Paper Reading AI Learner

An objective test tool for pitch extractors' response attributes

2022-04-02 17:01:50
Hideki Kawahara, Kohei Yatabe, Ken-Ichi Sakakibara, Tatsuya Kitamura, Hideki Banno, Masanori Morise

Abstract

We propose an objective measurement method for pitch extractors' responses to frequency-modulated signals. It enables us to evaluate different pitch extractors with unified criteria. The method uses extended time-stretched pulses combined by binary orthogonal sequences. It provides simultaneous measurement results consisting of the linear and the non-linear time-invariant responses and random and time-varying responses. We tested representative pitch extractors using fundamental frequencies spanning 80~Hz to 400~Hz with 1/48 octave steps and produced more than 1000 modulation frequency response plots. We found that making scientific visualization by animating these plots enables us to understand different pitch extractors' behavior at once. Such efficient and effortless inspection is impossible by inspecting all individual plots. The proposed measurement method with visualization leads to further improvement of the performance of one of the extractors mentioned above. In other words, our procedure turns the specific pitch extractor into the best reliable measuring equipment that is crucial for scientific research. We open-sourced MATLAB codes of the proposed objective measurement method and visualization procedure.

Abstract (translated)

URL

https://arxiv.org/abs/2204.00902

PDF

https://arxiv.org/pdf/2204.00902.pdf


Tags
3D Action Action_Localization Action_Recognition Activity Adversarial Agent Attention Autonomous Bert Boundary_Detection Caption Chat Classification CNN Compressive_Sensing Contour Contrastive_Learning Deep_Learning Denoising Detection Dialog Diffusion Drone Dynamic_Memory_Network Edge_Detection Embedding Embodied Emotion Enhancement Face Face_Detection Face_Recognition Facial_Landmark Few-Shot Gait_Recognition GAN Gaze_Estimation Gesture Gradient_Descent Handwriting Human_Parsing Image_Caption Image_Classification Image_Compression Image_Enhancement Image_Generation Image_Matting Image_Retrieval Inference Inpainting Intelligent_Chip Knowledge Knowledge_Graph Language_Model Matching Medical Memory_Networks Multi_Modal Multi_Task NAS NMT Object_Detection Object_Tracking OCR Ontology Optical_Character Optical_Flow Optimization Person_Re-identification Point_Cloud Portrait_Generation Pose Pose_Estimation Prediction QA Quantitative Quantitative_Finance Quantization Re-identification Recognition Recommendation Reconstruction Regularization Reinforcement_Learning Relation Relation_Extraction Represenation Represenation_Learning Restoration Review RNN Salient Scene_Classification Scene_Generation Scene_Parsing Scene_Text Segmentation Self-Supervised Semantic_Instance_Segmentation Semantic_Segmentation Semi_Global Semi_Supervised Sence_graph Sentiment Sentiment_Classification Sketch SLAM Sparse Speech Speech_Recognition Style_Transfer Summarization Super_Resolution Surveillance Survey Text_Classification Text_Generation Tracking Transfer_Learning Transformer Unsupervised Video_Caption Video_Classification Video_Indexing Video_Prediction Video_Retrieval Visual_Relation VQA Weakly_Supervised Zero-Shot