Results 1 to 10 of about 6,514 (211)
Applied Sciences, 2023 Recently, neural network technology has shown remarkable progress in speech recognition, including word classification, emotion recognition, and identity recognition. This paper introduces three novel speaker recognition methods to improve accuracy.
Young-Long Chen +3 more
doaj +4 more sources
Identification of Language using Mel-Frequency Cepstral Coefficients (MFCC)
Procedia Engineering, 2012 AbstractThis paper focuses on the task of identifying a language from speech signal. In this paper, we have use Mel-frequency cepstral coefficient as features. Language identification models are developed for fifteen Indian languages namely Assamese, Bangla, Guajarati, Hindi, Kannada, Kashmiri, Malayalam, Marathi, Nepali, Oriya, Punjabi, Rajasthani ...
Shashidhar G Koolagudi
exaly +3 more sources
Using Mel-Frequency Cepstral Coefficients in Missing Data Technique [PDF]
EURASIP Journal on Advances in Signal Processing, 2004 Filter bank is the most common feature being employed in the research of the marginalisation approaches for robust speech recognition due to its simplicity in detecting the unreliable data in the frequency domain.
Gang Wei +3 more
doaj +2 more sources
MEL frequency cepstral coefficients (MFCC) of original speakers and their imitators
Archives of Acoustics, 2014 The results of intra- and interspeaker distances between MFCC vectors obtained from speech samples of eight well-known Polish personalities and their imitations performed by cabaret entertainers are presented and discussed.
W. Majewski
doaj +1 more source
Analysis of COVID-19 Heavy Cough Sounds Using Bark Wavelet Cepstral Coefficients [PDF]
The Egyptian International Journal of Engineering Sciences and Technology, 2022 Coronavirus is known as COVID-19. It spreads in all over the world as pandemic. Until writing this paper, 164.5 million person worldwide is affected with this disease. Over 3.4 million people are died due to that disease.
Mohamed Azmy
doaj +1 more source
Combination of VMD Mapping MFCC and LSTM: A New Acoustic Fault Diagnosis Method of Diesel Engine
Sensors, 2022 Diesel engines have a wide range of functions in the industrial and military fields. An urgent problem to be solved is how to diagnose and identify their faults effectively and timely.
Hao Yan +5 more
doaj +1 more source
Mel Frequency Cepstral Coefficient and its Applications: A Review
IEEE Access, 2022 Feature extraction and representation has significant impact on the performance of any machine learning method. Mel Frequency Cepstrum Coefficient (MFCC) is designed to model features of audio signal and is widely used in various fields. This paper aims to review the applications that the MFCC is used for in addition to some issues that facing the MFCC
Zrar Kh. Abdul +1 more
openaire +2 more sources
Scientific African, 2021 Amyotrophic Lateral Sclerosis (ALS) and Myopathy are the most well-known neuromuscular diseases. Electromyography (EMG) signal is hugely used in the diagnosis of these neuromuscular disorders.
Abdelali Belkhou +2 more
doaj +1 more source
Regional language Speech Emotion Detection using Deep Neural Network [PDF]
ITM Web of Conferences, 2022 Speaking is the most basic and efficient mode of human contact. Emotions assist people in communicating and understanding others’ viewpoints by transmitting sentiments and providing feedback.The basic objective of speech emotion recognition is to enable ...
Padman Sweta, Magare Dhiraj
doaj +1 more source
Linear versus mel frequency cepstral coefficients for speaker recognition [PDF]
2011 IEEE Workshop on Automatic Speech Recognition & Understanding, 2011 Mel-frequency cepstral coefficients (MFCC) have been dominantly used in speaker recognition as well as in speech recognition. However, based on theories in speech production, some speaker characteristics associated with the structure of the vocal tract, particularly the vocal tract length, are reflected more in the high frequency range of speech.
Xinhui Zhou +4 more
openaire +1 more source