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Aperta - TÜBİTAK Açık Arşivi
Other literature type . 2005
License: CC BY
https://doi.org/10.1007/115695...
Part of book or chapter of book . 2005 . Peer-reviewed
Data sources: Crossref
DBLP
Conference object . 2022
Data sources: DBLP
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A DCOM-Based Turkish Speech Recognition System: TREN – Turkish Recognition ENgine

Authors: Hasan Palaz; Alper Kanak; Yücel Bicil; Mehmet Ugur Dogan;

A DCOM-Based Turkish Speech Recognition System: TREN – Turkish Recognition ENgine

Abstract

Turkish Recognition ENgine (TREN) is a modular, Hidden Markov Model based (HMM-based), speaker independent and Distributed Component Object Model based (DCOM-based) speech recognition system. TREN contains specialized modules that allow a fully interoperable platform including a Turkish speech recognizer, a feature extractor, an end-point detector and a performance monitoring module. TREN deals with the interaction between two layers constituting the distributed architecture of TREN. The first layer is the central server, which applies some speech signal preprocessing and distributes the recognition calls to the appropriate remote servers according to their current CPU load of the recognition process. The second layer is composed of the remote servers performing the critical recognition task. In order to increase the recognition performance, a Turkish telephony speech database with a very large word corpus is collected and statistically the widest span of triphones representing Turkish is examined. TREN has been used to assist speech technologies which require a modular and multithreaded recognizer with dynamic load sharing facilities.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
Green