Classification of Transmission Channels by Speech Signal Processing

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F13%3APU106086" target="_blank" >RIV/00216305:26220/13:PU106086 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Classification of Transmission Channels by Speech Signal Processing

Popis výsledku v původním jazyce

The paper deals with the classification of five different transmission channels by applying speech signal processing techniques. The channels considered are: GSM, two PSTN channels and two VoIP channels. For training and testing purpose, a speech database called SPLAB TranCh was constructed. The speech signals of this corpus originally come from well-known TIMIT database, where each utterance passed through each mentioned transmission channel. The main objective of this work is to find optimal featuresand classification technique that yield best classification accuracy. Several types of features, including MFCC, LPCC and spectral characteristics were put under examination. The best features were identified by using the mRMR algorithm. Various classifiers were tested as well. The results suggested that the classification of transmission channels can be performed with high accuracy (around 92%).

Název v anglickém jazyce

Classification of Transmission Channels by Speech Signal Processing

Popis výsledku anglicky

The paper deals with the classification of five different transmission channels by applying speech signal processing techniques. The channels considered are: GSM, two PSTN channels and two VoIP channels. For training and testing purpose, a speech database called SPLAB TranCh was constructed. The speech signals of this corpus originally come from well-known TIMIT database, where each utterance passed through each mentioned transmission channel. The main objective of this work is to find optimal featuresand classification technique that yield best classification accuracy. Several types of features, including MFCC, LPCC and spectral characteristics were put under examination. The best features were identified by using the mRMR algorithm. Various classifiers were tested as well. The results suggested that the classification of transmission channels can be performed with high accuracy (around 92%).

Druh

D - Stať ve sborníku

CEP obor

JA - Elektronika a optoelektronika, elektrotechnika

OECD FORD obor

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Projekt

<a href="/cs/project/ED2.1.00%2F03.0072" target="_blank" >ED2.1.00/03.0072: Centrum senzorických, informačních a komunikačních systémů (SIX)</a><br>

Návaznosti

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

Rok uplatnění

2013

Kód důvěrnosti údajů

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

Název statě ve sborníku

36th International Conference on Telecommunications and Signal processing

ISBN

978-1-4799-0402-0

ISSN

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e-ISSN

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Počet stran výsledku

4

Strana od-do

100-103

Název nakladatele

Neuveden

Místo vydání

Neuveden

Místo konání akce

Rome

Datum konání akce

2. 7. 2013

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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