DDR game charts generated from raw audio tracks.
problem Creating new step charts for songs without existing charts.
method Combining recurrent and convolutional neural networks for step placement and a conditional LSTM for step selection.
result Improved step charts generated from raw audio tracks.
Study the structure of a minimal chart with two crossings.
problem Enumerate minimal charts with two crossings.
method Analyze a disk not containing crossings but intersecting specific edge labels.
result Two crossings are contained in the intersection of specific edge labels.
Audio fingerprinting, also named as audio hashing, has been well-known as a powerful technique to perform audio identification and synchronization. It basically involves two major steps: fingerprint (voice pattern) design and matching search. While the first step concerns the derivation of a robust and compact audio si…
Predicts which songs will be Billboard hits using Spotify data.
problem Predicting which songs will become chart-topping hits.
method Used a dataset of 1.8 million hit and non-hit songs, extracted audio features, and tested four models (random forest achieved 88% accuracy).
result Random forest model achieved 88% accuracy in predicting Billboard song success.
Convolutional Neural Networks predict forex trends from charts.
problem Predicting forex trends from trading charts.
method Pre-process data, train CNN, evaluate model performance.
result Trades strategies can be automatically generated.
Unified detection of isolated and overlapping audio events using CNN-RNN.
problem Detecting both isolated and overlapping audio events simultaneously.
method Multi-label multi-task framework based on CNN-RNN, with sequential losses.
result Good generalization on isolated and overlapping audio event detection datasets.
The paper proposes a method to predict audio ad quality using acoustic features.
problem Improving user experience in online music streaming services by ensuring high quality audio advertisements.
method The paper proposes predicting audio ad quality using acoustic features and a proxy metric called Long Click Rate (LCR). A deep learning model is also introduced.
result The proposed deep learning model outperforms other models trained on hand-crafted features for audio ad quality prediction.
WaveGrad generates high-fidelity audio using gradient estimation.
problem Generating high-fidelity audio efficiently.
method Conditional model using score matching and diffusion models, iteratively refining a Gaussian white noise signal.
result WaveGrad can generate high-fidelity audio samples using as few as six iterations.
New system tracks musical performances in raw sheet images without preprocessing.
problem Lack of direct score position estimation in raw sheet images.
method Proposes an Audio-Conditioned U-Net architecture.
result Direct score position estimation in entire unprocessed sheet images.
This paper improves sentiment classification by combining text, audio, and video data using DCCA.
problem Improving sentiment classification accuracy using multi-modal data.
method Deep Canonical Correlation Analysis (DCCA) for combining text, audio, and video embeddings.
result One-Step DCCA outperforms current state-of-the-art in multi-modal embedding learning.
End-to-end probabilistic inference improves audio signal processing.
problem Efficiently processing large audio signals with varying characteristics.
method Formulated a spectral mixture Gaussian process model with nonstationary priors, enabling infinite-horizon Gaussian process regression.
result The method outperforms standard techniques in processing audio signals with hundreds of thousands of data points.
DiffWave generates high-fidelity audio waveforms efficiently.
problem Conditional and unconditional audio waveform generation.
method Non-autoregressive diffusion model using Markov chain synthesis.
result DiffWave produces high-quality audios in various tasks.
No minimal charts with exactly seven white vertices found.
problem Finding minimal charts with specific vertex counts.
method Investigating charts representing embedded surfaces in 4-space.
result No minimal chart with exactly seven white vertices exists.
Automated speaker fluency level assessment using machine learning.
problem Time-consuming manual evaluation of non-native English speakers' fluency levels.
method Built a dataset of labeled audio conversations, extracted features, and trained machine learning models.
result Support vector machine achieved 94.39% classification accuracy.
Paper proposes a robust audio classification method against adversarial attacks.
problem Adversarial attacks can fool machine learning models into making incorrect predictions.
method Proposes a novel SVM-based approach using DWT and SURF features.
result The proposed method provides a good balance between accuracy and resilience against adversarial attacks.
This paper studies minimal charts of a specific type to understand embedded surfaces in 4-space.
problem Investigating minimal charts of a specific type to understand embedded surfaces in 4-space.
method Analyzing charts of type (5,2) to find a minimal chart.
result Identified a minimal chart of type (5,2) representing an embedded surface in 4-space.
New method separates multiple voices in mixed audio.
problem Separating multiple simultaneous speakers in audio.
method Gated neural networks trained at multiple steps, selecting actual number of speakers.
result Outperforms current state of the art for more than two speakers.
In this paper, we give definitions of three kinds of minimal charts, and we investigate properties of minimal charts and establish fundamental theorems characterizing minimal charts. To classify charts with two or three crossings we use the fundamental theorems. In the future paper, we give an numeration of the charts …
No minimal chart of type (7) exists.
problem Characterizing minimal charts of specific types.
method Analyzing charts based on edge labels and white vertex counts.
result There is no minimal chart of type (7).
No minimal chart of type (4,3) exists in 4-space.
problem Existence of minimal charts of specific type in 4-space.
method Investigation of charts and their properties in 4-space.
result No minimal chart of type (4,3) exists.
Paper classifies surface-links using charts with specific properties.
problem Classifying surface-links with specific charts.
method Using quandle colorings to differentiate charts representing different surface-links.
result Charts in the second class represent different surface-links.
The paper studies 4-charts with three crossings and their equivalence to a specific knot.
problem Investigating the structure and equivalence of 4-charts with three crossings.
method Examining charts as oriented labeled graphs in a disk, focusing on acyclic components and equivalence through label-orientation-reflection.
result Any linear minimal 4-chart with three crossings is equivalent to a 2-twist spun trefoil knot.
No minimal chart of type (2,3,2) exists.
problem Characterizing minimal charts of specific types.
method Analyzing charts with given edge label constraints.
result No minimal chart of type (2,3,2) exists.
No minimal chart of type (3,2,2) exists.
problem Characterizing minimal charts of specific types.
method Analyzing charts of type (3,2,2) and proving non-existence.
result There is no minimal chart of type (3,2,2).
End-to-end ASR error detection using audio-transcript entailment.
problem Detecting transcription errors in ASR systems to prevent error propagation.
method Proposes a novel end-to-end approach using audio-transcript entailment, with acoustic and linguistic encoders.
result Achieves CER of 26.2% on all transcription errors and 23% on medical errors specifically, improving by 12% and 15.4% respectively over a strong baseline.
A new SVDD-based control chart for high-frequency multivariate data.
problem Challenges in interpreting kernel distance plots for high-frequency multivariate data.
method Proposes a new SVDD-based control chart, KT chart, to track process variation and central tendency. result Demonstrates successful use of KT chart on the Tennessee Eastman process data. Minimal charts of specific type contain unique subgraphs.
problem Characterizing minimal charts of type (m;2,3,2). method Analyzing the structure of charts and their subgraphs.
result Each of Γm+1 and Γm+2 contains one of three specific subgraphs. Simplifies surface-knots using chart moves involving black vertices.
problem Simplifying branched covering surface-knots.
method Chart moves involving black vertices to simplify surface-knots.
result Properties of simplified branched covering surface-knots with branch points.
In this paper, we shall show a condition for that a chart is C-move equivalent to the product of two charts, the union of two charts Γ∗ and Γ∗∗ which are contained in disks D∗ and D∗∗ with D∗∩D∗∗=∅.
Minimal charts of type (3,3) are equivalent to a specific subchart.
problem Characterizing minimal charts of type (3,3).
method Analyzing subgraphs and C-move equivalence.
result Minimal charts of type (3,3) are equivalent to a specific subchart.
Simplifies surface-knots by adding 1-handles with chart loops.
problem Complexity of branched covering surface-knots.
method Adding 1-handles with chart loops to simplify charts.
result Properties of simplified charts are investigated.
This research aims to develop robust audio spoofing detection methods that work across various spoofing techniques.
problem Detecting audio spoofing attacks in speaker verification systems.
method Examined traditional and machine learned audio features for robust spoofing detection.
result Fused models based on both known and machine learned features achieve comparable performance with an EER of 12.
This paper studies the structure of a specific neighborhood in minimal 2-crossing charts.
problem Understanding the structure of a minimal 2-crossing chart with specific neighborhoods.
method Analyzes the neighborhoods of Γα∪Γβ and proposes a normal form for 2-crossing minimal n-charts. result Proposes a normal form for 2-crossing minimal n-charts. A method to fix radius distortion in generative models on curved spaces.
problem Distortion in geodesic radius measurements across different charts on Riemannian manifolds.
method Radial Compensation (RC) adjusts the tangent-space base distribution to match the geodesic radius law, improving model stability and interpretability.
result RC ensures that the model's geodesic radius matches the intended distribution, improving numerical stability and curvature interpretation.
Paper improves channel charting using autoencoders with spatial constraints.
problem Improving logical positioning of UEs using channel-state information.
method Representation-constrained autoencoders to enhance channel charts.
result Improved quality of learned channel charts for UE positioning.
Study uses CNN and LSTM to recognize stock chart patterns.
problem Recognizing stock chart patterns for trading.
method Used CNN and LSTM neural networks on historical stock data.
result Obtained accuracies for recognizing two common chart patterns.
A 2-dimensional braid over an oriented surface-knot F is presented by a graph called a chart on a surface diagram of F. We consider 2-dimensional braids obtained by an addition of 1-handles equipped with chart loops. We introduce moves of 1-handles with chart loops, called 1-handle moves, and we investigate how muc…
A new VAD method uses respiration patterns from video to detect speech.
problem Improving VAD performance in noisy audio recordings.
method Extract respiration patterns from video, use neural models to detect speech.
result Efficacy demonstrated through experiments on real acoustic environments.
New surfaces in 4-ball constructed from knits, described by charts.
problem Constructing surfaces in 4-ball from knits.
method Introducing knitted surfaces, describing them with BMW charts.
result Every compact surface in 4-ball is ambiently isotopic to a knitted surface.
The paper finds charts for Legendrian curves in complex contact manifolds.
problem Finding charts for Legendrian curves in complex contact manifolds.
method Holomorphic Darboux charts and approximations of Legendrian immersions.
result Holomorphic Legendrian immersions can be approximated by embeddings.
Chart autoencoders learn latent features preserving manifold topology and geometry, with robust denoising capabilities.
problem Learning low-dimensional latent features of high-dimensional data sampled near a manifold.
method Chart autoencoders encode data into latent features on charts, preserving manifold topology and geometry.
result Chart autoencoders achieve a squared generalization error of n−d+22log4n under proper network architectures. Chart descriptions are a graphic method to describe monodromy representations of various topological objects. Here we introduce a chart description for hyperelliptic Lefschetz fibrations, and show that any hyperelliptic Lefschetz fibration can be stabilized by fiber-sum with certain basic Lefschetz fibrations.
We investigate minimal charts with loops, a simple closed curve consisting of edges of label m containing exactly one white vertex. We shall show that there does not exist any loop in a minimal chart with exactly seven white vertices in this paper.
CC charts radio geometry for user localization.
problem Locating users in radio environments.
method Unsupervised learning from passive CSI.
result Extracts channel features for spatial comparison.
Introduces Hurewicz fibrations for embedding maps of orbifold charts.
problem No specific problem stated; focuses on new concept definition.
method Defines E-fibration embedding and studies its properties.
result Introduces and studies properties of E-fibration embedding.
Deep learning predicts stock market trends using candlestick charts.
problem Predicting stock market prices with multiple influencing factors.
method Used Deep Convolutional Neural Networks and candlestick charts.
result 92.2% and 92.1% accuracy for Taiwan and Indonesian stock markets.
Chart descriptions are a graphic method to describe monodromy representations of various topological objects. Here we introduce a chart description for genus-two Lefschetz fibrations, and show that any genus-two Lefschetz fibration can be stabilized by fiber-sum with certain basic Lefschetz fibrations.
Paper proposes MTL for weakly labelled SED, improving performance with 2-step attention.
problem Weakly labelled sound event detection.
method Multi-Task Learning framework with 2-step Attention Pooling.
result Improved SED performance with 22.3%, 12.8%, 5.9% gains at 0, 10, 20 dB SNR.