From 236b6f4f66daba6a44efcb93903dcebe52065890 Mon Sep 17 00:00:00 2001 From: Kushal Agrawal <98145879+kushal34712@users.noreply.github.com> Date: Wed, 25 Oct 2023 21:37:16 +0530 Subject: [PATCH] Update README.md --- README.md | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/README.md b/README.md index 328035f..e4820e3 100644 --- a/README.md +++ b/README.md @@ -4,7 +4,7 @@ This repository contains the official implementation of ["Separate Anything You Describe"](https://audio-agi.github.io/Separate-Anything-You-Describe/AudioSep_arXiv.pdf). -We introduce AudioSep, a foundation model for open-domain sound separation with natural language queries. AudioSep demonstrates strong separation performance and impressive zero-shot generalization ability on numerous tasks, such as audio event separation, musical instrument separation, and speech enhancement. Check out the separated audio examples on the [Demo Page](https://audio-agi.github.io/Separate-Anything-You-Describe/)! +We introduce AudioSep, a foundation model for open-domain sound separation with natural language queries. AudioSep demonstrates strong separation performance and impressive zero-shot generalisation ability on numerous tasks, such as audio event separation, musical instrument separation, and speech enhancement. Check out the separated audio examples on the [Demo Page](https://audio-agi.github.io/Separate-Anything-You-Describe/)!

@@ -104,7 +104,7 @@ Train AudioSep from scratch: python train.py --workspace workspace/AudioSep --config_yaml config/audiosep_base.yaml --resume_checkpoint_path checkpoint/ '' ``` -Finetune AudioSep from pretrained checkpoint: +Finetune AudioSep from pre-trained checkpoint: ```python python train.py --workspace workspace/AudioSep --config_yaml config/audiosep_base.yaml --resume_checkpoint_path path_to_checkpoint ``` @@ -124,7 +124,7 @@ evaluation: - clotho/ - esc50/ ``` -Run benchmark inference script, the results will be saved at `eval_logs/` +Run benchmark inference script. The results will be saved at `eval_logs/` ```python python benchmark.py --checkpoint_path audiosep_base_4M_steps.ckpt