Feature Extraction Methods Based on Linear Predictive Coding and Wavelet Packet Decomposition for Recognizing Spoken Words in Malayalam

Sunny, Sonia; Peter, S. David; Jacob, K. Poulose

doi:10.1109/icacc.2012.7

Cited by 5 publications

(3 citation statements)

References 12 publications

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“…Various methods are used for feature extraction [33]. Most commonly used methods are Linear Predictive Coding (LPC) [34], Mel Frequency Cepstral Coefficient (MFCC) analysis, Wavelet Packet Decomposition (WPD) [34] and Perceptual Linear Prediction (PLP) [35]. MFCC method for feature extraction mimics the human auditory system and gives better performance rate.…”

Section: Speech To Text Conversionmentioning

confidence: 99%

Call Transcription and Text Classification - A Review

Arivazhagan¹,

Anaswara²,

Eliza³

et al. 2018

IJCA

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A common method of data exchange is speech. Keeping track of every word exchanged through verbal means is difficult. Mostly, verbal communication is carried out through voice calls. For keeping tab of information exchanged, calls can be converted to text. These text files can be classified according to the content of the document. Also, unwanted call recordings have to be eliminated. This research contains the various methods required to implement call transcription and text classification. More than 50 papers were reviewed regarding the sections, call recording, transcription and ordering of text documents.

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Section: Speech To Text Conversionmentioning

confidence: 99%

Call Transcription and Text Classification - A Review

Arivazhagan¹,

Anaswara²,

Eliza³

et al. 2018

IJCA

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“…Son numerosos los métodos de estimación de características aplicados al procesamiento de voz como el análisis cepstral [10], [11], el Linear Predictive Coding (LPC, por sus siglas en inglés) [12], [13], el MFCC [14], además de aproximaciones clásicas basadas en el análisis temporal de las señales y las representaciones en frecuencia de las mismas.…”

Section: Metodología Para La Extracción De Los Mfccunclassified

Reconocimiento de patrones de habla usando MFCC y RNA

Ramos¹,

Rojas²,

Gongora³

2016

Vis. Electron.

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En este trabajo se presentan los resultados del diseño y desarrollo de un algoritmo basado en inteligencia artificial para el reconocimiento de patrones de vocablos del idioma español, utilizando Coeﬁcientes Cepstrales en las Frecuencias de Mel o (MFCC), para representar el habla a través de la percepción auditiva del ser humano. La utilización de MFCC permitió caracterizar las señales de voz teniendo en cuenta el posible ruido presente en el ambiente de grabación, lo cual ayudo a la obtención de patrones comunes entre estas señales cuando presentan alteraciones. Como resultado se obtuvo un reconocimiento superior al 95% de las tres vocales escogidas, en este caso la /a/,/e/,/o/, entre un grupo de 22 muestras por vocal para el entrenamiento y 11 muestras para la validación. Las muestras fueron obtenidas de 11 personas, todas del género masculino.

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“…According to the literature [5], there follows the basic criterion. The mean vectors of two categories i…”

Section: Find the Optimal Wavelet Packet Basismentioning

confidence: 99%

Research and Implementation of a License Plate Recognition Algorithm Based on Hierarchical Classification

Gao¹,

Sun²,

Liu³

et al. 2014

JCC

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This paper proposed an improved method for license plate recognition based on hierarchical classification. First, the method of feature extraction and dimension reduction is presented by finding the optimal wavelet packet basis in the process of wavelet packet decomposition and K-L transform. Then the recognition algorithm is introduced based on feature extraction and hierarchical classification. Finally, the principles and procedures of using support vector machines, Harris corner detection algorithm and digital character classification are explained in detail. Simulation results indicate that the presented recognition algorithm performs well with higher speed and efficiency in recognition.

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Feature Extraction Methods Based on Linear Predictive Coding and Wavelet Packet Decomposition for Recognizing Spoken Words in Malayalam

Cited by 5 publications

References 12 publications

Call Transcription and Text Classification - A Review

Call Transcription and Text Classification - A Review

Reconocimiento de patrones de habla usando MFCC y RNA

Research and Implementation of a License Plate Recognition Algorithm Based on Hierarchical Classification

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