scholarly journals VOICE IDENTIFICATION BASED ON THE I-VECTOR AND DEEP NEURAL NETWORKS USING SHORT UTTERANCES

2020 ◽  
Vol 3 (77) ◽  
pp. 82-90
Author(s):  
O. Mamyrbayev, ◽  
◽  
A. Akhmediyarov, ◽  
A. Kydyrbekov, ◽  
N. Mekebayev, ◽  
...  
Keyword(s):  
Deep Neural Networks ◽  
Voice Recognition ◽  
Vector System ◽  
Nonlinear Mapping ◽  
Voice Identification ◽  
Large Spread ◽  
Short Utterances ◽  
User Recognition ◽  
The Voice ◽  
Distinguishing Features

Text-independent voice recognition of the user using short sentences is a very difficult task due to the large spread and inconsistency of the content between short sentences, in order to improve user recognition by voice, it is planned to highlight several sets of distinguishing features that contain more information related to the voice. The results show that the i-vector DNN system is superior to the GMM i-vector system for various durations. However, the characteristics of both systems deteriorate significantly as the duration of the sentences decreases. To solve this problem, we propose two new nonlinear mapping methods that train DNN models to map i-vectors extracted from short sentences to their corresponding i-vectors of long sentences.

scholarly journals Pengaruh Perubahan Pitch dan Formant Terhadap Hasil Identifikasi Kepemilikan Suara Dengan Metode Audio Forensik

2021 ◽  
Vol 9 (1) ◽  
pp. 1-8
Author(s):  
Mifta Nur Farid ◽  
Dani Dwi Putra ◽  
Barokatun Hasanah
Keyword(s):  
Analysis Of Variance ◽  
Voice Recognition ◽  
Frequency Characteristics ◽  
Sound Recordings ◽  
Voice Identification ◽  
Recorded Sound ◽  
Audio Forensics ◽  
The Difference ◽  
Pitch Analysis ◽  
The Voice

Audio forensics is a field of science that analyzes audio such as sound recordings. Voice recordings always have information in the form of frequency characteristics, the identities of these frequencies can be identified. Furthermore, an analysis of changes in pitch and formant will be carried out. This study used pitch analysis and analysis of variance on formants. With the correct procedure for handling recorded sound evidence which is then followed by procedural examination and analysis, it is hoped that the results of the voice recognition examination can scientifically show the ownership of the voice in the recording. Based on the results of the overall analysis of the sound recordings of evidence and comparison after carrying out various stages of analysis, the voice recordings are "not identical" from the same person. The thing that causes the inequality in voice identification is the difference in intonation or tone of the subject's speech when the voice is recorded.

scholarly journals THE IMPORTANCE OF VOICE IDENTIFICATION IN THE WITNESS RECOGNITION PROCEDURE

TEME ◽  
2020 ◽  
pp. 1157
Author(s):  
Jadranka R Otašević ◽  
Saša Atanasov
Keyword(s):  
Voice Recognition ◽  
Legal Framework ◽  
Point Of View ◽  
Theoretical Point ◽  
Witness Testimony ◽  
Voice Identification ◽  
Procedure Code ◽  
The Republic ◽  
Direct Recognition ◽  
The Voice

From a theoretical point of view, this paper considers the evidentiary action of recognizing the voice of the perpetrator by the witness. It is the identification of the voice by a person who is usually an "unprofessional listener". Due to the specificity of the voice as an object of recognition, the involvement of forensics (linguists and phoneticians) in the organization and immediate realization of the voice recognition action seems inevitable. Their activity would be manifested in giving guidance to the authority on how to increase the efficiency of voice identification and the accuracy of witness testimony. The witness gives evidence based on his perceptual (auditory) abilities in a procedure prescribed by the law, in which the credibility of his/her testimony is simultaneously checked and assessed. The Criminal Procedure Code of the Republic of Serbia establishes the legal framework for taking the voice recognition action, while the content of performing the direct recognition action is determined by the criminal-tactical rules.

Lampu Sein Helm Sepeda Berbasis Voice Recognition

2019 ◽  
Vol 11 (01) ◽  
pp. 20-25
Author(s):  
Indra Saputra ◽  
Parulian Silalahi ◽  
Bayu Cahyawan ◽  
Imam Akbar
Keyword(s):  
Voice Recognition ◽  
Driving Safety ◽  
Bicycle Helmet ◽  
Turn Signal ◽  
Voice Command ◽  
The Voice ◽  
Indicator Signal

Bicycles are not equipped with the turn signal. For driving safety, a bicycle helmet with a turn signal is designed with voice rrecognition. It is using the Arduino Nano as a controller to control the ON and OFF of turn signal lights with voice commands. This device uses a Voice Recognition sensor and microphone that placed on a bicycle helmet. When the voice command is mentioned in the microphone, the Voice Recognition sensor will detect the command specified, the sensor will automatically read and send a signal to Arduino, then the turn signal will light up as instructed, the Arduino on the helmet will send an indicator signal via the Bluetooth Module. The device is able to detect sound with a percentage of 80%. The tool can work with a distance of <2 meters with noise <71 db.

ANALYSIS OF VOICE CUES IN RECOGNITION OF SARCASM

2019 ◽  
Vol 12 ◽  
Author(s):  
Basavaraj N Hiremath ◽  
Malini M Patilb
Keyword(s):  
Feature Extraction ◽  
Computer Program ◽  
Principle Component Analysis ◽  
Voice Recognition ◽  
Component Analysis ◽  
Recognition System ◽  
Principle Component ◽  
Whole Process ◽  
The Voice

The voice recognition system is about cognizing the signals, by feature extraction and identification of related parameters. The whole process is referred to as voice analytics. The paper aims at analysing and synthesizing the phonetics of voice using a computer program called “PRAAT”. The work carried out in the paper also supports the analysis of voice segmentation labelling, analyse the unique features of voice cues, understanding physics of voice, further the process is carried out to recognize sarcasm. Different unique features identified in the work are, intensity, pitch, formants related to read, speak, interactive and declarative sentences by using principle component analysis.

Voice Assistant — Application of Speech Recognition Technology in the Android System

2014 ◽  
Vol 596 ◽  
pp. 384-387
Author(s):  
Ge Liu ◽  
Hai Bing Zhang
Keyword(s):  
Speech Recognition ◽  
Service Providers ◽  
Voice Recognition ◽  
Working Process ◽  
Bottleneck Problems ◽  
Speech Recognition Technology ◽  
Android System ◽  
The Voice

This paper introduces the concept of Voice Assistant, the voice recognition service providers, several typical Voice Assistant product, and then the basic working process of the Voice Assistant is described in detail and proposed the technical bottleneck problems in the development of Voice Assistant software.

scholarly journals Design and Fabrication of Voice Controlled Unmanned Aerial Vehicle

2016 ◽  
Vol 5 (3) ◽  
pp. 205
Author(s):  
S. Sakthi Anand ◽  
R. Mathiyazaghan
Keyword(s):  
Control System ◽  
Unmanned Aerial Vehicles ◽  
Unmanned Aerial Vehicle ◽  
Voice Recognition ◽  
Search And Rescue ◽  
Voice Input ◽  
Recognition Process ◽  
Aerial Vehicles ◽  
Aerial Vehicle ◽  
The Voice

<p class="Default">Unmanned Aerial Vehicles have gained well known attention in recent years for a numerous applications such as military, civilian surveillance operations as well as search and rescue missions. The UAVs are not controlled by professional pilots and users have less aviation experience. Therefore it seems to be purposeful to simplify the process of aircraft controlling. The objective is to design, fabricate and implement an unmanned aerial vehicle which is controlled by means of voice recognition. In the proposed system, voice commands are given to the quadcopter to control it autonomously. This system is navigated by the voice input. The control system responds to the voice input by voice recognition process and corresponding algorithms make the motors to run at specified speeds which controls the direction of the quadcopter.</p>

scholarly journals Voice Identification Using MFCC and Vector Quantization

2020 ◽  
Vol 17 (3(Suppl.)) ◽  
pp. 1019
Author(s):  
Bassel Alkhatib ◽  
Mohammad Madian Waleed Kamal Eddin
Keyword(s):  
Vector Quantization ◽  
Speech Processing ◽  
Large Scale ◽  
Feature Matching ◽  
Speaker Identification ◽  
Voice Recognition ◽  
Security Systems ◽  
Voice Identification ◽  
New Methodologies ◽  
Quick Search

The speaker identification is one of the fundamental problems in speech processing and voice modeling. The speaker identification applications include authentication in critical security systems and the accuracy of the selection. Large-scale voice recognition applications are a major challenge. Quick search in the speaker database requires fast, modern techniques and relies on artificial intelligence to achieve the desired results from the system. Many efforts are made to achieve this through the establishment of variable-based systems and the development of new methodologies for speaker identification. Speaker identification is the process of recognizing who is speaking using the characteristics extracted from the speech's waves like pitch, tone, and frequency. The speaker's models are created and saved in the system environment and used to verify the identity required by people accessing the systems, which allows access to various services that are controlled by voice, speaker identification involves two main parts: the first part is the feature extraction and the second part is the feature matching.

INFORMATION SYSTEM FOR PEOPLE WITH HEARING IMPAIRMENT

2021 ◽  
Vol 335 (1) ◽  
pp. 54-59
Author(s):  
Y.S. Nurakhov ◽  
A.E. Kami
Keyword(s):  
Quality Of Life ◽  
Information System ◽  
Public Life ◽  
Voice Recognition ◽  
Hearing Impairments ◽  
Hardware Complex ◽  
Software And Hardware ◽  
Functional Blocks ◽  
The Voice

The article presents the development of an information system for recognizing voice into text for people with hearing impairments, which makes it possible to improve the quality of life and interaction in society with other people. The device, software, functional blocks and subsystems of the information system are described. Examples of possible application and placement of the system in various spheres of public life are given. One of the types of implementation of the voice recognition information system is described. The development and creation of prototypes of a device for people with hearing impairments is considered. In the course of the research, the Google Speech Api technology was selected for speech recognition. In addition, this article presents a software and hardware complex that allows you to translate speech into text and then display it on the screen. Arduino UNO-based devices were chosen to achieve the goal. All information is processed on the smartphone of people with hearing impairments, which is sent to the device via Bluetooth with Arduino.

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