Malay syllable recognition based on multilayer perceptron and dynamic time warping

Ting, Hua Nong; Jasmy, Y.; Hussain, Samreen; Cheah, Eugene

doi:10.1109/isspa.2001.950257

Cited by 5 publications

(4 citation statements)

References 2 publications

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“…where σ(n) is defined by equation (12). Thus, as time n (i.e., the number of iteration) increases, the width σ(n) decreases at an exponential rate, and the topological neighbourhood shrinks in corresponding manner.…”

Section: Cooperative Processmentioning

confidence: 99%

“…The use of multi-layer perceptron as speech recognizer has been encouraged by many workers [1, 9,11,12] during the last few decades. The most obvious way to use multi-layer perceptron for speech recognition is to present all acoustic vectors of a speech unit (phoneme or word) at once at the input and detect the most probable speech unit at the output by determining the output neuron with highest activation.…”

Section: Introductionmentioning

confidence: 99%

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Search Key Identification in a Spoken Query using Isolated Keyword Recognition

Bhattacharjee¹

2010

IJCA

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This article presents a novel technique for the recognition of isolated keywords from spoken search queries. Recognition of the isolated keywords from spoken search queries may be considered as the first step towards the development of a speech-operated keyword-based searching technique. A database of 300 spoken search queries from Assamese language, a major Indian language mostly spoken by the people of north east India, has been created. The system developed during the study has been tested and evaluated with the above mentioned database. In the present study, Mel Frequency Cepstral Coefficient (MFCC) has been used as the feature vector and Multilayer Perceptron (MLP) to identify the phoneme boundaries as well as for recognition of the phonemes. Viterbi search technique has been used to identify the keywords from the sequence of phonemes generated by the phoneme recognizer. A recognition accuracy of 74.67% has been achieved in the present study.

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Section: Cooperative Processmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Search Key Identification in a Spoken Query using Isolated Keyword Recognition

Bhattacharjee¹

2010

IJCA

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“…The words in the Malay language can broken down into smaller linguistic units or syllable structures such as CV, VC, CVC, CCVC, CVCC, CCCV and CCCVC [12] where C and V represent consonant and vowel respectively.…”

Section: Speech Lexiconmentioning

confidence: 99%

“…Numerous research and development has been done in recent years in speech recognition in various languages. However, Malay speech recognition is still in its infancy and at the start of this research, the few published research papers in this field [9,10,11,12] had employed variations of the neural network approach.…”

Section: Introductionmentioning

confidence: 99%

Isolated malay speech recognition using Hidden Markov Models

Rosdi

Ainon

2008

2008 International Conference on Computer and Communication Engineering

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The study aims to develop an automated isolated word speech recognition for Malay language that relies heavily on the well known and widely used statistical method in characterizing the speech pattern, the Hidden Markov Model (HMM). This paper discusses the development and implementation of an isolated Malay word speech recognition system using HMM as the acoustic model. This research focuses on isolated 5 phonemes word structure such as empat (four), lapan (eight), rekod (record), tidak (no), tujuh (seven) and tutup (close). The proposed system is relatively successful where it can identify spoken word at 88% recognition rate which is an acceptable rate of accuracy for speech recognition.

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Alveolar Consonant Recognition of Malay Children Using Neural Networks

Ting

Lee

2009

IFMBE Proceedings

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Malay syllable recognition based on multilayer perceptron and dynamic time warping

Cited by 5 publications

References 2 publications

Search Key Identification in a Spoken Query using Isolated Keyword Recognition

Search Key Identification in a Spoken Query using Isolated Keyword Recognition

Isolated malay speech recognition using Hidden Markov Models

Alveolar Consonant Recognition of Malay Children Using Neural Networks

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