光点点,伴随着微风拂面,我在静谧中感受着时光的流转,思念如涟漪荡漾,梦境如画卷展开,我与自然融为一体,沉静在这片宁静的美丽之中,感受着生命的奇迹与温柔。" \
--output-wav ./generated.wav
ls -lh *.wav
soxi ./generated.wav
rm -v ./generated.wav
rm -v generator_v2
}
function export_onnx() {
pushd matcha/exp
curl -SL -O https://huggingface.co/csukuangfj/icefall-tts-baker-matcha-zh-2024-12-27/resolve/main/epoch-2000.pt
popd
pushd data/fbank
rm -v *.json
curl -SL -O https://huggingface.co/csukuangfj/icefall-tts-baker-matcha-zh-2024-12-27/resolve/main/cmvn.json
popd
./matcha/export_onnx.py \
--exp-dir ./matcha/exp \
--epoch 2000 \
--tokens ./data/tokens.txt \
--cmvn ./data/fbank/cmvn.json
ls -lh *.onnx
if false; then
# The CI machine does not have enough memory to run it
#
curl -SL -O https://github.com/csukuangfj/models/raw/refs/heads/master/hifigan/generator_v1
curl -SL -O https://github.com/csukuangfj/models/raw/refs/heads/master/hifigan/generator_v2
curl -SL -O https://github.com/csukuangfj/models/raw/refs/heads/master/hifigan/generator_v3
python3 ./matcha/export_onnx_hifigan.py
else
curl -SL -O https://huggingface.co/csukuangfj/icefall-tts-ljspeech-matcha-en-2024-10-28/resolve/main/exp/hifigan_v1.onnx
curl -SL -O https://huggingface.co/csukuangfj/icefall-tts-ljspeech-matcha-en-2024-10-28/resolve/main/exp/hifigan_v2.onnx
curl -SL -O https://huggingface.co/csukuangfj/icefall-tts-ljspeech-matcha-en-2024-10-28/resolve/main/exp/hifigan_v3.onnx
fi
ls -lh *.onnx
python3 ./matcha/generate_lexicon.py
for v in v1 v2 v3; do
python3 ./matcha/onnx_pretrained.py \
--acoustic-model ./model-steps-6.onnx \
--vocoder ./hifigan_$v.onnx \
--tokens ./data/tokens.txt \
--lexicon ./lexicon.txt \
--input-text "当夜幕降临,星光点点,伴随着微风拂面,我在静谧中感受着时光的流转,思念如涟漪荡漾,梦境如画卷展开,我与自然融为一体,沉静在这片宁静的美丽之中,感受着生命的奇迹与温柔。" \
--output-wav /icefall/generated-matcha-tts-steps-6-$v.wav
done
ls -lh /icefall/*.wav
soxi /icefall/generated-matcha-tts-steps-6-*.wav
cp ./model-steps-*.onnx /icefall
d=matcha-icefall-zh-baker
mkdir $d
cp -v data/tokens.txt $d
cp -v lexicon.txt $d
cp model-steps-3.onnx $d
pushd $d
curl -SL -O https://github.com/csukuangfj/cppjieba/releases/download/sherpa-onnx-2024-04-19/dict.tar.bz2
tar xvf dict.tar.bz2
rm dict.tar.bz2
curl -SL -O https://huggingface.co/csukuangfj/icefall-tts-aishell3-vits-low-2024-04-06/resolve/main/data/date.fst
curl -SL -O https://huggingface.co/csukuangfj/icefall-tts-aishell3-vits-low-2024-04-06/resolve/main/data/number.fst
curl -SL -O https://huggingface.co/csukuangfj/icefall-tts-aishell3-vits-low-2024-04-06/resolve/main/data/phone.fst
cat >README.md <<EOF
# Introduction
This model is trained using the dataset from
https://en.data-baker.com/datasets/freeDatasets/
The dataset contains 10000 Chinese sentences of a native Chinese female speaker,
which is about 12 hours.
**Note**: The dataset is for non-commercial use only.
You can find the training code at
https://github.com/k2-fsa/icefall/tree/master/egs/baker_zh/TTS
EOF
ls -lh
popd
tar cvjf $d.tar.bz2 $d
mv $d.tar.bz2 /icefall
}
prepare_data
train
infer
export_onnx
rm -rfv generator_v* matcha/exp
git checkout .