Speech recognition systems have become a unique human-computer interaction(HCI)family.Speech is one of the most naturally developed human abilities;speech signal processing opens up a transparent and hand-free computa...Speech recognition systems have become a unique human-computer interaction(HCI)family.Speech is one of the most naturally developed human abilities;speech signal processing opens up a transparent and hand-free computation experience.This paper aims to present a retrospective yet modern approach to the world of speech recognition systems.The development journey of ASR(Automatic Speech Recognition)has seen quite a few milestones and breakthrough technologies that have been highlighted in this paper.A step-by-step rundown of the fundamental stages in developing speech recognition systems has been presented,along with a brief discussion of various modern-day developments and applications in this domain.This review paper aims to summarize and provide a beginning point for those starting in the vast field of speech signal processing.Since speech recognition has a vast potential in various industries like telecommunication,emotion recognition,healthcare,etc.,this review would be helpful to researchers who aim at exploring more applications that society can quickly adopt in future years of evolution.展开更多
Automatic speech recognition systems are developed for translating the speech signals into the corresponding text representation.This translation is used in a variety of applications like voice enabled commands,assist...Automatic speech recognition systems are developed for translating the speech signals into the corresponding text representation.This translation is used in a variety of applications like voice enabled commands,assistive devices and bots,etc.There is a significant lack of efficient technology for Indian languages.In this paper,an wavelet transformer for automatic speech recognition(WTASR)of Indian language is proposed.The speech signals suffer from the problem of high and low frequency over different times due to variation in speech of the speaker.Thus,wavelets enable the network to analyze the signal in multiscale.The wavelet decomposition of the signal is fed in the network for generating the text.The transformer network comprises an encoder decoder system for speech translation.The model is trained on Indian language dataset for translation of speech into corresponding text.The proposed method is compared with other state of the art methods.The results show that the proposed WTASR has a low word error rate and can be used for effective speech recognition for Indian language.展开更多
The increased ownership of mobile phone users and the advancement of mobile applications enlarge the practicality and popularity of use for learning purposes among Chinese university students.However,even if innovativ...The increased ownership of mobile phone users and the advancement of mobile applications enlarge the practicality and popularity of use for learning purposes among Chinese university students.However,even if innovative functions of these applications are increasingly reported in relevant research in the education field,little research has been in the application of spoken English language.This paper examined the effect of using a Mobile-Assisted Language Learning(MALL)application“IELTS Liulishuo”(speaking English fluently in the IELTS test)as a unit of analysis to improve the English-speaking production of university students in China.The measurement of this mobile application in its effectiveness of validity and reliability is through the use of seven dimensional criteria.Although some technical and pedagogical issues challenge adoptions of MALL in some less-developed regions in China,the study showed positive effects of using a MALL oral English assessment application characterised with Automatic Speech Recognition(ASR)system on the improvement of complexity,accuracy,and fluency of English learners in China’s colleges.展开更多
文摘Speech recognition systems have become a unique human-computer interaction(HCI)family.Speech is one of the most naturally developed human abilities;speech signal processing opens up a transparent and hand-free computation experience.This paper aims to present a retrospective yet modern approach to the world of speech recognition systems.The development journey of ASR(Automatic Speech Recognition)has seen quite a few milestones and breakthrough technologies that have been highlighted in this paper.A step-by-step rundown of the fundamental stages in developing speech recognition systems has been presented,along with a brief discussion of various modern-day developments and applications in this domain.This review paper aims to summarize and provide a beginning point for those starting in the vast field of speech signal processing.Since speech recognition has a vast potential in various industries like telecommunication,emotion recognition,healthcare,etc.,this review would be helpful to researchers who aim at exploring more applications that society can quickly adopt in future years of evolution.
文摘Automatic speech recognition systems are developed for translating the speech signals into the corresponding text representation.This translation is used in a variety of applications like voice enabled commands,assistive devices and bots,etc.There is a significant lack of efficient technology for Indian languages.In this paper,an wavelet transformer for automatic speech recognition(WTASR)of Indian language is proposed.The speech signals suffer from the problem of high and low frequency over different times due to variation in speech of the speaker.Thus,wavelets enable the network to analyze the signal in multiscale.The wavelet decomposition of the signal is fed in the network for generating the text.The transformer network comprises an encoder decoder system for speech translation.The model is trained on Indian language dataset for translation of speech into corresponding text.The proposed method is compared with other state of the art methods.The results show that the proposed WTASR has a low word error rate and can be used for effective speech recognition for Indian language.
文摘The increased ownership of mobile phone users and the advancement of mobile applications enlarge the practicality and popularity of use for learning purposes among Chinese university students.However,even if innovative functions of these applications are increasingly reported in relevant research in the education field,little research has been in the application of spoken English language.This paper examined the effect of using a Mobile-Assisted Language Learning(MALL)application“IELTS Liulishuo”(speaking English fluently in the IELTS test)as a unit of analysis to improve the English-speaking production of university students in China.The measurement of this mobile application in its effectiveness of validity and reliability is through the use of seven dimensional criteria.Although some technical and pedagogical issues challenge adoptions of MALL in some less-developed regions in China,the study showed positive effects of using a MALL oral English assessment application characterised with Automatic Speech Recognition(ASR)system on the improvement of complexity,accuracy,and fluency of English learners in China’s colleges.
