Results 1 to 10 of about 650,365 (230)

Query-by-Example with Acoustic Word Embeddings Using wav2vec Pretraining [PDF]

open access: greenJisuanji kexue, 2022
Query-by-Example is a popular keyword detection method in the absence of speech resources.It can build a keyword query system with excellent performance when there are few labeled voice resources and a lack of pronunciation dictionaries.In recent years ...
LI Zhao-qi, LI Ta
doaj   +2 more sources

Query by Example: Semantic Traffic Scene Retrieval Using LLM-Based Scene Graph Representation [PDF]

open access: yesSensors
In autonomous driving, retrieving a specific traffic scene in huge datasets is a significant challenge. Traditional scene retrieval methods struggle to cope with the semantic complexity and heterogeneity of traffic scenes and are unable to meet the ...
Yafu Tian   +4 more
doaj   +2 more sources

ALBAYZIN Query-by-example Spoken Term Detection 2016 evaluation [PDF]

open access: goldEURASIP Journal on Audio, Speech, and Music Processing, 2018
Query-by-example Spoken Term Detection (QbE STD) aims to retrieve data from a speech repository given an acoustic (spoken) query containing the term of interest as the input.
Javier Tejedor   +9 more
doaj   +2 more sources

SPARQL Query Recommendations by Example [PDF]

open access: yes, 2016
In this demo paper, a SPARQL Query Recommendation Tool (called SQUIRE) based on query reformulation is presented. Based on three steps, Generalization, Specialization and Evaluation, SQUIRE implements the logic of reformulating a SPARQL query that is satisfiable w.r.t a source RDF dataset, into others that are satisfiable w.r.t a target RDF dataset. In
Allocca, Carlo   +3 more
openaire   +3 more sources

Query-by-Example Music Information Retrieval by Score-Informed Source Separation and Remixing Technologies

open access: greenEURASIP Journal on Advances in Signal Processing, 2010
We describe a novel query-by-example (QBE) approach in music information retrieval that allows a user to customize query examples by directly modifying the volume of different instrument parts.
Goto Masataka   +4 more
doaj   +3 more sources

From Query-By-Keyword to Query-By-Example [PDF]

open access: yesProceedings of the 2017 ACM on Conference on Information and Knowledge Management, 2017
One key challenge in talent search is to translate complex criteria of a hiring position into a search query, while it is relatively easy for a searcher to list examples of suitable candidates for a given position. To improve search efficiency, we propose the next generation of talent search at LinkedIn, also referred to as Search By Ideal Candidates ...
Viet Ha-Thuc   +5 more
openaire   +3 more sources

Synthesizing Trajectory Queries from Examples

open access: green, 2023
AbstractData scientists often need to write programs to process predictions of machine learning models, such as object detections and trajectories in video data. However, writing such queries can be challenging due to the fuzzy nature of real-world data; in particular, they often include real-valued parameters that must be tuned by hand.
Stephen Mell   +3 more
openalex   +3 more sources

Search on speech from spoken queries: the Multi-domain International ALBAYZIN 2018 Query-by-Example Spoken Term Detection Evaluation [PDF]

open access: goldEURASIP Journal on Audio, Speech, and Music Processing, 2019
The huge amount of information stored in audio and video repositories makes search on speech (SoS) a priority area nowadays. Within SoS, Query-by-Example Spoken Term Detection (QbE STD) aims to retrieve data from a speech repository given a spoken query.
Javier Tejedor   +6 more
doaj   +2 more sources

Bridging the Gap: Query by Semantic Example [PDF]

open access: yesIEEE Transactions on Multimedia, 2007
A combination of query-by-visual-example (QBVE) and semantic retrieval (SR), denoted as query-by-semantic-example (QBSE), is proposed. Images are labeled with respect to a vocabulary of visual concepts, as is usual in SR. Each image is then represented by a vector, referred to as a semantic multinomial, of posterior concept probabilities.
Nikhil Rasiwasia   +2 more
exaly   +3 more sources

Queries = examples + counterexamples

open access: hybridInformation Systems, 1996
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Levent V. Orman
openalex   +3 more sources

Home - About - Disclaimer - Privacy