Convolutional Neural Networks and X-Vector Embedding for DCASE2018 Acoustic Scene Classification Challenge

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F18%3APU130803" target="_blank" >RIV/00216305:26230/18:PU130803 - isvavai.cz</a>

Result on the web

<a href="http://dcase.community/documents/workshop2018/proceedings/DCASE2018Workshop_Zeinali_149.pdf" target="_blank" >http://dcase.community/documents/workshop2018/proceedings/DCASE2018Workshop_Zeinali_149.pdf</a>

DOI - Digital Object Identifier

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Result language

angličtina

Original language name

Convolutional Neural Networks and X-Vector Embedding for DCASE2018 Acoustic Scene Classification Challenge

Original language description

In this paper, the Brno University of Technology (BUT) team submissions for Task 1 (Acoustic Scene Classification, ASC) of the DCASE-2018 challenge are described. Also, the analysis of different methods on the leaderboard set is provided. The proposed approach is a fusion of two different Convolutional Neural Network (CNN) topologies. The first one is the common two-dimensional CNNs which is mainly used in image classification. The second one is a one-dimensional CNN for extracting fixed-length audio segment embeddings, so called x-vectors, which has also been used in speech processing, especially for speaker recognition. In addition to the different topologies, two types of features were tested: log mel-spectrogram and CQT features. Finally, the outputs of different systems are fused using a simple output averaging in the best performing system. Our submissions ranked third among 24 teams in the ASC sub-task A (task1a).

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

Result was created during the realization of more than one project. More information in the Projects tab.

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2018

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

Proceedings of DCASE 2018 Workshop

ISBN

978-952-15-4262-6

ISSN

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e-ISSN

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Number of pages

5

Pages from-to

1-5

Publisher name

Tampere University of Technology

Place of publication

Surrey

Event location

Surrey

Event date

Nov 19, 2018

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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