Auditory Spectrum-Based Pitched Instrument Onset Detection

In this paper, a method for onset detection of music signals using auditory spectra is proposed. The auditory spectrogram provides a time-frequency representation that employs a sound processing model resembling the human auditory system. Recent work on onset detection employs DFT-based features describing spectral energy and phase differences, as well as pitch-based features. These features are often combined for maximizing detection performance. Here, the spectral flux and phase slope features are derived in the auditory framework and a novel fundamental frequency estimation algorithm based on auditory spectra is introduced. An onset detection algorithm is proposed, which processes and combines the aforementioned features at the decision level. Experiments are conducted on a dataset covering 11 pitched instrument types, consisting of 1829 onsets in total. Results indicate that auditory representations outperform various state-of-the-art approaches, with the onset detection algorithm reaching an F-measure of 82.6%

Gamelan Music Onset Detection based on Spectral Features

This research detects onsets of percussive instruments by examining the performance on the sound signals of gamelan instruments as one of  traditional music instruments in Indonesia. Onset plays important role in determining musical rythmic structure, like beat, tempo, measure, and is highly required in many applications of music information retrieval. Four onset detection methods that employ spectral features, such as magnitude, phase, and the combination of both are compared in this paper. They are phase slope (PS), weighted phase deviation (WPD), spectral flux (SF), and rectified complex domain (RCD). Features are extracted by representing the sound signals into time-frequency domain using overlapped Short-time Fourier Transform (STFT) and by varying the window length. Onset detection functions are processed through peak-picking using dynamic threshold. The results showed that by using suitable window length and parameter setting of dynamic threshold, F-measure which is greater than 0.80 can be obtained for certain methods

Automatic Drum Transcription and Source Separation

While research has been carried out on automated polyphonic music transcription, to-date the problem of automated polyphonic percussion transcription has not received the same degree of attention. A related problem is that of sound source separation, which attempts to separate a mixture signal into its constituent sources. This thesis focuses on the task of polyphonic percussion transcription and sound source separation of a limited set of drum instruments, namely the drums found in the standard rock/pop drum kit. As there was little previous research on polyphonic percussion transcription a broad review of music information retrieval methods, including previous polyphonic percussion systems, was also carried out to determine if there were any methods which were of potential use in the area of polyphonic drum transcription. Following on from this a review was conducted of general source separation and redundancy reduction techniques, such as Independent Component Analysis and Independent Subspace Analysis, as these techniques have shown potential in separating mixtures of sources. Upon completion of the review it was decided that a combination of the blind separation approach, Independent Subspace Analysis (ISA), with the use of prior knowledge as used in music information retrieval methods, was the best approach to tackling the problem of polyphonic percussion transcription as well as that of sound source separation. A number of new algorithms which combine the use of prior knowledge with the source separation abilities of techniques such as ISA are presented. These include sub-band ISA, Prior Subspace Analysis (PSA), and an automatic modelling and grouping technique which is used in conjunction with PSA to perform polyphonic percussion transcription. These approaches are demonstrated to be effective in the task of polyphonic percussion transcription, and PSA is also demonstrated to be capable of transcribing drums in the presence of pitched instruments

A COMPARISON OF EXTENDED SOURCE-FILTER MODELS FOR MUSICAL SIGNAL RECONSTRUCTION

China Scholarship Council (CSC)/ Queen Mary Joint PhD scholarship; Royal Academy of Engineering Research Fellowshi

Analysing multi-person timing in music and movement : event based methods

Accurate timing of movement in the hundreds of milliseconds range is a hallmark of human activities such as music and dance. Its study requires accurate measurement of the times of events (often called responses) based on the movement or acoustic record. This chapter provides a comprehensive over - view of methods developed to capture, process, analyse, and model individual and group timing [...] This chapter is structured in five main sections, as follows. We start with a review of data capture methods, working, in turn, through a low cost system to research simple tapping, complex movements, use of video, inertial measurement units, and dedicated sensorimotor synchronisation software. This is followed by a section on music performance, which includes topics on the selection of music materials, sound recording, and system latency. The identification of events in the data stream can be challenging and this topic is treated in the next section, first for movement then for music. Finally, we cover methods of analysis, including alignment of the channels, computation of between channel asynchrony errors and modelling of the data set

Schaeffer's Solfège, Percussion, Audio Descriptors: Towards an Interactive Musical System

Pierre Schaeffer's typomorphology (1966) proposes seven criteria of musical perception for the identification and qualification of sound objects, which form the basis of his musical theory. This Solfège fits well into contexts where pitch is not the dominant dimension. Relying on similarities between the practice of reduced listening and the utilization of low-level audio descriptors, we present the first version of a real-time setup in which these descriptors are applied to qualify percussive sounds. The paper describes the tools and strategies used for addressing different criteria: envelope followers with different window sizes and filtering; detection of transients and amplitude modulations; extraction and counting of spectral components; estimation of intrinsic dissonance and spectral distribution; among others. The extracted data is subjected to simple statistical analysis, producing scalar values associated with each segmented object. Finally, we present a variety of examples