Total matches
24
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Search the curated corpus with lexical retrieval first.
Title + abstract lexical searchDeterministic ordering
Search v1 is intentionally narrow: lexical retrieval over titles and abstracts, plus practical filters for narrowing the current corpus. Semantic assist can come later, but it is not part of Search v1's scope.
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16-24
Core papers shown
4
Rows with topics
4
Search v1 scope: dedicated lexical search, practical filters, and clean handoff into dossier and ranking views. When ranking family filtering is active, the API resolves and returns one explicit run context.
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What Search v1 supports
- Lexical retrieval over
title + abstract. - Filters for year, scope, venue/source, topic label, and ranking family filter.
- Stable ordering: lexical rank, then year, citations, and work id.
- Run metadata appears only when the search depended on ranking state.
Topic labels are imported metadata and can be noisy; use them as coarse navigation hints, not authoritative classifications.
Workflow map
How search moves through Research Radar
01
Find the right candidate set
Start with lexical retrieval and narrow with year, venue, topic, and scope filters until the candidate set is focused enough to inspect.
02
Inspect the dossier
Open the paper dossier to review abstract, metadata, ranking presence, and adjacent papers without losing the corpus framing.
03
Move into signals
Use Recommended and Evaluation to understand why a result matters now and how it sits inside the exact resolved ranking run when family filtering is active.
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: abstract
This paper summarizes the music demixing (MDX) track of the Sound Demixing Challenge (SDX'23). We provide a summary of the challenge setup and introduce the task of robust music source separation (MSS), i.e., training MSS models in the pre...
- introduce the task of robust music [[source]] [[separation]] (MSS), i.e., training MSS models in the presence
Music and Audio ProcessingSpeech and Audio ProcessingMusic Technology and Sound Studies - includedmatched: abstract
Score-based diffusion models have demonstrated promise to separate individual sources from music mixture signals in a generative fashion, paving the way for a new class of solutions for this challenging task. However, existing works rely o...
- diffusion models have demonstrated promise to [[separate]] individual [[sources]] from music mixture signals in a generative...modeling to perform weakly-supervised singing voice [[separation]] for Carnatic Music, a music repertoire for which
- includedmatched: abstract
In music, feature separation is the process of separating distinguishable auditory characteristics, such as pitch, timbre, rhythm, and harmonic content, from a complicated, mixed signal. Virtual reality (VR), gaming, music transcription, k...
- [[separation]] of audio components is very difficult. In this research, extracting features from mixed audio [[sources]]...dataset was highly effective for feature [[separation]]
- corematched: abstract
Recent spatial audio techniques involve separating multichannel signals into direct and background parts. However, determining parameters for localizing short sound sources in background sounds remains challenging due to the limited knowle...
- [[separating]] multichannel signals into direct and background parts. However, determining parameters for localizing short sound [[sources]]
Image and Signal Denoising MethodsStructural Health Monitoring Techniques - corematched: abstract
This paper proposes and evaluates a perceptual model for the measurement of "punch" in musical signals based on a novel algorithm. Punch is an attribute that is often used to characterize music or sound sources that convey a sense of dynam...
- often used to characterize music or sound [[sources]] that convey a sense of dynamic power...methodology is explored that combines signal [[separation]], onset detection, and low level feature measurement to produce
Structural Health Monitoring TechniquesVehicle Noise and Vibration ControlSpeech and Audio Processing - includedmatched: abstract
Identifying noise sources in exceedance-triggered audio is essential for targeted source tracing and sustainable urban social noise governance. While accurate models require massive labeled data, the acoustic complexity, high redundancy, a...
- exceedance-triggered audio is essential for targeted [[source]] tracing and sustainable urban social noise governance. While...treating uncertainty, class balance, and diversity as [[separate]] query criteria, it encodes uncertainty and dynamic class
- corematched: abstract
Existing multi-timbre transcription models struggle with generalization beyond pre-trained instruments, rigid source-count constraints, and high computational demands that hinder deployment on low-resource devices. We address these limitat...
- with generalization beyond pre-trained instruments, rigid [[source]]-count constraints, and high computational demands that hinder...note level, enabling joint transcription and dynamic [[separation]] of arbitrary instruments given a specified number
Music and Audio ProcessingMusic Technology and Sound StudiesImage Processing and 3D Reconstruction - includedmatched: abstract
Introduction Stochastic waveforms are intrinsic to many physical and telecommunication processes, yet reproducible interfaces for converting them into compact stochastic representations suitable for bitstream-domain processing remain limit...
- using a NOT-NOT identity protocol that [[separates]] finite-K representational loss from finite-N stochastic...between truncation-limited and encoding-limited error [[sources]]. Discussion Harmonic parameter factorization offers an interpretable bridge
- includedmatched: abstract
With the increasing demand for intelligent fault monitoring, acoustic-based diagnosis has emerged as a promising solution for industrial applications such as pipeline leakage and electrical equipment fault detection. However, complex worki...
- aligns amplitude and phase features across multiple [[source]] domains and performs label-consistent sample augmentation...improving intra-class compactness and inter-class [[separability]]. We evaluate the proposed method on two publicly
Showing 16-24 of 24