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Found 29 papers, 11 papers with code
MegaTTS 3: Sparse Alignment Enhanced Latent Diffusion Transformer for Zero-Shot Speech Synthesis
While recent zero-shot text-to-speech (TTS) models have significantly improved speech quality and expressiveness, mainstream systems still suffer from issues related to speech-text alignment modeling: 1) models without explicit speech-text alignment modeling exhibit less robustness, especially for hard sentences in practical applications; 2) predefined alignment-based models suffer from naturalness constraints of forced alignments.
A Learnable Multi-views Contrastive Framework with Reconstruction Discrepancy for Medical Time-Series
In medical time series disease diagnosis, two key challenges are identified. First, the high annotation cost of medical data leads to overfitting in models trained on label-limited, single-center datasets.
GaussianMarker: Uncertainty-Aware Copyright Protection of 3D Gaussian Splatting
3D Gaussian Splatting (3DGS) has become a crucial method for acquiring 3D assets.
MuVi: Video-to-Music Generation with Semantic Alignment and Rhythmic Synchronization
Generating music that aligns with the visual content of a video has been a challenging task, as it requires a deep understanding of visual semantics and involves generating music whose melody, rhythm, and dynamics harmonize with the visual narratives.
TCSinger: Zero-Shot Singing Voice Synthesis with Style Transfer and Multi-Level Style Control
To address these challenges, we introduce TCSinger, the first zero-shot SVS model for style transfer across cross-lingual speech and singing styles, along with multi-level style control.
GTSinger: A Global Multi-Technique Singing Corpus with Realistic Music Scores for All Singing Tasks
The scarcity of high-quality and multi-task singing datasets significantly hinders the development of diverse controllable and personalized singing tasks, as existing singing datasets suffer from low quality, limited diversity of languages and singers, absence of multi-technique information and realistic music scores, and poor task suitability.
Distributionally Robust Stochastic Data-Driven Predictive Control with Optimized Feedback Gain
We consider the problem of direct data-driven predictive control for unknown stochastic linear time-invariant (LTI) systems with partial state observation.
WavTokenizer: an Efficient Acoustic Discrete Codec Tokenizer for Audio Language Modeling
Despite the reduced number of tokens, WavTokenizer achieves state-of-the-art reconstruction quality with outstanding UTMOS scores and inherently contains richer semantic information.
Accompanied Singing Voice Synthesis with Fully Text-controlled Melody
Text-to-song (TTSong) is a music generation task that synthesizes accompanied singing voices.
WindowMixer: Intra-Window and Inter-Window Modeling for Time Series Forecasting
Time series forecasting (TSF) is crucial in fields like economic forecasting, weather prediction, traffic flow analysis, and public health surveillance.
Self-Supervised Singing Voice Pre-Training towards Speech-to-Singing Conversion
We adopt discrete-unit random resampling and pitch corruption strategies, enabling training with unpaired singing data and thus mitigating the issue of data scarcity.
Frieren: Efficient Video-to-Audio Generation Network with Rectified Flow Matching
By employing a non-autoregressive vector field estimator based on a feed-forward transformer and channel-level cross-modal feature fusion with strong temporal alignment, our model generates audio that is highly synchronized with the input video.
Ranked #4 on
Video-to-Sound Generation
on VGG-Sound
FAITH: Frequency-domain Attention In Two Horizons for Time Series Forecasting
Time Series Forecasting plays a crucial role in various fields such as industrial equipment maintenance, meteorology, energy consumption, traffic flow and financial investment.
Robust Singing Voice Transcription Serves Synthesis
Note-level Automatic Singing Voice Transcription (AST) converts singing recordings into note sequences, facilitating the automatic annotation of singing datasets for Singing Voice Synthesis (SVS) applications.
Text-to-Song: Towards Controllable Music Generation Incorporating Vocals and Accompaniment
A song is a combination of singing voice and accompaniment.
Prompt-Singer: Controllable Singing-Voice-Synthesis with Natural Language Prompt
Recent singing-voice-synthesis (SVS) methods have achieved remarkable audio quality and naturalness, yet they lack the capability to control the style attributes of the synthesized singing explicitly.
Stochastic Data-Driven Predictive Control with Equivalence to Stochastic MPC
We propose a data-driven receding-horizon control method dealing with the chance-constrained output-tracking problem of unknown stochastic linear time-invariant (LTI) systems with partial state observation.
StyleSinger: Style Transfer for Out-of-Domain Singing Voice Synthesis
Moreover, existing SVS methods encounter a decline in the quality of synthesized singing voices in OOD scenarios, as they rest upon the assumption that the target vocal attributes are discernible during the training phase.
Speech-to-Speech Translation with Discrete-Unit-Based Style Transfer
The acoustic language model we introduce for style transfer leverages self-supervised in-context learning, acquiring style transfer ability without relying on any speaker-parallel data, thereby overcoming data scarcity.
When Do Discourse Markers Affect Computational Sentence Understanding?
The capabilities and use cases of automatic natural language processing (NLP) have grown significantly over the last few years.
DisCover: Disentangled Music Representation Learning for Cover Song Identification
We analyze the CSI task in a disentanglement view with the causal graph technique, and identify the intra-version and inter-version effects biasing the invariant learning.
Automated Action Model Acquisition from Narrative Texts
Action models, which take the form of precondition/effect axioms, facilitate causal and motivational connections between actions for AI agents.
AlignSTS: Speech-to-Singing Conversion via Cross-Modal Alignment
The speech-to-singing (STS) voice conversion task aims to generate singing samples corresponding to speech recordings while facing a major challenge: the alignment between the target (singing) pitch contour and the source (speech) content is difficult to learn in a text-free situation.
Zero-shot Medical Image Translation via Frequency-Guided Diffusion Models
However, for medical image translation, the existing diffusion models are deficient in accurately retaining structural information since the structure details of source domain images are lost during the forward diffusion process and cannot be fully recovered through learned reverse diffusion, while the integrity of anatomical structures is extremely important in medical images.
EDeR: A Dataset for Exploring Dependency Relations Between Events
We argue that an important type of relation not explored in NLP or IR research to date is that of an event being an argument - required or optional - of another event.
M4Singer: a Multi-Style, Multi-Singer and Musical Score Provided Mandarin Singing Corpus
The lack of publicly available high-quality and accurately labeled datasets has long been a major bottleneck for singing voice synthesis (SVS).
Data-Driven Model Predictive Control for Linear Time-Periodic Systems
Robustness of the algorithm to noisy data is illustrated via simulation of a regularized version of the algorithm applied to a stochastic multi-input multi-output LTP system.
Latent Space Arc Therapy Optimization
Volumetric modulated arc therapy planning is a challenging problem in high-dimensional, non-convex optimization.
The Geometry of Information Cocoon: Analyzing the Cultural Space with Word Embedding Models
In contrast, the people of higher social class have more capability to stride over the constraints of information cocoon.
Computers and Society
