Combined Bidirectional Long Short-Term Memory with Mel-Frequency Cepstral Coefficients Using Autoencoder for Speaker Recognition [PDF]
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) [PDF]
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]
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
Analysis of COVID-19 Heavy Cough Sounds Using Bark Wavelet Cepstral Coefficients [PDF]
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
MEL frequency cepstral coefficients (MFCC) of original speakers and their imitators
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
Combination of VMD Mapping MFCC and LSTM: A New Acoustic Fault Diagnosis Method of Diesel Engine
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
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
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
Speech reconstruction from mel frequency cepstral coefficients and pitch frequency [PDF]
This paper presents a novel low complexity, frequency domain algorithm for reconstruction of speech from the mel-frequency cepstral coefficients (MFCC), commonly used by speech recognition systems, and the pitch frequency values. The reconstruction technique is based on the sinusoidal speech representation.
Dan Chazan +3 more
openaire +1 more source
Regional language Speech Emotion Detection using Deep Neural Network [PDF]
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

