The Temperament Police: The Truth, the Ground Truth, and Nothing but the Truth

The tuning system of a keyboard instrument is chosen so that frequently used musical intervals sound as consonant as possible. Temperament refers to the compromise arising from the fact that not all intervals can be maximally consonant simultaneously. Recent work showed that it is possible to estimate temperament from audio recordings with no prior knowledge of the musical score, using a conservative (high precision, low recall) automatic transcription algorithm followed by frequency estimation using quadratic interpolation and bias correction from the log magnitude spectrum. In this paper we develop a harpsichord-specific transcription system to analyse over 500 recordings of solo harpsichord music for which the temperament is specified on the CD sleeve notes. We compare the measured temperaments with the annotations and discuss the differences between temperament as a theoretical construct and as a practical issue for professional performers and tuners. The implications are that ground truth is not always scientific truth, and that content-based analysis has an important role in the study of historical performance practice. 1

In Seeking a Definition of Mash: Attitude in Musical Style

“Mash” is a term used to describe one of the most recent major style shifts in the iconic American string band music known as bluegrass. Beginning in the 1990s, the bluegrass sound began to evolve, and ‘mash’ worked its way into the genre as a descriptor of a certain sound. Though a handful of scholars have discussed the social stigmas of the style, no one yet has investigated the simple musical question about mash: what is it? The purpose of this thesis is to define mash in its musical form through a combination of transcription methods and extensive analysis. Through this research, a recurring set of musical phenomena is identified in the repertoire, related to rhythms, melody, and modality. This study shows the relationship between the downbeat and this music, and identifies and articulates the musical characteristics that define mash as a unique style of bluegrass

Multiple-instrument polyphonic music transcription using a temporally constrained shift-invariant model

A method for automatic transcription of polyphonic music is proposed in this work that models the temporal evolution of musical tones. The model extends the shift-invariant probabilistic latent component analysis method by supporting the use of spectral templates that correspond to sound states such as attack, sustain, and decay. The order of these templates is controlled using hidden Markov model-based temporal constraints. In addition, the model can exploit multiple templates per pitch and instrument source. The shift-invariant aspect of the model makes it suitable for music signals that exhibit frequency modulations or tuning changes. Pitch-wise hidden Markov models are also utilized in a postprocessing step for note tracking. For training, sound state templates were extracted for various orchestral instruments using isolated note samples. The proposed transcription system was tested on multiple-instrument recordings from various datasets. Experimental results show that the proposed model is superior to a non-temporally constrained model and also outperforms various state-of-the-art transcription systems for the same experiment

“The Theory is Not Yet Music”: An Analysis of Pierre Schaeffer’s \u3ci\u3eEtude aux allures\u3c/i\u3e

Throughout his career, Pierre Schaeffer composed several sound works to test and inspire his evolving musical theories. By composing with edited sound recordings, rather than traditional musical instruments, he hoped to discover new ways of creating musical structures based on sound parameters other than pitch. This study is an analysis of Schaeffer’s sound work Etude aux allures. This Etude examines the musical potential of the sound parameter allure, which is Schaeffer’s term for the pulsed modulation of pitch, volume, or other sound parameters. Without the existence of a standardized analytical methodology, the Etude is viewed from several perspectives. First, a typomorphological analysis of the sound-work is presented in the form of a transcription using Lasse Thoresen’s Aural Sonology graphic notational symbols. The symbols represent the salient characteristics of each sound object in the Etude. Next, the piece is compared to a hypothetical compositional plan from Schaeffer’s Treatise on Musical Objects. This comparison explains why the sounds in the piece might have been selected. Finally, the role of the sound characteristic allure is analyzed. I argue that the Etude is an example of what Schaeffer called a Teaching Reel, intended to help listeners focus their attention on the allure of each sound object

Frequency shifting approach towards textual transcription of heartbeat sounds

Auscultation is an approach for diagnosing many cardiovascular problems. Automatic analysis of heartbeat sounds and extraction of its audio features can assist physicians towards diagnosing diseases. Textual transcription allows recording a continuous heart sound stream using a text format which can be stored in very small memory in comparison with other audio formats. In addition, a text-based data allows applying indexing and searching techniques to access to the critical events. Hence, the transcribed heartbeat sounds provides useful information to monitor the behavior of a patient for the long duration of time. This paper proposes a frequency shifting method in order to improve the performance of the transcription. The main objective of this study is to transfer the heartbeat sounds to the music domain. The proposed technique is tested with 100 samples which were recorded from different heart diseases categories. The observed results show that, the proposed shifting method significantly improves the performance of the transcription

A temporally-constrained convolutive probabilistic model for pitch detection

A method for pitch detection which models the temporal evolution of musical sounds is presented in this paper. The proposed model is based on shift-invariant probabilistic latent component analysis, constrained by a hidden Markov model. The time-frequency representation of a produced musical note can be expressed by the model as a temporal sequence of spectral templates which can also be shifted over log-frequency. Thus, this approach can be effectively used for pitch detection in music signals that contain amplitude and frequency modulations. Experiments were performed using extracted sequences of spectral templates on monophonic music excerpts, where the proposed model outperforms a non-temporally constrained convolutive model for pitch detection. Finally, future directions are given for multipitch extensions of the proposed model