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 operations which makes it easy to use and feel like a natural extension.

Features

  • AM inference with CUDA CTC Beam Seach Decoder
  • On device audio-visual automatic speech recognition
  • Loading waveform Tensors from files and saving them
  • Documentation available
  • CTC Forced Alignment API
  • Forced alignment for multilingual data
  • Streaming media decoding with StreamReader

Project Samples

Project Activity

See All Activity >

License

BSD License

Follow TorchAudio

TorchAudio Web Site

Other Useful Business Software
Full-stack observability with actually useful AI | Grafana Cloud Icon
Full-stack observability with actually useful AI | Grafana Cloud

Our generous forever free tier includes the full platform, including the AI Assistant, for 3 users with 10k metrics, 50GB logs, and 50GB traces.

Built on open standards like Prometheus and OpenTelemetry, Grafana Cloud includes Kubernetes Monitoring, Application Observability, Incident Response, plus the AI-powered Grafana Assistant. Get started with our generous free tier today.
Create free account
Rate This Project
Login To Rate This Project

User Reviews

Be the first to post a review of TorchAudio!

Additional Project Details

Operating Systems

Linux, Mac, Windows

Programming Language

Python

Related Categories

Python Machine Learning Software, Python LLM Inference Tool

Registered

2024-08-08