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Lexical results
Results for “source separation”
Order: lexical_rank desc, year desc, citation_count desc, work_id ascTotal matches: 24
Resolved filters: scope all_included
- corematched: title, abstract
Music remixing is difficult when the original multitrack recording is not available. One solution is to estimate the elements of a mixture using source separation. However, existing techniques suffer from imperfect separation and perceptib...
- [[Source]] [[Separation]] for RemixingMusic
- estimate the elements of a mixture using [[source]] [[separation]]. However, existing techniques suffer from imperfect [[separation]]...perceptible artifacts on single [[separated]] [[sources]]. To investigate their influence on a remix, five state
Speech and Audio ProcessingMusic and Audio ProcessingBlind Source Separation Techniques Chinese instrument music source separation with frequency-attentive multi-band neural networks
lex 0.713includedmatched: title, abstractRecent progress in music source separation has been accelerated by deep learning techniques, yet most studies have focused on Western instruments and vocals, with limited attention to traditional Chinese instruments. These instruments poss...
- [[source]] [[separation]] with
- Recent progress in music [[source]] [[separation]] has been accelerated by deep learning techniques, yet most studies...multi-head attention mechanisms to enhance music [[source]] [[separation]] performance. Extensive experiments with 13 band-division
- includedmatched: title, abstract
Music source separation (MSS) is a task of extracting one or more constituent components, or composites thereof, from a musical audio mixture. Historically, music source separation has been dominated by a stem-based paradigm, leading to mo...
- [[Separate]] this, and all of these Things Around It: Music [[Source]]
- Music [[source]] [[separation]] (MSS) is a task of extracting one or more constituent components, or composites...from a musical audio mixture. Historically, music [[source]] [[separation]] has been dominated by a stem-based
- corematched: title, abstract
Recent advances in automatic music transcription have facilitated the creation of large databases of symbolic transcriptions of improvised music forms including jazz, where traditional notated scores are not normally available. In conjunct...
- Audio [[Source]] [[Separation]]
- normally available. In conjunction with music [[source]] [[separation]] models that enable audio to be "demixed" into...scraping user-based listening and discographic data; [[source]] [[separation]] models were applied to isolate audio
Music and Audio ProcessingMusic Technology and Sound StudiesSpeech and Audio Processing - includedmatched: title, abstract
Music source separation, as a fundamental task in intelligent audio processing, plays a critical role in enhancing the performance of music generation, editing, and understanding systems. However, existing separation models often suffer fr...
- [[source]] [[separation]] method
- Music [[source]] [[separation]], as a fundamental task in intelligent audio processing, plays a critical role...introduces a new architectural paradigm for music [[source]] [[separation]] that balances accuracy and efficiency. The implementation
- corematched: title, abstract
Dialogue Enhancement (DE) is one of the most promising applications of user interactivity enabled by object-based audio broadcasting. DE allows personalization of the relative level of dialogue for intelligibility or aesthetic reasons. Thi...
- [[Source]] [[Separation]] for Enabling
- MPEG-H, with a special focus on [[source]] [[separation]] methods enabling DE also for legacy content...investigates the subjective quality penalty from using [[source]] [[separation]] for obtaining the objects. The results show
Speech and Audio ProcessingAdvanced Data Compression TechniquesAdvanced Adaptive Filtering Techniques - includedmatched: title, abstract
Music source separation (MSS) focuses on decomposing a mixed audio signal into individual instrumental components and is increasingly relevant for music production, restoration, remixing, education, and music information retrieval. Deep le...
- [[Source]] [[Separation]] Performance
- Music [[source]] [[separation]] (MSS) focuses on decomposing a mixed audio signal into individual instrumental components...work presents an optimized multi-[[source]] U-Net model for [[separating]] selected musical instruments from stereo
- includedmatched: title, abstract
In recent years, significant advances have been made in music source separation, with model architectures such as dual-path modeling, band-split modules, or transformer layers achieving comparably good results. However, these models often...
- Music [[Source]] [[Separation]]
- significant advances have been made in music [[source]] [[separation]], with model architectures such as dual-path
- corematched: title, abstract
Cockpit voice recorders (CVRs) are one of the two mandatory flight recording devices embarked in commercial aircraft. Its analysis is crucial to understand the context of an air incident or accident. However, in such scenarios, when the au...
- [[Source]] [[Separation]] Enhances
- cocktail party problem" that blind [[source]] [[separation]] (BSS) aims to tackle, modeling CVR mixtures-that...While not trivial-even in a two-[[source]] scenario-BSS methods can be applied to real
Speech and Audio ProcessingBlind Source Separation TechniquesVehicle Noise and Vibration Control - includedmatched: abstract
We propose DeepASA, a multi-purpose model for auditory scene analysis that performs multi-input multi-output (MIMO) source separation, dereverberation, sound event detection (SED), audio classification, and direction-of-arrival estimation...
- that performs multi-input multi-output (MIMO) [[source]] [[separation]], dereverberation, sound event detection (SED), audio classification...evaluated tasks, demonstrating its effectiveness in both [[source]] [[separation]] and auditory parameter estimation under diverse spatial
- includedmatched: abstract
This paper presents the Deep learning-based Perceptual Audio Quality metric (DeePAQ) for evaluating general audio quality. Our approach leverages metric learning together with the music foundation model MERT, guided by surrogate labels, to...
- across listening tests spanning audio coding and [[source]] [[separation]]. Results show that our method surpasses existing...generalizes well to unseen distortions such as [[source]] [[separation]], highlighting its robustness and versatility
- corematched: abstract
The piano concerto is a genre of central importance in Western classical music, often consisting of a virtuoso solo part for piano and an orchestral accompaniment. In this article, we introduce the Piano Concerto Dataset (PCD), which compr...
- which comprises a collection of excerpts with [[separate]] piano and orchestral tracks from piano concertos ranging...Music Information Retrieval (MIR) tasks, including music [[source]] [[separation]], automatic accompaniment, music synchronization, editing, and upmixing
Music and Audio ProcessingSpeech and Audio ProcessingMusic Technology and Sound Studies - includedmatched: abstract
Abstract: Foliage-penetration (FOPEN) radar systems operating in VHF/UHF bands enable detection of man-made targets concealed beneath dense vegetation, yet their performance is significantly constrained by strong, non-Gaussian, and tempora...
- cancellation, entropy-weighted coherent integration, and blind-[[source]] [[separation]] methods provide only partial suppression under wind...doi.org/10.5281/zenodo.17876452 Paper Download Link ([[Source]]) https://www.researchpublish.com/papers/a-review-on-image-processing-techniques-on-fopen-radar-clutter-cancellation
- includedmatched: abstract
Short video platforms like YouTube Shorts and TikTok face significant copyright compliance challenges, as infringers frequently embed arbitrary background music (BGM) to obscure original soundtracks (OST) and evade content originality dete...
- propose a novel pipeline that integrates Music [[Source]] [[Separation]] (MSS) and cross-modal video-music retrieval
Percussion and Instrumentation in Music Emotion Recognition: A Feature Engineering Approach
lex 0.286includedmatched: abstractWe propose a new set of features for audio-based Music Emotion Recognition (MER) that are related to percussion and individual instrument information. One limitation of current feature engineering approaches in MER is that they primarily f...
- approach leverages the Demucs framework for music [[source]] [[separation]] (which enables drum channel [[separation]]
Showing 1-15 of 24