From 62230ef37a85c0f1b55d202628648895468f567d Mon Sep 17 00:00:00 2001 From: 0xlws Date: Fri, 15 Sep 2023 19:56:49 +0200 Subject: [PATCH] docs: typos in joint_tracker.py --- src/jump_reward_inference/joint_tracker.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/src/jump_reward_inference/joint_tracker.py b/src/jump_reward_inference/joint_tracker.py index e91ab0a..d72a298 100644 --- a/src/jump_reward_inference/joint_tracker.py +++ b/src/jump_reward_inference/joint_tracker.py @@ -4,9 +4,9 @@ The model first takes the waveform to the spectral domain and then feeds them into one of the pre-trained BeatNet models to obtain beat/downbeat activations. Finally, the activations are used in a jump-reward inference model to infer beats, downbeats, tempo, and meter. -system input: Raw audio waveform +System input: Raw audio waveform -System output: a vector with beats, downbeats, local tempo, and local meter columns, respectively. shape (num_beats, 4). +System output: A vector with beats, downbeats, local tempo, and local meter columns, respectively. shape (num_beats, 4). References: @@ -29,8 +29,8 @@ def __init__(self, model, plot=False): def process(self, audio_path): preds = self.activation_estimator.activation_extractor_online( - audio_path) # extracting the activations using the BeatNet nueral network + audio_path) # extracting the activations using the BeatNet neural network output = self.estimator.process( - preds) # infering online joing beat, downbeat, tempo and meter using the 1D state space and jump back reward technique + preds) # inferring online joint beat, downbeat, tempo and meter using the 1D state space and jump back reward technique return output