Curating and annotating a collection of traditional Irish flute recordings to facilitate stylistic analysis

This paper presents the curation and annotation of a collection of traditional Irish flute recordings to facilitate the analysis of stylistic characteristics. We introduce the structure of Irish tunes, types of tunes and the ornamentation, which is a decisive stylistic determinant in Irish traditional music. We identify seminal recordings of prominent flute players and provide information related to players and their style and geographical context. We describe the process of manual annotation of the audio data. The annotations consist of the onsets of notes, note frequency and identity of notes and ornaments. We also present initial stylistic analysis of individual players in terms of ornamentation and phrasing and provide a variety of statistics for the data. The ability to accurately represent and analyse stylistic features such as ornaments allow for the development of discourse related to several key ethnomusicological questions surrounding music making, musical heritage and cultural change

On the Opportunities of the Soundscape Approach to Revitalise Acoustics Training in Undergraduate Architectural Courses

Soundscape research has been gaining prominence in studies on the built environment. The soundscape concept is defined as the acoustic environment as perceived and/or understood by a person in context. Compared with traditional building acoustics, the soundscape concept brings interesting perspectives—but also challenges—for undergraduate architectural curricula, where it tries to strike a balance between qualitative and quantitative methodologies, a theoretical approach that in the context of soundscape studies it is often referred to as ‘triangulation’. Starting from real-world higher education courses, the aim of this paper is to examine how the soundscape approach can be integrated into teaching building acoustics at the undergraduate level in architectural courses. Methods such as soundwalks, acoustic measurements, and computational simulations that are commonly used in soundscape research are introduced in educational projects as tools for students to experience, analyse, and articulate the narrative around the sound environment to inform their design concepts and details

Combining Gestural and Audio Approaches to the Classification of Violin Bow Strokes

This paper details a brief exploration of methods by which gestural and audio based approaches may be used in the classification of violin performances. These are based upon a multimodal dataset. Onsets are derived from audio signals and used to segment synchronous gestural recordings, allowing for the classification of individual bow strokes utilising data of either type—or both. Classification accuracies for the purposes of participant identification ranged between 71.06% and 91.35% for various data type combinations. Classification accuracies for the identification of bowing technique were typically lower, ranging between 53.33% and 77.35%. The findings of this paper inform a number of recommendations for future work. These are to be considered in the development of a principally similar dataset, for the analysis of traditional fiddle playing styles

Improved onset detection for traditional flute recordings using convolutional neural networks

The usage of ornaments is key attribute that defines the style of a flute performances within the genre of Irish Traditional Music (ITM). Automated analysis of ornaments in ITM would allow for the musicological investigation of a player’s style and would be a useful feature in the analysis of trends within large corpora of ITM music. As ornament onsets are short and subtle variations within an analysed signal, they are substantially more difficult to detect than longer notes. This paper addresses the topic of onset detection for notes, ornaments and breaths in ITM. We propose a new onset detection method based on a convolutional neural network (CNN) trained solely on flute recordings of ITM. The presented method is evaluated alongside a state-of-the-art gen eralised onset detection method using a corpus of 79 full-length solo flute recordings. The results demonstrate that the proposed system outperforms the generalised system over a range of musi cal patterns idiomatic of the genre

Automatied detection of single- and multi-note ornaments in Irish traditional flute playing

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Note, Cut and Strike Detection for Traditional Irish Flute Recordings

This paper addresses the topic of note, cut and strike detection inIrish traditional music (ITM). In order to do this we first evaluate state of the art onset detection methods for identifying note boundaries. Our method utilises the results from manually and automatically segmented flute recordings. We then demonstrate how this information may be utilised for the detection of notes and single note articulations idiomatic of this genre for the purposes of player style identification. Results for manually annotated onsets achieve 86%, 70% and 74% accuracies for note, cut and strike classification respectively. Results for automatically segmented recordings are considerably, lower therefore we perform an analysis of the onset detection results per event class to establish which musical patterns contain the most errors

Computational analysis of style in Irish traditional flute playing

The wooden flute is a common melodic instrument used in Irish traditional music (ITM). A player’s style is a personal interpretation of a traditional melody reflecting technical skill, education, heritage and influences. Mastery of the instrument is reflected in the ability to individualise a tune in real-time using ornamentation, dynamics, phrasing and changes in timbre. The aim of this thesis is to develop automated analysis tools for stylistic traits in ITM flute performances. This is achieved through specialised computational methods capable of note onset detection, ornament detection and player recognition. Parameterisation of these tools is informed by ethnomusicological research into how ITM is made on the flute. This discussion covers the instrument, its operation and history and an overview of the ITM timeline. The use of computational analysis in the definition of stylistic differences between players is intended to offer objective measurements for ethnomusicology research and provide educative value for practitioners. To train the proposed systems, two corpora have been created. The first is comprised of released recordings with 18,000 annotated events including pitch, timing and note type information. The second dataset was specifically recorded to allow comparative studies in a more controlled manner. It is comprised of recordings of timed and untimed versions of the same set of popular tunes as performed by six professional players. Using these datasets, four evaluations were conducted to determine the performance of the proposed systems. The proposed note onset detection system results in an F-measure of 88.5, which is higher than current state of the art systems. The ornament detection system achieves a mean accuracy of 84% across a range of contexts, outperforming leading generalised systems. The player recognition system is capable of identifying a single player with an accuracy of 90%. This demonstrates the worth of the proposed systems, highlighting the importance of style-specific training of models and confirming the need for historical and musicological domain knowledge

Combining Gestural and Audio Approaches to the Classification of Violin Bow Strokes

This paper details a brief exploration of methods by which gestural and audio based approaches may be used in the classification of violin performances. These are based upon a multimodal dataset. Onsets are derived from audio signals and used to segment synchronous gestural recordings, allowing for the classification of individual bow strokes utilising data of either type—or both. Classification accuracies for the purposes of participant identification ranged between 71.06% and 91.35% for various data type combinations. Classification accuracies for the identification of bowing technique were typically lower, ranging between 53.33% and 77.35%. The findings of this paper inform a number of recommendations for future work. These are to be considered in the development of a principally similar dataset, for the analysis of traditional fiddle playing styles

An in-situ investigation of office soundscape perceptual evaluation methodologies

The importance of acoustics in open-plan offices is well documented, with studies highlighting associations between acoustical characteristics and job satisfaction, productivity, and well-being

An in-situ investigation of office soundscape perceptual evaluation methodologies

The importance of acoustics in open-plan offices is well documented, with studies highlighting associations between acoustical characteristics and job satisfaction, productivity, and well-being