Open AccessJournal Article
Multi Lingual Speaker Identification on Foreign Languages using Artificial Neural Network
TL;DR: Application of developed system is mainly used in speaker authentication in telephony security oriented applications where the normal conversations are of short durations and the tendency of the spokesperson is to switch language from one to another.
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Abstract: on the Back Propagation Algorithm, this paper portrait a method for speaker identification in multiple foreign languages. In order to identify speaker, the complete process goes through recording of the speech utterances of different speakers in multiple foreign languages, features extraction, data clustering and system training. In order to realize the purpose, a database has been prepared which contains one sentence in 8 different international languages i.e. Catalan, French, Finnish, Italian, Portuguese, Indonesian, Hindi, English spoken by 19 distinct speakers, both male and female, in each language. With total size of 760 speech utterances, the average performance of the system is 95.657%. Application of developed system is mainly used in speaker authentication in telephony security oriented applications where the normal conversations are of short durations and the tendency of the spokesperson is to switch language from one to another
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Citations
Multilingual Person Identification
TL;DR: This paper explores the idea to identify multi-lingual person by basic features by considering two languages Hindi and Marathi including male and female and base the approach on multilingual person identification using basic features.
5
Algorithms and architectures of speech recognition systems
Nurbapa Mekebayev,Orken Mamyrbayev,Mussa Turdalyuly,D Oralbekova,M Tasbolatov +4 more
- 20 Feb 2021
TL;DR: This article presents an algorithm of extracting MFCC for speech recognition that reduces the processing power by 53% compared to the conventional algorithm.
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Review of neural networks for speech recognition
TL;DR: Further work is necessary for large-vocabulary continuous-speech problems, to develop training algorithms that progressively build internal word models, and to develop compact VLSI neural net hardware.
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Speech Recognition by Machine, A Review
M. A. Anusuya,S. K. Katti +1 more
TL;DR: The objective of this review paper is to summarize and compare some of the well known methods used in various stages of speech recognition system and identify research topic and applications which are at the forefront of this exciting and challenging field.
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Revisiting Recurrent Neural Networks for robust ASR
Oriol Vinyals,Suman V. Ravuri,Daniel Povey +2 more
- 25 Mar 2012
TL;DR: The Recurrent Neural Network is revisited, which explicitly models the Markovian dynamics of a set of observations through a non-linear function with a much larger hidden state space than traditional sequence models such as an HMM.
Neural networks used for speech recognition
TL;DR: This investigation on the speech recognition classification performance is performed using two standard neural networks structures as the classifier using Feed-forward Neural Network with back propagation algorithm and a Radial Basis Functions Neural Networks.