Local compressed convex spectral embedding for bird species identification Article Swipe
Anshul Thakur
,
Vinayak Abrol
,
Pulkit Sharma
,
P.K. Rajan
·
YOU?
·
· 2018
· Open Access
·
· DOI: https://doi.org/10.1121/1.5042241
YOU?
·
· 2018
· Open Access
·
· DOI: https://doi.org/10.1121/1.5042241
This paper proposes a multi-layer alternating sparse−dense framework for bird species identification. The framework takes audio recordings of bird vocalizations and produces compressed convex spectral embeddings (CCSE). Temporal and frequency modulations in bird vocalizations are ensnared by concatenating frames of the spectrogram, resulting in a high dimensional and highly sparse super-frame-based representation. Random projections are then used to compress these super-frames. Class-specific archetypal analysis is employed on the compressed super-frames for acoustic modeling, obtaining the convex-sparse CCSE representation. This representation efficiently captures species-specific discriminative information. However, many bird species exhibit high intra-species variations in their vocalizations, making it hard to appropriately model the whole repertoire of vocalizations using only one dictionary of archetypes. To overcome this, each class is clustered using Gaussian mixture models (GMM), and for each cluster, one dictionary of archetypes is learned. To calculate CCSE for any compressed super-frame, one dictionary from each class is chosen using the responsibilities of individual GMM components. The CCSE obtained using this GMM-archetypal analysis framework is referred to as local CCSE. Experimental results corroborate that local CCSE either outperforms or exhibits comparable performances to existing methods including support vector machine powered by dynamic kernels and deep neural networks.
Related Topics
Concepts
Computer science
Pattern recognition (psychology)
Mixture model
Sparse approximation
Artificial intelligence
Discriminative model
Embedding
Representation (politics)
Frame (networking)
Compressed sensing
Gaussian
Identification (biology)
Class (philosophy)
Politics
Political science
Biology
Quantum mechanics
Physics
Telecommunications
Law
Botany
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1121/1.5042241
- https://asa.scitation.org/doi/pdf/10.1121/1.5042241
- OA Status
- bronze
- Cited By
- 10
- References
- 26
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2810464261
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W2810464261Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1121/1.5042241Digital Object Identifier
- Title
-
Local compressed convex spectral embedding for bird species identificationWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2018Year of publication
- Publication date
-
2018-06-01Full publication date if available
- Authors
-
Anshul Thakur, Vinayak Abrol, Pulkit Sharma, P.K. RajanList of authors in order
- Landing page
-
https://doi.org/10.1121/1.5042241Publisher landing page
- PDF URL
-
https://asa.scitation.org/doi/pdf/10.1121/1.5042241Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
bronzeOpen access status per OpenAlex
- OA URL
-
https://asa.scitation.org/doi/pdf/10.1121/1.5042241Direct OA link when available
- Concepts
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Computer science, Pattern recognition (psychology), Mixture model, Sparse approximation, Artificial intelligence, Discriminative model, Embedding, Representation (politics), Frame (networking), Compressed sensing, Gaussian, Identification (biology), Class (philosophy), Politics, Political science, Biology, Quantum mechanics, Physics, Telecommunications, Law, BotanyTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
10Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 1, 2024: 1, 2023: 3, 2022: 1, 2021: 2Per-year citation counts (last 5 years)
- References (count)
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26Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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