scholarly journals Smart information desk system with voice assistant for universities

2021 ◽  
Vol 11 (6) ◽  
pp. 5206
Author(s):  
Dabiah Alboaneen ◽  
Dalia Alsaffar ◽  
Amani Alqahtani ◽  
Lama Alamri ◽  
Amjad Alfahhad ◽  
...  
Keyword(s):  
Voice Recognition ◽  
General Information ◽  
Raspberry Pi ◽  
Mirror Surface ◽  
Academic Information ◽  
The University ◽  
The Voice

This article aims to develop a smart information desk system through a smart mirror for universities. It is a mirror with extra capabilities of displaying answers for academic inquiries such as asking about the lecturers’ office numbers and hours, exams dates and times on the mirror surface. In addition, the voice recognition feature was used to answer spoken inquiries in audio responds to serve all types of users including disabled ones. Furthermore, the system showed general information such as date, weather, time and the university map. The smart mirror was connected to an outdoor camera to monitor the traffics at the university entrance gate. The system was implemented on a Raspberry Pi 4 model B connected to a two-way mirror and an infrared (IR) touch frame. The results of this study helped to overcome the problem of the information desk absence in the university. Therefore, it helped users to save their time and effort in making requests for important academic information.

scholarly journals CAMPUS MITHRA: Design and implementation of voice based attender robot

2021 ◽  
Vol 2115 (1) ◽  
pp. 012006
Author(s):  
Ambreen Saniya ◽  
M S Chandana ◽  
Maria Sharon Dennis ◽  
K Pooja ◽  
D J Chaithanya ◽  
...  
Keyword(s):  
Natural Language ◽  
Voice Recognition ◽  
Embedded Control ◽  
Railway Stations ◽  
Human Voice ◽  
Domains Of Life ◽  
The University ◽  
The Voice ◽  
University Setting ◽  
Line Following

Abstract A robot is a machine which is programmed by a computer and the movements and functions of which are controlled by an external or an embedded control. It has dynamic uses in all domains of life. A robot in a university setting can be used as an attender for passing circulars around instead of multiple attenders doing the task manually which is a cost and time consuming process. Parents often find it difficult to navigate through the unfamiliar university. In this paper, we have focused on a voice based attender robot with line following capabilities along with speech recognition that can be used at universities for a variety of purposes like passing around the circulars, interacting with parents and helping them navigate through the university through Spoken Natural Language. The main objectives of the proposed work is to reduce the burden of passing circulars, calling a student/faculty on the attender by designing a robot that is also competent enough to connect with human through spoken natural language such as English or Kannada, so that it interacts with parents who are new to the institution and do not know whom to approach. The main aim of this work is to introduce a robot that it is able to interact with human through the Spoken Natural Language. Here, the focus is on two languages; English and Kannada. This system uses a voice recognition module to recognize human voice and a voice playback module is used to reply back in either English or Kannada according to the user’s command. It can work in two modes, the voice recognition mode to answer to user queries or in line following mode to pass circulars, call student/faculty. In this way, the voice based attender robot finds its applications in the university setting. But it is not limited to only universities. It can also be further implemented in places like railway stations, bus stations, big factories and other similar surroundings.

scholarly journals Comparison of CNNs and SVM for voice control wheelchair

2020 ◽  
Vol 9 (3) ◽  
pp. 387
Author(s):  
Mohammad Shahrul Izham Sharifuddin ◽  
Sharifalillah Nordin ◽  
Azliza Mohd Ali
Keyword(s):  
Feature Extraction ◽  
Processing Time ◽  
Voice Recognition ◽  
The Other ◽  
Raspberry Pi ◽  
Intelligent Wheelchair ◽  
Voice Control ◽  
Voice Data ◽  
The Voice ◽  
Feature Extraction Technique

In this paper, we develop an intelligent wheelchair using CNNs and SVM voice recognition methods. The data is collected from Google and some of them are self-recorded. There are four types of data to be recognized which are go, left, right, and stop. Voice data are extracted using MFCC feature extraction technique. CNNs and SVM are then used to classify and recognize the voice data. The motor driver is embedded in Raspberry PI 3B+  to control the movement of the wheelchair prototype. CNNs produced higher accuracy i.e. 95.30% compared to SVM which is only 72.39%. On the other hand, SVM only took 8.21 seconds while CNNs took 250.03 seconds to execute. Therefore, CNNs produce better result because noise are filtered in the feature extraction layer before classified in the classification layer. However, CNNs took longer time due to the complexity of the networks and the less complexity implementation in SVM give shorter processing time.

scholarly journals Review of Voice Controlled Robotic Arm-Raspberry Pi

2021 ◽  
Vol 5 (2) ◽  
pp. 1-4
Author(s):  
B. Shoban Babu ◽  
V. Priyadharshini ◽  
Prince Patel
Keyword(s):  
Wireless Communication ◽  
Life Skills ◽  
Voice Recognition ◽  
Smart Phone ◽  
Assistive Robotics ◽  
Robotic Arm ◽  
Raspberry Pi ◽  
Automotive Applications ◽  
The Voice ◽  
Knowledge Communication

One of the most essential life skills is to be able to communicate easily. In order to produce greater comprehension, communication is described as transmitting knowledge. Communication and technologies are not mutually exclusive. Speech Recognition is a technique that facilitates the processing of voice information to text and is independent of the speaker. This enables it to be used in various applications, from digital assistants to machinery control. The aim of this paper is to study numerous robotic vehicles powered by human speech commands. To accomplish this functionality, most of these systems run with the use of an android smart phone that transmits voice commands to a raspberry pi. The voice-operated robot is used to build one moving object. It is moved as per the voice recognition module commands, and the robot obtains that command. The robot compares the command with the stored software and then sets the command using wireless communication as per voice. These suggested methods would be useful for devices such as assistive robotics for people with disabilities or automotive applications such as work robots.

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.

scholarly journals Development of a Smartphone-Based University Library Navigation and Information Service Employing Wi-Fi Location Fingerprinting

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 432
Author(s):  
Guenther Retscher ◽  
Alexander Leb
Keyword(s):  
Performance Improvement ◽  
Low Cost ◽  
Information Service ◽  
Raspberry Pi ◽  
University Library ◽  
Stop And Go ◽  
Promising Solution ◽  
Localization Performance ◽  
The University ◽  
Suitable Location

A guidance and information service for a University library based on Wi-Fi signals using fingerprinting as chosen localization method is under development at TU Wien. After a thorough survey of suitable location technologies for the application it was decided to employ mainly Wi-Fi for localization. For that purpose, the availability, performance, and usability of Wi-Fi in selected areas of the library are analyzed in a first step. These tasks include the measurement of Wi-Fi received signal strengths (RSS) of the visible access points (APs) in different areas. The measurements were carried out in different modes, such as static, kinematic and in stop-and-go mode, with six different smartphones. A dependence on the positioning and tracking modes is seen in the tests. Kinematic measurements pose much greater challenges and depend significantly on the duration of a single Wi-Fi scan. For the smartphones, the scan durations differed in the range of 2.4 to 4.1 s resulting in different accuracies for kinematic positioning, as fewer measurements along the trajectories are available for a device with longer scan duration. The investigations indicated also that the achievable localization performance is only on the few meter level due to the small number of APs of the University own Wi-Fi network deployed in the library. A promising solution for performance improvement is the foreseen usage of low-cost Raspberry Pi units serving as Wi-Fi transmitter and receiver.

Periprosthetic Leakage in Tracheoesophageal Prosthesis: Proposal of a Standardized Therapeutic Algorithm

2021 ◽  
pp. 019459982098334
Author(s):  
Claudio Parrilla ◽  
Ylenia Longobardi ◽  
Jacopo Galli ◽  
Mario Rigante ◽  
Gaetano Paludetti ◽  
...  
Keyword(s):  
Total Laryngectomy ◽  
Retrospective Cohort ◽  
Voice Prosthesis ◽  
Management Algorithm ◽  
Therapeutic Algorithm ◽  
Periprosthetic Leakage ◽  
Tracheoesophageal Puncture ◽  
The University ◽  
The Voice

Objective Periprosthetic leakage represents the most demanding long-term complication in the voice prosthesis rehabilitation. The aim of this article is to discuss the various causes of periprosthetic leakage and to propose a systematic management algorithm. Study Design Retrospective cohort study. Setting Otolaryngology clinic of the University Polyclinic A. Gemelli–IRCCS Foundation. Methods The study included 115 patients with voice prosthesis who were treated from December 2014 to December 2019. All patients who experienced periprosthetic leakage were treated with the same step-by-step therapeutic approach until it was successful. Incidence, management, and success rate of every attempt are analyzed and discussed. Results Periprosthetic leakage was reported 330 times by 82 patients in 1374 clinic accesses. Radiotherapy, timing of tracheoesophageal puncture, and type of total laryngectomy (primary or salvage) did not influence the incidence of periprosthetic leakage. Salvage total laryngectomy increases the risk of more clinically relevant leakages. Conclusion By using a systematic algorithm with a step-by-step standardized approach, periprosthetic leakage management could become a less treacherous issue.

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.

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