Showing 2 open source projects for "audio waveform"

View related business solutions
  • Stop Cyber Threats with VM-Series Next-Gen Firewall on Azure Icon
    Stop Cyber Threats with VM-Series Next-Gen Firewall on Azure

    Native application identity and user-based security for your Azure cloud

    Gain integrated visibility across all traffic in a single pass. Deploy Palo Alto Networks VM-Series to determine application identity and content while automating security policy updates via rich APIs.
    Get a free trial
  • $300 Free Credits to Build on Google Cloud Icon
    $300 Free Credits to Build on Google Cloud

    New to Google Cloud? Get $300 in credits to explore Compute Engine, BigQuery, Cloud Run, Gemini Enterprise Agent Platform, and more.

    Start your next project with $300 in free Google Cloud credit. Spin up VMs, run containers, query petabytes in BigQuery, or build agents with Gemini Enterprise Agent Platform. Once your credits are used, keep building with 20+ always-free tier products including Compute Engine, Cloud Storage, GKE, and Cloud Run functions. No commitment required—just sign up and start building.
    Claim $300 Free
  • 1
    pyAudioAnalysis

    pyAudioAnalysis

    Python Audio Analysis Library: Feature Extraction, Classification

    pyAudioAnalysis is an open-source Python library designed for audio signal analysis, machine learning, and music information retrieval tasks. The project provides a collection of tools that allow developers to extract meaningful features from audio files and use those features for classification, segmentation, and analysis. The library supports multiple audio processing workflows, including feature extraction from raw audio signals, training of machine learning models, and automatic audio...
    Downloads: 1 This Week
    Last Update:
    See Project
  • 2
    TorchAudio

    TorchAudio

    Data manipulation and transformation for audio signal processing

    The aim of torchaudio is to apply PyTorch to the audio domain. By supporting PyTorch, torchaudio follows the same philosophy of providing strong GPU acceleration, having a focus on trainable features through the autograd system, and having consistent style (tensor names and dimension names). Therefore, it is primarily a machine learning library and not a general signal processing library. The benefits of PyTorch can be seen in torchaudio through having all the computations be through PyTorch...
    Downloads: 2 This Week
    Last Update:
    See Project
  • Previous
  • You're on page 1
  • Next
Auth0 Logo