From 1b10379a667c89538413fd0f6bcc9cdbd005774c Mon Sep 17 00:00:00 2001 From: van Date: Mon, 11 Dec 2023 13:48:56 +0800 Subject: [PATCH] Update benchmark. --- benchmark/README.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/benchmark/README.md b/benchmark/README.md index 834261f..0732e34 100644 --- a/benchmark/README.md +++ b/benchmark/README.md @@ -7,8 +7,8 @@ In the field of deep learning for audio, the mel spectrogram is the most commonl | ---- | ---- | ---- | ---- | | [audioFlux](https://github.com/libAudioFlux/audioFlux) | C/Python | 0.1.5 | A library for audio and music analysis, feature extraction | | [torchaudio](https://github.com/pytorch/audio) | Python | 0.11.0 | Data manipulation and transformation for audio signal processing, powered by PyTorch | -| [librosa](https://github.com/librosa/librosa) | Python | 0.10.0 | C++ library for audio and music analysis, description and synthesis, including Python bindings | -| [essentia](https://github.com/MTG/essentia) | C++/Python | 2.0.1 | Python library for audio and music analysis | +| [librosa](https://github.com/librosa/librosa) | Python | 0.10.0 | Python library for audio and music analysis | +| [essentia](https://github.com/MTG/essentia) | C++/Python | 2.0.1 | C++ library for audio and music analysis, description and synthesis, including Python bindings | - audioFlux: developed in C with a Python wrapper, it has different bridging processes for different platforms, and supports **OpenBLAS**, **MKL**, etc. - torchaudio: developed in PyTorch, which is optimized for CPUs and uses **MKL** as its backend. This evaluation does not include the GPU version of PyTorch.