464 research outputs found
Multimodal music information processing and retrieval: survey and future challenges
Towards improving the performance in various music information processing
tasks, recent studies exploit different modalities able to capture diverse
aspects of music. Such modalities include audio recordings, symbolic music
scores, mid-level representations, motion, and gestural data, video recordings,
editorial or cultural tags, lyrics and album cover arts. This paper critically
reviews the various approaches adopted in Music Information Processing and
Retrieval and highlights how multimodal algorithms can help Music Computing
applications. First, we categorize the related literature based on the
application they address. Subsequently, we analyze existing information fusion
approaches, and we conclude with the set of challenges that Music Information
Retrieval and Sound and Music Computing research communities should focus in
the next years
Graph based representation of the music symbolic level. A music information retrieval application
In this work, a new music symbolic level representation system is described. It has been tested in two information retrieval tasks concerning similarity between segments of music and genre detection of a given segment. It could include both harmonic and contrapuntal informations. Moreover, a new large dataset consisting of more than 5000 leadsheets is presented, with meta informations taken from different web databases, including author information, year of first performance, lyrics, genre, etc.ope
Variational Autoencoders for Anomaly Detection in Respiratory Sounds
This paper proposes a weakly-supervised machine learning-based approach
aiming at a tool to alert patients about possible respiratory diseases. Various
types of pathologies may affect the respiratory system, potentially leading to
severe diseases and, in certain cases, death. In general, effective prevention
practices are considered as major actors towards the improvement of the
patient's health condition. The proposed method strives to realize an easily
accessible tool for the automatic diagnosis of respiratory diseases.
Specifically, the method leverages Variational Autoencoder architectures
permitting the usage of training pipelines of limited complexity and relatively
small-sized datasets. Importantly, it offers an accuracy of 57 %, which is in
line with the existing strongly-supervised approaches.Comment: Published at ICANN 202
The role of autophagy in liver epithelial cells and its Impact on systemic homeostasis
Autophagy plays a role in several physiological and pathological processes as it controls
the turnover rate of cellular components and influences cellular homeostasis. The liver plays a
central role in controlling organismsâ metabolism, regulating glucose storage, plasma proteins and
bile synthesis and the removal of toxic substances. Liver functions are particularly sensitive to
autophagy modulation. In this review we summarize studies investigating how autophagy
influences the hepatic metabolism, focusing on fat accumulation and lipids turnover. We also
describe how autophagy affects bile production and the scavenger function within the complex
homeostasis of the liver. We underline the role of hepatic autophagy in counteracting the metabolic
syndrome and the associated cardiovascular risk. Finally, we highlight recent reports demonstrating
how the autophagy occurring within the liver may affect skeletal muscle homeostasis as well as
different extrahepatic solid tumors, such as melanoma
Neonatal Encephalopathy and SIADH during RSV Infection
Abstract
ObjectiveâThis report discusses the neurological involvement in respiratory syncytial virus (RSV) infection in neonates.
Study DesignâWe present a case report of a 2-month-old infant affected by a bronchiolitis RSV-positive, with syndrome of inappropriate antidiuretic hormone secretion (SIADH) correlated seizure and encephalopathy.
ResultsâRSV infection can be associated as a serious disease in newborns involving the central nervous system (CNS) and causing seizures or acute encephalopathy. RSV may be also responsible for SIADH and seizures associated with hyponatremia. The RSV related encephalopathy could be caused by different mechanisms, such as direct viral invasion of the CNS or by indirect mechanism mediated by inflammatory cytokines. In addition, it can be favored by severe hyponatremia and SIADH that can cause cerebral edema. Some studies highlight that this virus-related encephalopathy lead to sudden infant death syndrome.
ConclusionâIn presence of neurological involvement during RSV-infection must be taken in consideration to performing instrumental test to detect cerebral edema. In addiction could be useful to dose inflammatory cytokines, and to consider the immune-modulatory therapy
Optimizing Feature Extraction for Symbolic Music
This paper presents a comprehensive investigation of existing feature
extraction tools for symbolic music and contrasts their performance to
determine the set of features that best characterizes the musical style of a
given music score. In this regard, we propose a novel feature extraction tool,
named musif, and evaluate its efficacy on various repertoires and file formats,
including MIDI, MusicXML, and **kern. Musif approximates existing tools such as
jSymbolic and music21 in terms of computational efficiency while attempting to
enhance the usability for custom feature development. The proposed tool also
enhances classification accuracy when combined with other sets of features. We
demonstrate the contribution of each set of features and the computational
resources they require. Our findings indicate that the optimal tool for feature
extraction is a combination of the best features from each tool rather than
those of a single one. To facilitate future research in music information
retrieval, we release the source code of the tool and benchmarks.Comment: Published at ISMIR 202
- âŠ