Radek Martinek¹, Jan Baros¹, Rene Jaros¹, Lukas Danys^1,*, Jan Nedoma²

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4659-4676, 2022, DOI:10.32604/cmc.2022.019904 - 14 January 2022

Abstract This pilot study focuses on employment of hybrid LMS-ICA system for in-vehicle background noise reduction. Modern vehicles are nowadays increasingly supporting voice commands, which are one of the pillars of autonomous and SMART vehicles. Robust speaker recognition for context-aware in-vehicle applications is limited to a certain extent by in-vehicle background noise. This article presents the new concept of a hybrid system, which is implemented as a virtual instrument. The highly modular concept of the virtual car used in combination with real recordings of various driving scenarios enables effective testing of the investigated methods of in-vehicle More >

Mohamed Hashim Changrampadi^1,*, A. Shahina², M. Badri Narayanan², A. Nayeemulla Khan³

Intelligent Automation & Soft Computing, Vol.32, No.2, pp. 1309-1323, 2022, DOI:10.32604/iasc.2022.022021 - 17 November 2021

Abstract Research in speech recognition is progressing with numerous state-of-the-art results in recent times. However, relatively fewer research is being carried out in Automatic Speech Recognition (ASR) for languages with low resources. We present a method to develop speech recognition model with minimal resources using Mozilla DeepSpeech architecture. We have utilized freely available online computational resources for training, enabling similar approaches to be carried out for research in a low-resourced languages in a financially constrained environments. We also present novel ways to build an efficient language model from publicly available web resources to improve accuracy in More >

Nadia H. Alsulami^1,*, Amani T. Jamal¹, Lamiaa A. Elrefaei²

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 85-108, 2022, DOI:10.32604/cmc.2022.019450 - 03 November 2021

Abstract Lip-reading technologies are rapidly progressing following the breakthrough of deep learning. It plays a vital role in its many applications, such as: human-machine communication practices or security applications. In this paper, we propose to develop an effective lip-reading recognition model for Arabic visual speech recognition by implementing deep learning algorithms. The Arabic visual datasets that have been collected contains 2400 records of Arabic digits and 960 records of Arabic phrases from 24 native speakers. The primary purpose is to provide a high-performance model in terms of enhancing the preprocessing phase. Firstly, we extract keyframes from… More >

Shibli Nisar¹, Muhammad Asghar Khan^2,*, Fahad Algarni³, Abdul Wakeel¹, M. Irfan Uddin⁴, Insaf Ullah²

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2991-3004, 2022, DOI:10.32604/cmc.2022.020376 - 27 September 2021

Abstract One of the most commonly reported disabilities is vision loss, which can be diagnosed by an ophthalmologist in order to determine the visual system of a patient. This procedure, however, usually requires an appointment with an ophthalmologist, which is both time-consuming and expensive process. Other issues that can arise include a lack of appropriate equipment and trained practitioners, especially in rural areas. Centered on a cognitively motivated attribute extraction and speech recognition approach, this paper proposes a novel idea that immediately determines the eyesight deficiency. The proposed system uses an adaptive filter bank with weighted… More >

Radek Martinek¹, Rene Jaros¹, Jan Baros¹, Lukas Danys¹, Aleksandra Kawala-Sterniuk², Jan Nedoma^3,*, Zdenek Machacek¹, Jiri Koziorek¹

CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 1073-1096, 2021, DOI:10.32604/cmc.2021.017568 - 04 June 2021

Abstract This paper discusses the reduction of background noise in an industrial environment to extend human-machine-interaction. In the Industry 4.0 era, the mass development of voice control (speech recognition) in various industrial applications is possible, especially as related to augmented reality (such as hands-free control via voice commands). As Industry 4.0 relies heavily on radiofrequency technologies, some brief insight into this problem is provided, including the Internet of things (IoT) and 5G deployment. This study was carried out in cooperation with the industrial partner Brose CZ spol. s.r.o., where sound recordings were made to produce a dataset.… More >

Amany M. Sarhan¹, Nada M. Elshennawy¹, Dina M. Ibrahim^1,2,*

CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 1531-1549, 2021, DOI:10.32604/cmc.2021.016509 - 13 April 2021

Abstract

Lip reading is typically regarded as visually interpreting the speaker’s lip movements during the speaking. This is a task of decoding the text from the speaker’s mouth movement. This paper proposes a lip-reading model that helps deaf people and persons with hearing problems to understand a speaker by capturing a video of the speaker and inputting it into the proposed model to obtain the corresponding subtitles. Using deep learning technologies makes it easier for users to extract a large number of different features, which can then be converted to probabilities of letters to obtain accurate results.

… More >

Hao Wu^1,*, Arun Kumar Sangaiah²

Intelligent Automation & Soft Computing, Vol.28, No.1, pp. 121-132, 2021, DOI:10.32604/iasc.2021.016457 - 17 March 2021

Abstract In oral English teaching in China, teachers usually improve students’ pronunciation by their subjective judgment. Even to the same student, the teacher gives different suggestions at different times. Students’ oral pronunciation features can be obtained from the reconstructed acoustic and natural language features of speech audio, but the task is complicated due to the embedding of multimodal sentences. To solve this problem, this paper proposes an English speech recognition based on enhanced temporal convolution network. Firstly, a suitable UNet network model is designed to extract the noise of speech signal and achieve the purpose of… More >

Li-Hong Juang^1,*, Yi-Hua Zhao²

Intelligent Automation & Soft Computing, Vol.26, No.2, pp. 291-301, 2020, DOI:10.31209/2020.100000164

Abstract Speech recognition is one of the most convenient forms of human beings engaging in the exchanging of information. In this research, we want to make robots understand human language and communicate with each other through the human language, and to realize man–machine interactive and humanoid– robot interactive. Therefore, this research mainly studies NAO robots’ speech recognition and humanoid communication between double -humanoid robots. This paper introduces the future direction and application prospect of speech recognition as well as its basic method and knowledge of speech recognition fields. This research also proposes the application of the… More >

Jeong-Sik Park¹, Seok-Hoon Kim^2,*

Intelligent Automation & Soft Computing, Vol.26, No.1, pp. 149-159, 2020, DOI:10.31209/2019.100000136

Abstract Variety types of smart home devices have a main function of a human-machine interaction by speech recognition. Speech recognition system may be vulnerable to rapidly changing noises in home environments. This study proposes an efficient noise cancellation approach to eliminate the noises directly on the devices in real time. Firstly, we propose an advanced voice activity detection (VAD) technique to efficiently detect speech and non-speech regions on the basis of spectral property of speech signals. The VAD is then employed to enhance the conventional spectral subtraction method by steadily estimating noise signals in non-speech regions. More >

Lamia Bouafif¹, Noureddine Ellouze^2,*

Sound & Vibration, Vol.54, No.1, pp. 1-15, 2020, DOI:10.32604/sv.2020.08665 - 01 March 2020

Abstract In order to assist physically handicapped persons in their movements, we developed an embedded isolated word speech recognition system (ASR) applied to voice control of smart wheelchairs. However, in spite of the existence in the industrial market of several kinds of electric wheelchairs, the problem remains the need to manually control this device by hand via joystick; which limits their use especially by people with severe disabilities. Thus, a significant number of disabled people cannot use a standard electric wheelchair or drive it with difficulty. The proposed solution is to use the voice to control and… More >