• Corpus ID: 2022157

The Importance of F0 Tracking in Query-by-singing-humming

  title={The Importance of F0 Tracking in Query-by-singing-humming},
  author={Emilio Molina and Lorenzo J. Tard{\'o}n and Isabel Barbancho and Ana M. Barbancho},
In this paper, we present a comparative study of several state-of-the-art F0 trackers applied to the context of queryby-singing-humming(QBSH). This study has been carried out using the well known, freely available, MIR-QBSH dataset in differentconditionsof added pub-style noise and smartphone-style distortion. For audio-to-MIDI melodic matching, we have used two state-of-the-art systems and a simple, easily reproduciblebaselinemethod. Fortheevaluation, we measured the QBSH performance for 189… 
Computer-aided Melody Note Transcription Using the Tony Software: Accuracy and Efficiency
Tony, a software tool for the interactive annotation of melodies from monophonic audio recordings, is presented, and it is shown that Tony’s built in automatic note transcription method compares favourably with existing tools.
Audio to Score Matching by Combining Phonetic and Duration Information
This work argues that, due to the existence of a basic melodic contour for each mode in jingju music, only using melodic information will result in an ambiguous matching, and proposes a matching approach based on the use of phonetic and duration information.
Influence of Room Acoustics on Choir Singing
Multitrack recordings of a mixed adult choir with 23 singers were collected in order to investigate the influence of varied room acoustical conditions on a choir’s performance with regard to
By Humming System using Convolutional Neural Network
In this paper, we propose a note-based query by humming (QBH) system with Hidden Markov Model (HMM) and Convolutional Neural Network (CNN) since note-based systems are much more efficient than the
Influence of virtual room acoustics on choir singing
(ProQuest: ... denotes formulae omitted)The aesthetic appreciation of a choir performance heavily relies on both the singers' skills and the acoustical characteristics of the venue. Choir directors
Unified Algorithm for Melodic Music Similarity and Retrieval in Query by Humming
A unified algorithm for measuring melodic music similarity in QBH is proposed based on the study of melody representation in the form of note string and user query variations to reduce the effective computational time and improve accuracy.
Joint Detection and Classification of Singing Voice Melody Using Convolutional Recurrent Neural Networks
Singing melody extraction essentially involves two tasks: one is detecting the activity of a singing voice in polyphonic music, and the other is estimating the pitch of a singing voice in the
Analysis of Song/Artist Latent Features and Its Application for Song Search
This paper proposes two concepts of artist-song relationships: overall similarity and prominent affinity, and proposes three applications for song search that are beneficial for searching for songs according to the users' various search intents.
Query-by-Blending: A Music Exploration System Blending Latent Vector Representations of Lyric Word, Song Audio, and Artist
Query-by-Blending is a novel music exploration system that enables users to find unfamiliar music content by flexibly combining three musical aspects: lyric word, song audio, and artist by constructing a novel vector space model.
A Machine Learning based Music Retrieval and Recommendation System
A query by humming system for music retrieval that uses deep neural networks for note transcription and a note-based retrieval system for retrieving the correct song from the database and a similar artist recommendation system which recommends similar artists based on acoustic features of the artists’ music, online text descriptions of the Artists and social media data is proposed.


An effective and efficient method for query by humming system based on multi-similarity measurement fusion
This paper proposes a novel scheme taking advantage of two different similarity measurements to improve not only the retrieval accuracy but also the retrieving speed.
The importance of optimal parameter setting for pitch extraction.
In this study we present a performance comparison for five pitch extraction algorithms: Auto Correlation, Cross Correlation, and Sub-Harmonic Summation (as implemented in PRAAT [Boersma and Weenick
The Audio Degradation Toolbox and Its Application to Robustness Evaluation
It is demonstrated that specific degradations can reduce or even reverse the performance difference between two competing methods, and it is shown that performance strongly depends on the combination of method and degradation applied.
On the use of autocorrelation analysis for pitch detection
Several types of (nonlinear) preprocessing which can be used to effectively spectrally flatten the speech signal are presented and an algorithm for adaptively choosing a frame size for an autocorrelation pitch analysis is discussed.
Improving searching speed and accuracy of query by humming system based on three methods: feature fusion, candidates set reduction and multiple similarity measurement rescoring
Three methods for improving the searching speed and accuracy for query by humming (QBH) system with large melody database and utilizes scores generated during the filtering stage and finematching stage to fusing together to get more accurate result.
PYIN: A fundamental frequency estimator using probabilistic threshold distributions
  • Matthias Mauch, S. Dixon
  • Computer Science
    2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
  • 2014
The Probabilistic YIN (PYIN) algorithm is proposed, a modification of the well-known YIN algorithm for fundamental frequency (F0) estimation that is modified to output multiple pitch candidates with associated probabilities from a prior distribution on the YIN threshold parameter.
Melody Extraction From Polyphonic Music Signals Using Pitch Contour Characteristics
  • J. Salamon, E. Gómez
  • Computer Science
    IEEE Transactions on Audio, Speech, and Language Processing
  • 2012
A comparative evaluation of the proposed approach shows that it outperforms current state-of-the-art melody extraction systems in terms of overall accuracy.
This document describes our submission to QBSH task of MIREX 2013. Our algorithm adopts a two-stage cascaded solution based on Locality Sensitive Hashing (LSH) and accurate matching of frame-level
We present a straightforward and robust algorithm for periodicity detection, working in the lag (autocorrelation) domain. When it is tested for periodic signals and for signals with additive noise or
YIN, a fundamental frequency estimator for speech and music.
An algorithm is presented for the estimation of the fundamental frequency (F0) of speech or musical sounds. It is based on the well-known autocorrelation method with a number of modifications that