Results 21 to 30 of about 3,790,103 (166)

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

Feature extraction method for reflective sound signal of high pressure water-jet target

Gong-kuang zidonghua, 2014
In order to improve recognition rate of target materials by using reflective sound signal of high pressure water-jet, in view of four common targets of mine, stone, brick and wood block, different feature extraction methods were used to identify target ...
SUN Shuai, YANG Hongtao, ZHANG Dongsu, FANG Chuanzhi, NIU Mingqiang   +4 more
doaj   +1 more source

Modeling Sub-Band Information Through Discrete Wavelet Transform to Improve Intelligibility Assessment of Dysarthric Speech.

International Journal of Interactive Multimedia and Artificial Intelligence, 2022
The speech signal within a sub-band varies at a fine level depending on the type, and level of dysarthria. The Mel-frequency filterbank used in the computation process of cepstral coefficients smoothed out this fine level information in the higher ...
Laxmi Priya Sahu, Gayadhar Pradhan, Jyoti Prakash Singh   +2 more
doaj   +1 more source

Discriminant Analysis of Voice Commands in the Presence of an Unmanned Aerial Vehicle

Information, 2021
The aim of this study was to perform discriminant analysis of voice commands in the presence of an unmanned aerial vehicle equipped with four rotating propellers, as well as to obtain background sound levels and speech intelligibility.
Marzena Mięsikowska
doaj   +1 more source

Emotion Recognition using Mel-Frequency Cepstral Coefficients

Journal of Natural Language Processing, 2007
In this paper, we propose a new approach to emotion recognition. Prosodic features are currently used in most emotion recognition algorithms. However, emotion recognition algorithms using prosodic features are not sufficiently accurate. Therefore, we focused on the phonetic features of speech for emotion recognition.
Sato, Nobuo, Obuchi, Yasunari
openaire   +3 more sources

Wavelet based feature combination for recognition of emotions

Ain Shams Engineering Journal, 2018
In this paper, authors tried to develop reduced combinational features for emotional speech recognition. The spectral/cepstral features like wavelet coefficient, LPCC (linear prediction cepstral coefficient) and MFCC (mel-frequency cepstral coefficient ...
Hemanta Kumar Palo, Mihir Narayan Mohanty   +1 more
doaj   +1 more source

SYSTEM OF RECOGNITION THE STEGANOGRAPHIC-TRANSFORMED VOICE COMMANDS OF THE UAV CONTROL

Радіоелектронні і комп'ютерні системи, 2018
It is created the system of recognition the steganographic-transformed voice commands of unmanned aerial vehicle control based on a cepstral analysis.
Александр Юрьевич Лавриненко, Юрий Анатольевич Кочергин, Георгий Филимонович Конахович   +2 more
doaj   +1 more source

Sistem Pengenalan Suara Dengan Metode Mel Frequency Cepstral Coefficients Dan Gaussian Mixture Model

Komputika, 2022
ABSTRAK – Teknologi biometrik sedang menjadi tren teknologi dalam berbagai bidang kehidupan. Teknologi biometrik memanfaatkan bagian tubuh manusia sebagai alat ukur sistem yang memiliki keunikan disetiap individu.
Ababil Azies Sasilo, Rizal Adi Saputra, Ika Purwanti Ningrum   +2 more
doaj   +1 more source

Speech reconstruction from mel frequency cepstral coefficients and pitch frequency [PDF]

2000 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.00CH37100), 2002
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, Ron Hoory, Gilad Cohen, Meir Zibulski   +3 more
openaire   +2 more sources

Mel-frequency cepstral coefficient-based bandwidth extension of narrowband speech [PDF]

Interspeech 2008, 2008
Abstract We present a novel MFCC-based scheme for the BandwidthExtension (BWE) of narrowband speech. BWE is based onthe assumption that narrowband speech (0.3–3.4 kHz) cor-relates closely with the highband signal (3.4–7 kHz), en-abling estimation of the highband frequency content given thenarrow band.
Amr H. Nour-Eldin, Peter Kabal
openaire   +1 more source