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Comparison of different implementations of MFCC

Fang Zheng, Guoliang Zhang, Zhanjiang Song
2001 Journal of Computer Science and Technology  
In this paper, several comparison experiments are done to find a best implementation.  ...  The performance of the Mel-Frequency Cepstrum Coefficients (MFCC) may be affected by (1) the number of filters, (2) the shape of filters, (3) the way that filters are spaced, and (4) the way that the power  ...  COMPARISONS OF MFCC IMPLEMENTATION According to the MFCC calculation, the performance of MFCC may be affected by: (1) the number of the filters, (2) the shape of the filters, (3) the way that the filters  ... 
doi:10.1007/bf02943243 fatcat:unmpxm5tmrhohmhazszzp5wse4

Analysis of Various Features using Different Temporal Derivatives from Speech Signals

Muskan Muskan, Naveen Aggarwal
2015 International Journal of Computer Applications  
Comparison of range and accuracy for acceptable results has been determined using HMM.  ...  Research in speech recognition for different languages is at peak. Less amount of work has been done for Indian languages particularly for Punjabi language.  ...  Various feature extraction techniques being implemented were FBANK, LPC, MFCC and LPCEPSTRA.In 2005, Aik Ming Toh et al. [27] implemented speech recognition techniques MFCC and FBANK for different types  ... 
doi:10.5120/20762-3191 fatcat:kqaarefom5eszpdpmd4xakheme

A Survey on Isolated Word and Digit Recognition using Different Techniques

Pooja Prajapati, Miral Patel
2017 International Journal of Computer Applications  
Various techniques are used for isolated speech recognition like MFCC, HMM, LPC. But among all of them many researchers found that MFCC is widely used & give a more accurate result.  ...  Likewise, discussing different approaches, methods & comparative analysis about recent research work done in isolated digit & word recognition in various languages.  ...  to English digits from 0 to 9 which is spoken by 28 speakers that is implemented using different type of feature extraction techniques like MFCC,LPC,ZCR & STE.  ... 
doi:10.5120/ijca2017913130 fatcat:6uxrjp6ruzhchht5bxrv3f43xe

A Survey Report on Speech Recognition System

Moirangthem TikenSingh, Abdur Razzaq Fayjie, Biswajeet Kachari
2015 International Journal of Computer Applications  
This paper present a report on a Automatic Speech Recognition System (ASR) for different language under different accent.  ...  And Moreover ASR implemented by using Hidden Markov Tool kit(HTK) are more efficient then the other systems implemented by using other tools  ...  due to the different speaking styles of human beings (i.e. the accents).  ... 
doi:10.5120/21581-4672 fatcat:s6iw55rtkvb67js6t5mk7fk3pa


P Mahalakshmi
2016 Asian Journal of Pharmaceutical and Clinical Research  
features.Results: The review results show that research in MFCC has been dominant in signal processing in comparison to VAD and other existing techniques.Conclusion: A comparison of different speaker  ...  ABSTRACTObjective: The objective of this review article is to give a complete review of various techniques that are used for speech recognition purposes overtwo decades.Methods: VAD-Voice Activity Detection  ...  Usage of different are used in different MFCC implementations.  ... 
doi:10.22159/ajpcr.2016.v9s3.14352 fatcat:hzuobzxrxfdh7koblyegnwkeiy

Mel Frequency Cepstral Coefficients: An Evaluation Of Robustness Of Mp3 Encoded Music

Sigurdur Sigurdsson, Kaare Brandt Petersen, Tue Lehn-Schiøler
2006 Zenodo  
MFCC Implementations The implementation comparison used only WAV files for evaluation. MFCCs were computed for each song for all 4 implementations.  ...  Note that the images are different in size, due to different number of MFCCs for each implementation. Figure 3 . 3 Figure 3.  ... 
doi:10.5281/zenodo.1417149 fatcat:23hazv3ssjelziwrllqrmbszfi

Self-Organizing Feature Map Preprocessed Vocabulary Renewal Algorithm for the Isolated Word Recognition System

A. Serackis, G. Tamulevicius, T. Sledevic, L. Stasionis, D. Navakauskas
2014 Elektronika ir Elektrotechnika  
The comparison of the time-dependent MFCC feature variations is performed using Needleman-Wunsch sequence alignment algorithm.  ...  The isolated word recognition is performed using dynamic time warping of the Mel-frequency cepstrum coefficients (MFCC) estimated during short-time analysis of speech signals.  ...  Comparison of the Time-dependent MFCC Variations The classified MFCC feature vectors give not only the grouping of the MFCC vectors but also provide the timedependent distribution of the self-organizing  ... 
doi:10.5755/j01.eee.20.6.7280 fatcat:llqtcq75fbfbdgf3ijtsty6r4u

PEAF: Learnable Power Efficient Analog Acoustic Features for Audio Recognition [article]

Boris Bergsma, Minhao Yang, Milos Cernak
2022 arXiv   pre-print
At the end of Moore's law, new computing paradigms are required to prolong the battery life of wearable and IoT smart audio devices.  ...  A novel theoretical framework based on information theory is established to analyze the information flow in each individual stage of the feature extraction pipeline.  ...  Feature comparison for KWS task We compared digital MFCCs, and analog PEAF variants on the Speech Command dataset V2 [19] , with all the 35 different classes and no added noise.  ... 
arXiv:2110.03715v2 fatcat:f45laehdbjajjkhg75g3wi2tda

Real Time Speech Recognition based on PWP Thresholding and MFCC using SVM

W. Helali, Ζ. Hajaiej, A. Cherif
2020 Engineering, Technology & Applied Science Research  
This paper proposes a new robust acoustic extraction approach development based on a hybrid technique consisting of Perceptual Wavelet Packet (PWP) and Mel Frequency Cepstral Coefficients (MFCCs).  ...  The proposed system was implemented on a Rasberry Pi board and its performance was checked in a clean environment, reaching 99% average accuracy.  ...  II COMPARISON OF RESOURCE CONSUMPTION AND EXECUTION TIME FOR DIFFERENT FEATURE EXTRACTION METHODSTable II shows that the average CPU usage is 10.9% in MF-PWP/MFCC.  ... 
doi:10.48084/etasr.3759 fatcat:33xlo3hd3vf6lmmvgmov3dngai

A Robust Feature Extraction Method for Real-Time Speech Recognition System on a Raspberry Pi 3 Board

A. Mnassri, M. Bennasr, C. Adnane
2019 Engineering, Technology & Applied Science Research  
A combination of Mel-frequency cepstral coefficients (MFCC) and discrete wavelet transform (DWT) is proposed.  ...  The proposed system has been implemented on Raspberry Pi 3 which is a suitable platform for real-time requirements.  ...  It can increase the classification rate up to 23% in comparison with DWT-MFCC and more than 50% compared to MFMFCC for white noise with a SNR of -5dB.  ... 
doi:10.48084/etasr.2533 fatcat:cweoiqk62ncnxegmclo4ujknly

An Examination of Emotion Recognition using Machine Learning Algorithms on Different Speech Databases

The performance of the speech recognition system is effects on the speech signals. The speech contains different emotions feelings.  ...  Many researchers introduced different emotion recognition techniques. However, these techniques achieved better performance but unsatisfied in identify emotion of natural languages.  ...  In the process of pre-processing different noise, techniques are used to remove the noise. Four different emotion recognition model was implemented.  ... 
doi:10.35940/ijitee.d1009.0394s220 fatcat:xetdyl7xg5agbahgvsuklmv7wa


Dacheng Tao, Hao Liu, Xiaoou Tang
2004 Proceedings of the 12th annual ACM international conference on Multimedia - MULTIMEDIA '04  
Experiments show that the 3 rd coefficient is the most relevant to music comparison out of 13 coefficients and the proposed simplified MFCC feature is able to achieve a reasonable trade-off between accuracy  ...  We also propose a new method for model-selection of K-means algorithm.  ...  MFCC Accuracy Analysis Different coefficients of the MFCC matrix represent different acoustic features.  ... 
doi:10.1145/1027527.1027639 dblp:conf/mm/TaoLT04 fatcat:y7c3p6hhefhkja5ljwhfijbe5y

Automatic Speaker Recognition using MFCC and Artificial Neural Network

Automatic speaker recognition is the process of identification of a person automatically from his/her voices.  ...  This proposed method gives an accuracy of 94.44%.  ...  In the future, we will be implementing ASR using Deep learning for better recognition. Fig. 1 : 1 Fig.1: Block diagram of the proposed method Fig. 2 : 2 Fig.2: steps of MFCC Feature Extraction.  ... 
doi:10.35940/ijitee.a1010.1191s19 fatcat:hsca4o5qtbe4fneh4h3e5yhyjm

Wake-Up-Word Feature Extraction on FPGA

Veton Z. Këpuska, Mohamed M. Eljhani, Brian H. Hight
2014 World Journal of Engineering and Technology  
The state of the art WUW-SR system is based on three different sets of features: Mel-Frequency Cepstral Coefficients (MFCC), Linear Predictive Coding Coefficients (LPC), and Enhanced Mel-Frequency Cepstral  ...  In (front-end of Wake-Up-Word Speech Recognition System Design on FPGA) [1] , we presented an experimental FPGA design and implementation of a novel architecture of a real-time spectrogram extraction processor  ...  We present an experimental design and implementation on FPGA of a novel architecture of a real-time feature extraction processor that generates three different features simultaneously.  ... 
doi:10.4236/wjet.2014.21001 fatcat:j5m3dkkjtrdmbd2cy6uqsdf6fq

Autocorrelation-based noise subtraction method with smoothing, overestimation, energy, and cepstral mean and variance normalization for noisy speech recognition

Gholamreza Farahani
2017 EURASIP Journal on Audio, Speech, and Music Processing  
Finally, with the addition of energy and cepstral mean and variance normalization to features of speech, recognition rate has improved considerably in comparison to standard features and other correlation-based  ...  rate improvement in average than MFCC features which is 64.91% on the Aurora 2 database.  ...  from Amirkabir University of Technology (Polytechnic), Tehran, Iran in 2000 and 2006, respectively.  ... 
doi:10.1186/s13636-017-0110-8 fatcat:evbor6qinnhadkfjio7qwbsupu
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