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DeepSpeech
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8d919781
编写于
3月 17, 2022
作者:
小湉湉
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差异文件
add hifigan in syn of aishell3, test=tts
上级
1410a840
变更
2
隐藏空白更改
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并排
Showing
2 changed file
with
88 addition
and
33 deletion
+88
-33
examples/aishell3/tts3/local/synthesize.sh
examples/aishell3/tts3/local/synthesize.sh
+41
-15
examples/aishell3/tts3/local/synthesize_e2e.sh
examples/aishell3/tts3/local/synthesize_e2e.sh
+47
-18
未找到文件。
examples/aishell3/tts3/local/synthesize.sh
浏览文件 @
8d919781
...
...
@@ -4,18 +4,44 @@ config_path=$1
train_output_path
=
$2
ckpt_name
=
$3
FLAGS_allocator_strategy
=
naive_best_fit
\
FLAGS_fraction_of_gpu_memory_to_use
=
0.01
\
python3
${
BIN_DIR
}
/../synthesize.py
\
--am
=
fastspeech2_aishell3
\
--am_config
=
${
config_path
}
\
--am_ckpt
=
${
train_output_path
}
/checkpoints/
${
ckpt_name
}
\
--am_stat
=
dump/train/speech_stats.npy
\
--voc
=
pwgan_aishell3
\
--voc_config
=
pwg_aishell3_ckpt_0.5/default.yaml
\
--voc_ckpt
=
pwg_aishell3_ckpt_0.5/snapshot_iter_1000000.pdz
\
--voc_stat
=
pwg_aishell3_ckpt_0.5/feats_stats.npy
\
--test_metadata
=
dump/test/norm/metadata.jsonl
\
--output_dir
=
${
train_output_path
}
/test
\
--phones_dict
=
dump/phone_id_map.txt
\
--speaker_dict
=
dump/speaker_id_map.txt
stage
=
0
stop_stage
=
0
# pwgan
if
[
${
stage
}
-le
0
]
&&
[
${
stop_stage
}
-ge
0
]
;
then
FLAGS_allocator_strategy
=
naive_best_fit
\
FLAGS_fraction_of_gpu_memory_to_use
=
0.01
\
python3
${
BIN_DIR
}
/../synthesize.py
\
--am
=
fastspeech2_aishell3
\
--am_config
=
${
config_path
}
\
--am_ckpt
=
${
train_output_path
}
/checkpoints/
${
ckpt_name
}
\
--am_stat
=
dump/train/speech_stats.npy
\
--voc
=
pwgan_aishell3
\
--voc_config
=
pwg_aishell3_ckpt_0.5/default.yaml
\
--voc_ckpt
=
pwg_aishell3_ckpt_0.5/snapshot_iter_1000000.pdz
\
--voc_stat
=
pwg_aishell3_ckpt_0.5/feats_stats.npy
\
--test_metadata
=
dump/test/norm/metadata.jsonl
\
--output_dir
=
${
train_output_path
}
/test
\
--phones_dict
=
dump/phone_id_map.txt
\
--speaker_dict
=
dump/speaker_id_map.txt
fi
# hifigan
if
[
${
stage
}
-le
1
]
&&
[
${
stop_stage
}
-ge
1
]
;
then
FLAGS_allocator_strategy
=
naive_best_fit
\
FLAGS_fraction_of_gpu_memory_to_use
=
0.01
\
python3
${
BIN_DIR
}
/../synthesize.py
\
--am
=
fastspeech2_aishell3
\
--am_config
=
${
config_path
}
\
--am_ckpt
=
${
train_output_path
}
/checkpoints/
${
ckpt_name
}
\
--am_stat
=
dump/train/speech_stats.npy
\
--voc
=
hifigan_aishell3
\
--voc_config
=
hifigan_aishell3_ckpt_0.2.0/default.yaml
\
--voc_ckpt
=
hifigan_aishell3_ckpt_0.2.0/snapshot_iter_2500000.pd
\
--voc_stat
=
hifigan_aishell3_ckpt_0.2.0/feats_stats.npy
\
--test_metadata
=
dump/test/norm/metadata.jsonl
\
--output_dir
=
${
train_output_path
}
/test
\
--phones_dict
=
dump/phone_id_map.txt
\
--speaker_dict
=
dump/speaker_id_map.txt
fi
examples/aishell3/tts3/local/synthesize_e2e.sh
浏览文件 @
8d919781
...
...
@@ -4,21 +4,50 @@ config_path=$1
train_output_path
=
$2
ckpt_name
=
$3
FLAGS_allocator_strategy
=
naive_best_fit
\
FLAGS_fraction_of_gpu_memory_to_use
=
0.01
\
python3
${
BIN_DIR
}
/../synthesize_e2e.py
\
--am
=
fastspeech2_aishell3
\
--am_config
=
${
config_path
}
\
--am_ckpt
=
${
train_output_path
}
/checkpoints/
${
ckpt_name
}
\
--am_stat
=
dump/train/speech_stats.npy
\
--voc
=
pwgan_aishell3
\
--voc_config
=
pwg_aishell3_ckpt_0.5/default.yaml
\
--voc_ckpt
=
pwg_aishell3_ckpt_0.5/snapshot_iter_1000000.pdz
\
--voc_stat
=
pwg_aishell3_ckpt_0.5/feats_stats.npy
\
--lang
=
zh
\
--text
=
${
BIN_DIR
}
/../sentences.txt
\
--output_dir
=
${
train_output_path
}
/test_e2e
\
--phones_dict
=
dump/phone_id_map.txt
\
--speaker_dict
=
dump/speaker_id_map.txt
\
--spk_id
=
0
\
--inference_dir
=
${
train_output_path
}
/inference
stage
=
0
stop_stage
=
0
# pwgan
if
[
${
stage
}
-le
0
]
&&
[
${
stop_stage
}
-ge
0
]
;
then
FLAGS_allocator_strategy
=
naive_best_fit
\
FLAGS_fraction_of_gpu_memory_to_use
=
0.01
\
python3
${
BIN_DIR
}
/../synthesize_e2e.py
\
--am
=
fastspeech2_aishell3
\
--am_config
=
${
config_path
}
\
--am_ckpt
=
${
train_output_path
}
/checkpoints/
${
ckpt_name
}
\
--am_stat
=
dump/train/speech_stats.npy
\
--voc
=
pwgan_aishell3
\
--voc_config
=
pwg_aishell3_ckpt_0.5/default.yaml
\
--voc_ckpt
=
pwg_aishell3_ckpt_0.5/snapshot_iter_1000000.pdz
\
--voc_stat
=
pwg_aishell3_ckpt_0.5/feats_stats.npy
\
--lang
=
zh
\
--text
=
${
BIN_DIR
}
/../sentences.txt
\
--output_dir
=
${
train_output_path
}
/test_e2e
\
--phones_dict
=
dump/phone_id_map.txt
\
--speaker_dict
=
dump/speaker_id_map.txt
\
--spk_id
=
0
\
--inference_dir
=
${
train_output_path
}
/inference
fi
# hifigan
if
[
${
stage
}
-le
1
]
&&
[
${
stop_stage
}
-ge
1
]
;
then
echo
"in hifigan syn_e2e"
FLAGS_allocator_strategy
=
naive_best_fit
\
FLAGS_fraction_of_gpu_memory_to_use
=
0.01
\
python3
${
BIN_DIR
}
/../synthesize_e2e.py
\
--am
=
fastspeech2_aishell3
\
--am_config
=
${
config_path
}
\
--am_ckpt
=
${
train_output_path
}
/checkpoints/
${
ckpt_name
}
\
--am_stat
=
fastspeech2_nosil_aishell3_ckpt_0.4/speech_stats.npy
\
--voc
=
hifigan_aishell3
\
--voc_config
=
hifigan_aishell3_ckpt_0.2.0/default.yaml
\
--voc_ckpt
=
hifigan_aishell3_ckpt_0.2.0/snapshot_iter_2500000.pdz
\
--voc_stat
=
hifigan_aishell3_ckpt_0.2.0/feats_stats.npy
\
--lang
=
zh
\
--text
=
${
BIN_DIR
}
/../sentences.txt
\
--output_dir
=
${
train_output_path
}
/test_e2e
\
--phones_dict
=
fastspeech2_nosil_aishell3_ckpt_0.4/phone_id_map.txt
\
--speaker_dict
=
fastspeech2_nosil_aishell3_ckpt_0.4/speaker_id_map.txt
\
--spk_id
=
0
\
--inference_dir
=
${
train_output_path
}
/inference
fi
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