The acts of speaking and singing are different phenomena displaying distinct characteristics. The classification and distinction of these voice acts is vastly approached utilizing voice audio ...recordings and microphones. The use of audio recordings, however, can become challenging and computationally expensive due to the complexity of the voice signal. The research presented in this paper seeks to address this issue by implementing a deep learning classifier of speaking and singing voices based on bioimpedance measurement in replacement of audio recordings. In addition, the proposed research aims to develop a real-time voice act classification for the integration with voice-to-MIDI conversion. For such purposes, a system was designed, implemented, and tested using electroglottographic signals, Mel Frequency Cepstral Coefficients, and a deep neural network. The lack of datasets for the training of the model was tackled by creating a dedicated dataset 7200 bioimpedance measurement of both singing and speaking. The use of bioimpedance measurements allows to deliver high classification accuracy whilst keeping low computational needs for both preprocessing and classification. These characteristics, in turn, allows a fast deployment of the system for near-real-time applications. After the training, the system was broadly tested achieving a testing accuracy of 92% to 94%.
This study explores the integration of music and technology, illustrating their potential to collaboratively push the boundaries of musical exploration. Despite traditionally being viewed as ...unrelated, the combination of these two fields can significantly contribute to the progress of musical development. This study uses advanced computational methods to build a dataset filled with symbolic musical sequences that belong to a specific genre. This dataset is shown to be highly accurate and provides a detailed analysis of frequencies when examined closely, highlighting its quality and depth. We subject our dataset to comparative analysis with the renowned MAESTRO dataset, employing chromagrams to examine audio signals, rhythms, chords, solos, and note patterns in MIDI format through a variety of methods. This comparison underscores the superior quality of our sequences relative to those in the MAESTRO dataset, emphasizing the meticulousness of our sequence creation process. Moreover, we conduct internal evaluations of our dataset using both three-dimensional and two-dimensional approaches to melody representation, confirming its viability for future scholarly work. This effort seeks to enhance the music field by integrating computer science insights and methodologies, expanding the scope for future music technology research. It highlights the collaborative potential between musical creativity and technological advances in ongoing studies.
Joseph Delteil à la recherche de l’Occitanie Terral, Hervé
Lengas (Montpellier, Centre d'études occitanes, Université Paul Valéry),
11/2021, Volume:
90, Issue:
90
Journal Article
Peer reviewed
Open access
Joseph Delteil (1894-1978), a French-speaking writer from Aude, claims to have been born in Villar-en-Val (Aude) in the garrigue (more likely in a village bedroom), a few dozen kilometers from the ...Big Blue. At various times in his work, Delteil set out regular milestones for understanding the "Midi", whose different facets he explored in terms of both landscape and history.
Composing music is an inspired yet challenging task, in that the process involves many considerations such as assigning pitches, determining rhythm, and arranging accompaniment. Algorithmic ...composition aims to develop algorithms for music composition. Recently, algorithmic composition using artificial intelligence technologies received considerable attention. In particular, computational intelligence is widely used and achieves promising results in the creation of music. This paper attempts to provide a survey on the music generation based on the Monte Carlo (MC) algorithm. First, transform the MIDI music format files to digital data. Among these data, use the logistic fitting method to fit the time series, obtain the time distribution regular pattern. Except for time series, the converted data also includes duration, pitch, and velocity. Second, using MC simulation to deal with them summed up their distribution law respectively. The two main control parameters are the value of discrete sampling and standard deviation. Processing the above parameters and converting the data to MIDI file, then compared with the output generated by LSTM neural network, evaluate the music comprehensively.
RESUMENEn la actualidad existe una amplia variedad de estilos musicales que incluyen el sintetizador en su pro- ceso de creación. El uso de este instrumento en la industria musical se ha extendido ...de tal modo que consideramos necesario llevar a cabo una investigación exploratoria para examinar cómo esta ten- dencia se reflejaba en las aulas de educación musical. El objetivo de la investigación se centró, pues, en indagar acerca del conocimiento y el uso pedagógico del sintetizador en los diversos niveles de la educación musical de Cataluña. Para ello, se realizaron entrevistas semiestructuradas a 8 expertos en tecnología y educación musical. La información fue analizada mediante la técnica del análisis temá- tico y los resultados obtenidos revelaron que: (1) las experiencias con el sintetizador en la educación musical son escasas; (2) los motivos por los que el sintetizador no se usa regularmente en la educa- ción musical son variados, destacando la falta de formación del profesorado, la falta de tiempo en los currículos y la falta de materiales didácticos; (3) las propuestas de los expertos para la didáctica del sintetizador muestran puntos de acuerdo y discrepancias, y (4) las opiniones de los expertos muestran la importancia de una miscelánea de temas en torno al sintetizador en el contexto educativo actual, la importancia del autodidactismo en el aprendizaje del sintetizador, las TIC y la música. A partir de este análisis, podemos concluir que (1) es preciso formar al profesorado en cuanto al conocimiento y uso pedagógico del sintetizador, (2) es necesario poner al alcance del profesorado materiales didácticos y orientaciones metodológicas, y (3) el uso apropiado del sintetizador puede dar al alumnado la oportu- nidad de experimentar con sonidos que le son familiares, garantizando que el timbre reciba la misma atención en la educación musical que en la industria musical.
This open access book presents the proceedings of the 10th Machine Intelligence and Digital Interaction Conference. Artificial intelligence (AI) is rapidly affecting more aspects of our lives as a ...result of significant advancements in its research and the widespread usage of interactive technologies. This has led to the birth of several new social phenomena. Many nations have been working to comprehend these phenomena and discover solutions for moving artificial intelligence development in the proper direction to benefit individuals and communities at large. These efforts necessitate multidisciplinary approaches, encompassing not only the scientific fields involved in the creation of artificial intelligence and human–computer interaction but also strong collaboration between academics and practitioners. Because of this, the primary objective of the MIDI conference, which was conducted online on December 13–15, 2022, is to combine two up until recently distinct disciplines of research—artificial intelligence and human–technology interaction.
Voice-to-MIDI real-time conversion is a challenging problem that comes with a series of obstacles and complications. The main issue is the tracking of the human voice pitch. Extracting the voice ...fundamental frequency can be inaccurate and highly computationally exacting due to the spectral complexity of voice signals. In addition, on account of microphone usage, the presence of environmental noise can further affect voice processing. An analysis of the current research and status of the market shows a plethora of voice-to-MIDI implementations revolving around the processing of audio signals deriving from microphones. This paper addresses the above-mentioned issues by implementing a novel experimental method where electroglottography is employed instead of microphones as a source for pitch-tracking. In the proposed system, the signal is processed and converted through an embedded hardware device. The use of electroglottography improves both the accuracy of pitch evaluation and the ease of voice information processing; firstly, it provides a direct measurement of the vocal folds' activity and, secondly, it bypasses the interferences caused by external sound sources. This allows the extraction of a simpler and cleaner signal that yields a more effective evaluation of the fundamental frequency during phonation. The proposed method delivers a faster and less computationally demanding conversion thus in turn, allowing for an efficacious real-time voice-to-MIDI conversion.
This book is open access, which means that you have free and unlimited access. This book presents the Proceedings of the 9th Machine Intelligence and Digital Interaction Conference. Significant ...progress in the development of artificial intelligence (AI) and its wider use in many interactive products are quickly transforming further areas of our life, which results in the emergence of various new social phenomena. Many countries have been making efforts to understand these phenomena and find answers on how to put the development of artificial intelligence on the right track to support the common good of people and societies. These attempts require interdisciplinary actions, covering not only science disciplines involved in the development of artificial intelligence and human-computer interaction but also close cooperation between researchers and practitioners. For this reason, the main goal of the MIDI conference held on 9-10.12.2021 as a virtual event is to integrate two, until recently, independent fields of research in computer science: broadly understood artificial intelligence and human-technology interaction.
Two aerobic, Gram-stain-negative, motile, mesophilic, rod-shaped and catalase-positive bacterial strains designated AF9R3
T
and GN2-R2
T
were isolated from flowers collected in the Republic of Korea. ...Strain AF9R3
T
grew at 4–33 °C, pH 4.0–9.0 and with 0–1 % NaCl (w/v), and strain GN2-R2
T
grew at 10–33 °C, pH 4.0–9.0 and with 0–1 % NaCl (w/v). Phylogenetic analysis on the basis of 16S rRNA gene sequences indicated that strains AF9R3
T
and GN2-R2
T
belonged to the genera
Duganella
and
Massilia
, respectively, showing high sequence similarity to
Duganella levis
CY42W
T
(99.4 %) and
Massilia putida
6 NM-7
T
(98.0 %), respectively. Both strains contained summed feature 3 (C
16 : 1
ω
7
c
and/or C
16 : 1
ω
6
c
) and C
16 : 0
as the major fatty acids, and ubiquinone Q-8 as the predominant quinone. Strain AF9R3
T
had diphosphatidylglycerol, phosphatidylglycerol and phosphatidylethanolamine, and strain GN2-R2
T
comprised diphosphatidylglycerol, phosphatidylglycerol, phosphatidylethanolamine and an unidentified phospholipid as the major polar lipids. Orthologous average nucleotide identity and digital DNA–DNA hybridization values of strain AF9R3
T
to its closest relative
D. levis
CY42W
T
were 92.6 and 56.5 %, and those of strain GN2-R2
T
to its closest relative
M. putida
6 NM-7
T
were 81.4 and 24.8 %. Based on genotypic and phenotypic data, strains AF9R3
T
and GN2-R2
T
are considered to represent novel species of the genus
Duganella
and
Massilia
, respectively, for which the names
Duganella dendranthematis
sp. nov. (type strain AF9R3
T
=KACC 21258
T
=NBRC 114510
T
) and
Massilia forsythiae
sp. nov. (type strain GN2-R2
T
=KACC 21261
T
=NBRC 114511
T
) have been proposed.
Professional musicians are often exposed to high noise levels and thus face the risk of noise-induced hearing loss. Yet, adoption rates for hearing protection among musicians are low. Previous ...surveys indicate that the chief concern is the effect of hearing protection use on performance. However, few studies have investigated actual changes in performance when wearing hearing protection. We report an experiment investigating differences in pianists’ performance and experience with and without hearing protection. We compare the effect of foam earplugs and musician earplugs, designed to preserve sound quality with a flat frequency response. The analysis revealed that participants performed overall more loudly with the foam earplugs than with the musician earplugs, and in turn performances with the musician earplugs were louder than the open condition, indicating a compensatory effect. However, this effect was stronger for novel excerpts than for familiar excerpts. No effect was observed on dynamic range. Furthermore, we observed an acclimatization effect, whereby the effect of hearing protection use, observed on the first performance, decreased on the second performance. In terms of experience, participants reported changes in coloration, difficulties gauging dynamics and articulation, and increased effort required when performing with hearing protection. These effects were more pronounced when wearing the foam earplugs, and the participants reported finding the musician earplugs more comfortable to wear and play with. In conclusion, hearing protection use affects pianists’ performance particularly in terms of dynamics and their experience more so in terms of coloration. But the effects are less marked for familiar pieces and after repetition, suggesting that pianists can quickly adjust their playing when playing familiar pieces with hearing protection.
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