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SemantiCodec

Ultra-low bitrate neural audio codec with a better semantic in the latent space.

Highlight

  • Bitrate: 0.31 kbps - 1.40 kbps
  • Token rate: 25, 50, or 100 per second
  • cpu, cuda, and mps are supported

Usage

Installation

pip install git+https://github.com/haoheliu/SemantiCodec-inference.git

Encoding and decoding

Checkpoints will be automatically downloaded when you initialize the SemantiCodec with the following code.

from semanticodec import SemantiCodec

semanticodec = SemantiCodec(token_rate=100, semantic_vocab_size=16384) 

filepath = "test/test.wav" # audio with arbitrary length

tokens = semanticodec.encode(filepath)
waveform = semanticodec.decode(tokens)

# Save the reconstruction file
import soundfile as sf
sf.write("output.wav", waveform[0,0], 16000)

Other Settings

from semanticodec import SemantiCodec

###############Choose one of the following######################
semanticodec = SemantiCodec(token_rate=100, semantic_vocab_size=32768) # 1.40 kbps
semanticodec = SemantiCodec(token_rate=50, semantic_vocab_size=32768) # 0.70 kbps
semanticodec = SemantiCodec(token_rate=25, semantic_vocab_size=32768) # 0.35 kbps

semanticodec = SemantiCodec(token_rate=100, semantic_vocab_size=16384) # 1.35 kbps
semanticodec = SemantiCodec(token_rate=50, semantic_vocab_size=16384) # 0.68 kbps
semanticodec = SemantiCodec(token_rate=25, semantic_vocab_size=16384) # 0.34 kbps

semanticodec = SemantiCodec(token_rate=100, semantic_vocab_size=8192) # 1.30 kbps
semanticodec = SemantiCodec(token_rate=50, semantic_vocab_size=8192) # 0.65 kbps
semanticodec = SemantiCodec(token_rate=25, semantic_vocab_size=8192) # 0.33 kbps

semanticodec = SemantiCodec(token_rate=100, semantic_vocab_size=4096) # 1.25 kbps
semanticodec = SemantiCodec(token_rate=50, semantic_vocab_size=4096) # 0.63 kbps
semanticodec = SemantiCodec(token_rate=25, semantic_vocab_size=4096) # 0.31 kbps
#####################################

filepath = "test/test.wav"

tokens = semanticodec.encode(filepath)
waveform = semanticodec.decode(tokens)

import soundfile as sf
sf.write("output.wav", waveform[0,0], 16000)

If you are interested in reusing the same evaluation pipeline and data in the paper, please refer to this zenodo repo.

Citation

If you find this repo helpful, please consider citing in the following format:

@article{liu2024semanticodec,
  title={SemantiCodec: An Ultra Low Bitrate Semantic Audio Codec for General Sound},
  author={Liu, Haohe and Xu, Xuenan and Yuan, Yi and Wu, Mengyue and Wang, Wenwu and Plumbley, Mark D},
  journal={arXiv preprint arXiv:2405.00233},
  year={2024}
}

result