speech enhancement mask unet
Overview
The Speech Enhancement Mask UNet is a deep learning architecture designed to isolate clean speech from noisy backgrounds by predicting time-frequency masks. Unlike direct waveform synthesis, this model operates on spectrograms, identifying which components of the signal are noise and which are voice to effectively 'mask' the interference. For developers, this is particularly useful for preprocessing pipelines in ASR (Automatic Speech Recognition) or building real-time voice cleanup tools. It offers a balanced trade-off between computational efficiency and noise suppression, making it a viable candidate for integration into audio processing middleware where latency and signal fidelity are critical.
Highlights
- Implements U-Net architecture for precise time-frequency masking
- Optimized for noise reduction in speech preprocessing pipelines
- Apache-2.0 license allows for flexible commercial integration
- Effective for improving ASR accuracy in noisy environments
Usage
Install
# Install Hugging Face transformers
pip install transformers torchSDK Usage
# Load model with transformers
from transformers import AutoModel, AutoTokenizer
model = AutoModel.from_pretrained("huseinzol05/speech-enhancement-mask-unet")
tokenizer = AutoTokenizer.from_pretrained("huseinzol05/speech-enhancement-mask-unet")Hugging Face Download
We recommend downloading the model via the Hugging Face CLI or Hub SDK.
Guidance：Before downloading, install huggingface_hub with:
Guidance
pip install -U huggingface_hubCLI Download
Download the full repository
Download the full repository
huggingface-cli download huseinzol05/speech-enhancement-mask-unetDownload a single file to a local folder (e.g. config.json into ./dir)
Download a single file to a local folder (e.g. config.json into ./dir)
huggingface-cli download huseinzol05/speech-enhancement-mask-unet config.json --local-dir ./dirSee the official docs for more CLI options
SDK Download
SDK Download
# 模型下载
from huggingface_hub import snapshot_download
model_dir = snapshot_download('huseinzol05/speech-enhancement-mask-unet')Git Download
Make sure git-lfs is installed first
Git Download
git lfs install
git clone https://huggingface.co/huseinzol05/speech-enhancement-mask-unetTo skip LFS large-file downloads, use:
Skip LFS
GIT_LFS_SKIP_SMUDGE=1 git clone https://huggingface.co/huseinzol05/speech-enhancement-mask-unetModel files are hosted on the Hugging Face Hub — download directly via HF CLI / SDK / Git, not through this site.
PyTorch / Transformers Usage
Install Transformers
Install Transformers
pip install -U transformers torchLoad the model and run inference
Load the model and run inference
from transformers import AutoModelForCausalLM, AutoTokenizer
model = AutoModelForCausalLM.from_pretrained('huseinzol05/speech-enhancement-mask-unet')
tokenizer = AutoTokenizer.from_pretrained('huseinzol05/speech-enhancement-mask-unet')