offline-tts.py
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#!/usr/bin/env python3
#
# Copyright (c) 2023 Xiaomi Corporation
"""
This file demonstrates how to use sherpa-onnx Python API to generate audio
from text, i.e., text-to-speech.
Usage:
1. Download a model
wget https://huggingface.co/csukuangfj/vits-ljs/resolve/main/vits-ljs.onnx
wget https://huggingface.co/csukuangfj/vits-ljs/resolve/main/lexicon.txt
wget https://huggingface.co/csukuangfj/vits-ljs/resolve/main/tokens.txt
python3 ./python-api-examples/offline-tts.py \
--vits-model=./vits-ljs.onnx \
--vits-lexicon=./lexicon.txt \
--vits-tokens=./tokens.txt \
--output-filename=./generated.wav \
'liliana, the most beautiful and lovely assistant of our team!'
"""
import argparse
import sherpa_onnx
import soundfile as sf
def get_args():
parser = argparse.ArgumentParser(
formatter_class=argparse.ArgumentDefaultsHelpFormatter
)
parser.add_argument(
"--vits-model",
type=str,
help="Path to vits model.onnx",
)
parser.add_argument(
"--vits-lexicon",
type=str,
help="Path to lexicon.txt",
)
parser.add_argument(
"--vits-tokens",
type=str,
help="Path to tokens.txt",
)
parser.add_argument(
"--output-filename",
type=str,
default="./generated.wav",
help="Path to save generated wave",
)
parser.add_argument(
"--debug",
type=bool,
default=False,
help="True to show debug messages",
)
parser.add_argument(
"--provider",
type=str,
default="cpu",
help="valid values: cpu, cuda, coreml",
)
parser.add_argument(
"--num-threads",
type=int,
default=1,
help="Number of threads for neural network computation",
)
parser.add_argument(
"text",
type=str,
help="The input text to generate audio for",
)
return parser.parse_args()
def main():
args = get_args()
print(args)
tts_config = sherpa_onnx.OfflineTtsConfig(
model=sherpa_onnx.OfflineTtsModelConfig(
vits=sherpa_onnx.OfflineTtsVitsModelConfig(
model=args.vits_model,
lexicon=args.vits_lexicon,
tokens=args.vits_tokens,
),
provider=args.provider,
debug=args.debug,
num_threads=args.num_threads,
)
)
tts = sherpa_onnx.OfflineTts(tts_config)
audio = tts.generate(args.text)
sf.write(
args.output_filename,
audio.samples,
samplerate=audio.sample_rate,
subtype="PCM_16",
)
print(f"Saved to {args.output_filename}")
print(f"The text is '{args.text}'")
if __name__ == "__main__":
main()