Real-time interactive speech technology at Threshold Technology, Incorporated

Basic real-time isolated-word recognition techniques are reviewed. Industrial applications of voice technology are described in chronological order of their development. Future research efforts are also discussed

Assessing the Performance of a Speech Recognition System Embedded in Low-Cost Devices

The main purpose of this research is to investigate how an Amazigh speech recognition system can be integrated into a low-cost minicomputer, specifically the Raspberry Pi, in order to improve the system\u27s automatic speech recognition capabilities. The study focuses on optimizing system parameters to achieve a balance between performance and limited system resources. To achieve this, the system employs a combination of Hidden Markov Models (HMMs), Gaussian Mixture Models (GMMs), and Mel Frequency Spectral Coefficients (MFCCs) with a speaker-independent approach. The system has been developed to recognize 20 Amazigh words, comprising of 10 commands and the first ten Amazigh digits. The results indicate that the recognition rate achieved on the Raspberry Pi system is 89.16% using 3 HMMs, 16 GMMs, and 39 MFCC coefficients. These findings demonstrate that it is feasible to create effective embedded Amazigh speech recognition systems using a low-cost minicomputer such as the Raspberry Pi. Furthermore, Amazigh linguistic analysis has been implemented to ensure the accuracy of the designed embedded speech system

Speech Recognition Implementation Using MFCC and DTW Algorithm for Home Automation

The use of speech recognition as part of home automation, especially for smart homes, is an exciting thing that is still being developed. That is because of human needs for comfort, convenience, quality of life, and better safety. Speech recognition built in this study is used as a device to control smart home devices by identifying the commands spoken by users, especially in a state of clean speech. The command used is a predetermined consecutive word. For the extraction of voice commands, the MFCC algorithm is used to match spoken words with templates using the Dynamic Time Warping (DTW) algorithm. DTW algorithm can find the difference between 2-time series that have different lengths of time. The results of the accuracy of this system by using these algorithms were successfully carried out by 86.67%, with an average time required to identify the commands of 5.28 seconds

Development of a Voice Controlled Electric Wheelchair to Aid the Movement of the Physically Challenged

Nigeria is said to have the highest number of physically challenged in Africa and second only to India in the world. Traditional Electrical Wheel Chair has some limitations. In order to assist the physically handicapped, this paper presents the development of a voice controlled wheelchair. The user can control the wheelchair by voice commands, such as “jagaba (go forward)” in Hausa. A grammar-based recognition parser was used in the system. The system comprises of a wheelchair motorize by a DC motor, works on inputs such as voice commands via an android phone and navigates according to the command and battery powered. Voice command input was taken from android mobile and converted into text which is transmitted to microcontroller via Bluetooth module to control the operation of DC motors. Also an IR detection system was used to detect the obstacle in the path of wheelchair to avoid its collision. The chair enables the handicapped person to independently move around. A running experiment with three (3) persons was carried out on speech recognition. 95.4% and 94.0% of the movement command and the verification command were obtained respectively. Keywords: Control, Home Navigation System, Microcontroller, Physically Challenged, Voice Command, Voice Recognition and Wheelchair

Study to determine potential flight applications and human factors design guidelines for voice recognition and synthesis systems

A study was conducted to determine potential commercial aircraft flight deck applications and implementation guidelines for voice recognition and synthesis. At first, a survey of voice recognition and synthesis technology was undertaken to develop a working knowledge base. Then, numerous potential aircraft and simulator flight deck voice applications were identified and each proposed application was rated on a number of criteria in order to achieve an overall payoff rating. The potential voice recognition applications fell into five general categories: programming, interrogation, data entry, switch and mode selection, and continuous/time-critical action control. The ratings of the first three categories showed the most promise of being beneficial to flight deck operations. Possible applications of voice synthesis systems were categorized as automatic or pilot selectable and many were rated as being potentially beneficial. In addition, voice system implementation guidelines and pertinent performance criteria are proposed. Finally, the findings of this study are compared with those made in a recent NASA study of a 1995 transport concept