Pitch and formant estimation of bangla speech signal using autocorrelation, cepstrum and LPC algorithm

Aadit, Muhammad Navid Anjum; Kirtania, Sharadindu Gopal; Mahin, Mehnaz Tabassum

doi:10.1109/iccitechn.2016.7860226

Cited by 3 publications

(5 citation statements)

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“…Pitch has the highest amplitude compared to the other constituent frequencies while formant is a combination of several frequencies that contribute in shaping the color of a sound. The extraction process to obtain pitch and formant can refer to (Schnupp, 2014) (Aadit, et al, 2017) and (Wang, et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

“…Many researches in the field of acoustics use pitch and formant for various purposes, including for gender classification (Rahim & Malik, 2015), identification of conversation characteristics of a nation (Aadit, et al, 2017) (Suyudi & Saptono, 2017), up to one's emotional predictions (Mohanta & Mittal, 2016). For the health sector, sound analysis is mostly used to predict the lung disorders such as respiratory syndrome (Gutierrez, et al, 2010), asthma (Batra, et al, 2015), and pneumonia (Maulidin, 2018).…”

Section: Introductionmentioning

confidence: 99%

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The Effect of Sore Throat on Changes of Vowel Sounds

Setiawan

Sutono

2021

ELKOMIKA

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

The Effect of Sore Throat on Changes of Vowel Sounds

Setiawan

Sutono

2021

ELKOMIKA

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“…The most commonly used classical methods in speech processing and recognition system are Dynamic Time Warping (DTW) [2], Hidden Markov Model (HMM) [3], Linear Predictive Coding (LPC) [4], Gaussian Mixture Model (GMM) [2], Template Matching [2], Autocorrelation [5], Cepstrum [5], Speech Application Program Interface (SAPI) [6], Factorial Hidden Markov Model [7], Minimum Classification Error [8], Knowledge Based Approaches [9], Template Based Approaches [9], and Perceptual Linear Prediction [10].…”

Section: B Classical Methodsmentioning

confidence: 99%

“…Aadit et al [5] proposed a technique for finding the Bangla alphabet's oral characteristics in terms of pitch and formant. The authors downsampled the speech signal and read small segments of 40 milliseconds in MATLAB.…”

Section: ) Classical Approachesmentioning

confidence: 99%

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Bangla Natural Language Processing: A Comprehensive Analysis of Classical, Machine Learning, and Deep Learning-Based Methods

et al. 2022

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The Bangla language is the seventh most spoken language, with 265 million native and non-native speakers worldwide. However, English is the predominant language for online resources and technical knowledge, journals, and documentation. Consequently, many Bangla-speaking people, who have limited command of English, face hurdles to utilize English resources. To bridge the gap between limited support and increasing demand, researchers conducted many experiments and developed valuable tools and techniques to create and process Bangla language materials. Many efforts are also ongoing to make it easy to use the Bangla language in the online and technical domains. There are some review papers to understand the past, previous, and future Bangla Natural Language Processing (BNLP) trends. The studies are mainly concentrated on the specific domains of BNLP, such as sentiment analysis, speech recognition, optical character recognition, and text summarization. There is an apparent scarcity of resources that contain a comprehensive review of the recent BNLP tools and methods. Therefore, in this paper, we present a thorough analysis of 75 BNLP research papers and categorize them into 11 categories,

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Bangla Natural Language Processing: A Comprehensive Analysis of Classical, Machine Learning, and Deep Learning Based Methods

Sen,

Fuad,

Islam

et al. 2021

Preprint

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The Bangla language is the seventh most spoken language, with 265 million native and non-native speakers worldwide. However, English is the predominant language for online resources and technical knowledge, journals, and documentation. Consequently, many Bangla-speaking people, who have limited command of English, face hurdles to utilize English resources. To bridge the gap between limited support and increasing demand, researchers conducted many experiments and developed valuable tools and techniques to create and process Bangla language materials. Many efforts are also ongoing to make it easy to use the Bangla language in the online and technical domains. There are some review papers to understand the past, previous, and future Bangla Natural Language Processing (BNLP) trends. The studies are mainly concentrated on the specific domains of BNLP, such as sentiment analysis, speech recognition, optical character recognition, and text summarization. There is an apparent scarcity of resources that contain a comprehensive study of the recent BNLP tools and methods. Therefore, in this paper, we present a thorough review of 71 BNLP research papers and categorize them into 11 categories,

show abstract

Pitch and formant estimation of bangla speech signal using autocorrelation, cepstrum and LPC algorithm

Cited by 3 publications

References 22 publications

The Effect of Sore Throat on Changes of Vowel Sounds

The Effect of Sore Throat on Changes of Vowel Sounds

Bangla Natural Language Processing: A Comprehensive Analysis of Classical, Machine Learning, and Deep Learning-Based Methods

Bangla Natural Language Processing: A Comprehensive Analysis of Classical, Machine Learning, and Deep Learning Based Methods

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