528 research outputs found
Chord-Conditioned Melody Choralization with Controllable Harmonicity and Polyphonicity
Melody choralization, i.e. generating a four-part chorale based on a
user-given melody, has long been closely associated with J.S. Bach chorales.
Previous neural network-based systems rarely focus on chorale generation
conditioned on a chord progression, and none of them realised controllable
melody choralization. To enable neural networks to learn the general principles
of counterpoint from Bach's chorales, we first design a music representation
that encoded chord symbols for chord conditioning. We then propose DeepChoir, a
melody choralization system, which can generate a four-part chorale for a given
melody conditioned on a chord progression. Furthermore, with the improved
density sampling, a user can control the extent of harmonicity and
polyphonicity for the chorale generated by DeepChoir. Experimental results
reveal the effectiveness of our data representation and the controllability of
DeepChoir over harmonicity and polyphonicity. The code and generated samples
(chorales, folk songs and a symphony) of DeepChoir, and the dataset we use now
are available at https://github.com/sander-wood/deepchoir.Comment: 7 pages, 4 figures, 2 table
Unraveling Feature Extraction Mechanisms in Neural Networks
The underlying mechanism of neural networks in capturing precise knowledge
has been the subject of consistent research efforts. In this work, we propose a
theoretical approach based on Neural Tangent Kernels (NTKs) to investigate such
mechanisms. Specifically, considering the infinite network width, we
hypothesize the learning dynamics of target models may intuitively unravel the
features they acquire from training data, deepening our insights into their
internal mechanisms. We apply our approach to several fundamental models and
reveal how these models leverage statistical features during gradient descent
and how they are integrated into final decisions. We also discovered that the
choice of activation function can affect feature extraction. For instance, the
use of the \textit{ReLU} activation function could potentially introduce a bias
in features, providing a plausible explanation for its replacement with
alternative functions in recent pre-trained language models. Additionally, we
find that while self-attention and CNN models may exhibit limitations in
learning n-grams, multiplication-based models seem to excel in this area. We
verify these theoretical findings through experiments and find that they can be
applied to analyze language modeling tasks, which can be regarded as a special
variant of classification. Our contributions offer insights into the roles and
capacities of fundamental components within large language models, thereby
aiding the broader understanding of these complex systems.Comment: Accepted by EMNLP 202
TunesFormer: Forming Irish Tunes with Control Codes by Bar Patching
This paper introduces TunesFormer, an efficient Transformer-based
dual-decoder model specifically designed for the generation of melodies that
adhere to user-defined musical forms. Trained on 214,122 Irish tunes,
TunesFormer utilizes techniques including bar patching and control codes. Bar
patching reduces sequence length and generation time, while control codes guide
TunesFormer in producing melodies that conform to desired musical forms. Our
evaluation demonstrates TunesFormer's superior efficiency, being 3.22 times
faster than GPT-2 and 1.79 times faster than a model with linear complexity of
equal scale while offering comparable performance in controllability and other
metrics. TunesFormer provides a novel tool for musicians, composers, and music
enthusiasts alike to explore the vast landscape of Irish music. Our model and
code are available at https://github.com/sander-wood/tunesformer.Comment: 5 pages, 3 figures, 1 tabl
The Application of OCTA in Assessment of Anti-VEGF Therapy for Idiopathic Choroidal Neovascularization
Purpose. To assess the morphology of idiopathic choroidal neovascularization (ICNV) by optical coherence tomography angiography (OCTA) and determine the therapeutic effects of intravitreal antivascular endothelial growth factor (anti-VEGF). Method. Patients with naive ICNV were assessed by spectral domain optical coherence tomography (SD-OCT) and OCTA in this observational study. The timing of observation was before treatment, 1 day after treatment with intravitreal anti-VEGF injection, and 1 month after the treatment. The central retina thickness (CRT) on SD-OCT, selected CNV area, and flow area on OCTA were measured. Results. A total of 17 eyes from 17 patients with ICNV were included in this study. OCTA showed visible irregular choroidal neovascularization with âtree-in-budâ form on outer retinal layer. After treatment, as well as in the 1-day follow-up, CNV decreased in size from the periphery, and the vessel density was reduced. As shown on OCTA, the selected CNV area and flow area were significantly reduced compared to pretreatment. The rate of CNV vessel area changes was higher on OCTA than the changes in CRT on SD-OCT at 1-day and 1-month follow-up. Conclusion. Intravitreal injection of anti-VEGF is effective for idiopathic choroidal neovascularization, and the treatment outcomes are observable after 1 day. OCTA provides a useful approach for monitoring and evaluating the treatment of intravitreal anti-VEGF for CNV
CCOM-HuQin: an Annotated Multimodal Chinese Fiddle Performance Dataset
HuQin is a family of traditional Chinese bowed string instruments. Playing
techniques(PTs) embodied in various playing styles add abundant emotional
coloring and aesthetic feelings to HuQin performance. The complex applied
techniques make HuQin music a challenging source for fundamental MIR tasks such
as pitch analysis, transcription and score-audio alignment. In this paper, we
present a multimodal performance dataset of HuQin music that contains
audio-visual recordings of 11,992 single PT clips and 57 annotated musical
pieces of classical excerpts. We systematically describe the HuQin PT taxonomy
based on musicological theory and practical use cases. Then we introduce the
dataset creation methodology and highlight the annotation principles featuring
PTs. We analyze the statistics in different aspects to demonstrate the variety
of PTs played in HuQin subcategories and perform preliminary experiments to
show the potential applications of the dataset in various MIR tasks and
cross-cultural music studies. Finally, we propose future work to be extended on
the dataset.Comment: 15 pages, 11 figure
THash: A Practical Network Optimization Scheme for DHT-based P2P Applications
International audienceP2P platforms have been criticized because of the heavy strain that they can inflict on costly inter-domain links of network operators. It is therefore mandatory to develop network optimization schemes for controlling the load generated by a P2P platform on an operator network. While many research efforts exist on centralized tracker-based systems, in recent years multiple DHT-based P2P platforms have been widely deployed and considered as commercial services due to their scalability and fault tolerance. Finding network optimization for DHT-based P2P applications has thereby potential large practical impacts. In this paper, we present THash, a simple scheme that implements a distributed and effective network optimization for DHT systems. THash uses standard DHT put/get semantics and utilizes a triple hash method to guide the DHT clients to choose their sharing peers in proper domains. We have implemented THash in a major commercial P2P system (PPLive), using the standard ALTO/P4P protocol as the network information source. We conducted experiments over this network in real operation and observed that compared with Native DHT, THash reduced respectively by 47.4% and 67.7% the inter-PID and inter-AS traffic, while reducing the average downloading time by 14.6% to 24.5%
Evolution of the tetragonal to rhombohedral transition in (1 â x)(Bi1/2Na1/2)TiO3 â xBaTiO3 (x †7%)
(1 â x)(Bi1/2Na1/2)TiO3 â xBaTiO3 has been the most studied Pb-free piezoelectric material in the last decade; however, puzzles still remain about its phase transitions, especially around the important morphotropic phase boundary (MPB). By introducing the strain glass transition concept from the ferroelastic field, it was found that the phase transition from tetragonal (T, P4bm) to rhombohedral (R, R3c) was affected by a strain glass transition at higher temperature for x â„ 4%. In these compositions, the TâR transition was delayed or even totally suppressed and displayed huge thermal hysteresis upon cooling and heating. Also, isothermal phase transitions were predicted and realized successfully in the crossover region, where the interaction between the TâR transition and the strain glass transition was strong. Our results revealed the strain glass nature in compositions around the MPB in this important material, and also provide new clues for understanding the transition complexity in other (Bi1/2Na1/2)TiO3-based Pb-free piezoelectric materials
Network Optimization for DHT-based Applications
International audienceP2P platforms have been criticized because of the heavy strain that some P2P services can inflict on costly inter-domain links of network operators. It is therefore necessary to develop network optimization schemes for controlling the load generated by P2P platforms on an operator network. Previous focus on network optimization has been mostly on centralized tracker-based systems. However, in recent years multiple DHT-based P2P networks are widely deployed due to their scalability and fault tolerance, and these networks have even been considered as platforms for commercial services..Thereby, finding network optimization for DHT-based P2P applications has potentially large practical impacts. In this paper, we present THash, a simple scheme to implement an effective distributed network optimization for DHT systems. THash is based on standard DHT put/get semantics and utilizes a triple hash method to guide the DHT clients sharing resources with peers in proper domains. We have implemented THash in a major P2P application (PPLive) by using the standard ALTO/P4P protocol as the network information source. We conducted realistic experiments over the network and observed that compared with Native DHT, THash only generated 45.5\% and 35.7\% of inter-PID and inter-AS traffic, and at the same time shortened the average downloading time by 13.8\% to 22.1\%
Txilm: Lossy Block Compression with Salted Short Hashing
Current blockchains are restricted by the low throughput. Aimed at this
problem, we propose Txilm, a protocol that compresses the size of transaction
presentation in each block to save the bandwidth of the network. In this
protocol, a block carries short hashes of TXIDs instead of complete
transactions. Combined with the sorted transactions based on TXIDs, Txilm
realizes 80 times of data size reduction compared with the original
blockchains. We also evaluate the probability of hash collisions, and provide
methods of resolving such collisions. Finally, we design strategies to protect
against potential attacks on Txilm.Comment: 5 pages and 2 figure
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