Skip to main content

Speech-Toolkit for bahasa Malaysia, powered by Deep Learning Tensorflow.

Project description

Malaya-Speech is a Speech-Toolkit library for bahasa Malaysia, powered by Deep Learning Tensorflow.

Documentation

Proper documentation is available at https://malaya-speech.readthedocs.io/

Installing from the PyPI

CPU version

$ pip install malaya-speech

GPU version

$ pip install malaya-speech-gpu

Only Python 3.6.x and above and Tensorflow 1.10 and above but not 2.0 are supported.

Features

  • Age Detection

    Detect age in speech using Finetuned Speaker Vector Malaya-Speech models.

  • Speaker Diarization

    Diarizing speakers using Pretrained Speaker Vector Malaya-Speech models.

  • Emotion Detection

    Detect emotions in speech using Finetuned Speaker Vector Malaya-Speech models.

  • Gender Detection

    Detect genders in speech using Finetuned Speaker Vector Malaya-Speech models.

  • Language Detection

    Detect hyperlocal languages in speech using Finetuned Speaker Vector Malaya-Speech models.

  • Noise Reduction

    Reduce multilevel noises using Pretrained STFT UNET Malaya-Speech models.

  • Speaker Change

    Detect changing speakers using Finetuned Speaker Vector Malaya-Speech models.

  • Speaker overlap

    Detect overlap speakers using Finetuned Speaker Vector Malaya-Speech models.

  • Speaker Vector

    Calculate similarity between speakers using Pretrained Malaya-Speech models.

  • Speech Enhancement

    Enhance voice activities using Pretrained STFT UNET Malaya-Speech models.

  • Voice Activity Detection

    Detect voice activities using Finetuned Speaker Vector Malaya-Speech models.

References

If you use our software for research, please cite:

@misc{Malaya, Speech-Toolkit library for bahasa Malaysia, powered by Deep Learning Tensorflow,
  author = {Husein, Zolkepli},
  title = {Malaya-Speech},
  year = {2020},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/huseinzol05/malaya-speech}}
}

Acknowledgement

Thanks to Mesolitica and KeyReply for sponsoring GCP and private cloud to train Malaya models.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distribution

malaya_speech-0.0.1.2-py3-none-any.whl (212.4 kB view hashes)

Uploaded Python 3

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page