Performance Analysis: AI-based VIST Audio Player by Microsoft Speech API by Ribwar Bakhtyar Ibrahim

Subjects: “…Speech Recognition, Microsoft Speech API, Subtitles, Speech to Text, speech-to-text recognition, Artificial Intelligence. …”
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qArI: A Hybrid CTC/Attention-Based Model for Quran Recitation Recognition Using Bidirectional LSTMP in an End-to-End Architecture by Sumayya Alfadhli, Hajar Alharbi, Asma Cherif

“…This research aims to improve the accuracy of speech recognition models for the recital of the Holy Quran. …”
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Isolated word recognition using neural networks by Mark Filipovič

“… This paper presents the speech recognition system, designed for recognition of 50 isolated Lithuanian words. …”
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Key technologies and development trends of intelligent customer service for operators by Xiaoliang MA, Ying LIU, Dequan DU, Lingling AN

“…The technology development trend of intelligent customer service for operators was discussed, and automatic speech recognition (ASR) transcription error correction technology, semantic extraction technology, encrypted database, and agent access control technology were introduced.Two different research directions of error detection and automatic error correction for speech recognition were analyzed, two directions of supervised learning and unsupervised learning were discussed, and big data encryption and agent access control technologies were introduced.At the same time, the technical directions of multimodal interaction technology, intelligent recommendation technology and disabled-oriented services were prospected.In conclusion, the development and innovation of intelligent customer service technology will bring a more efficient and convenient service experience to the communication industry and strongly promote the progress of the industry service level.…”
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Cross-Modal Functional Reorganization of Visual and Auditory Cortex in Adult Cochlear Implant Users Identified with fNIRS by Ling-Chia Chen, Pascale Sandmann, Jeremy D. Thorne, Martin G. Bleichner, Stefan Debener

“…Visual-evoked activation in auditory cortex is a maladaptive functional reorganization whereas auditory-evoked activation in visual cortex is beneficial for speech recognition in CI users. We investigated their joint influence on CI users’ speech recognition, by testing 20 postlingually deafened CI users and 20 NH controls with functional near-infrared spectroscopy (fNIRS). …”
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Articulatory-to-Acoustic Conversion Using BiLSTM-CNN Word-Attention-Based Method by Guofeng Ren, Guicheng Shao, Jianmei Fu

“…Aiming at developing novel recognition feature and application to speech recognition, this paper presents a new method for articulatory-to-acoustic conversion. …”
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Research and Implementation of Intelligent Home Pension System Based on Speech and Semantic Recognition by Guokun Xie, Sen Hao, Peipei Zhang, Ningning Wang

“…It has been proved that the key technology of speech recognition has been developed rapidly, the speech recognition rate has been improved (up to 97%) and the low-power speech wake up technology had breakthrough, the use of voice interaction is gradually expanding to intelligent hardware and robots, and voice interaction is undoubtedly the mainstream intelligent home pension system interaction mode after keyboard, mouse, and touch screen and also the main entrance of the future intelligent home pension system.…”
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Artificial intelligence in aviation English testing by Gökhan Demirdöken

“…Despite challenges such as speech recognition errors and ethical concerns, these tools offer scalable and accessible solutions for large aviation training programs. …”
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Exploring the Teaching Mode of English Audiovisual Speaking in Multimedia Network Environment by Shunlan Wang

“…Computers have been widely used in language evaluation and speech recognition for language learning, and speech recognition technology is an important reflection of the level of language learning. …”
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ADAPTIVE LEARNING OF HIDDEN MARKOV MODELS FOR EMOTIONAL SPEECH by A. V. Tkachenia

“…A functional block diagram of the hidden Markov models adaptation algorithm is also provided with obtained results, which improve the efficiency of emotional speech recognition.…”
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Echo: A crowd-sourced Romanian speech dataset. by Remus-Dan Ungureanu, Mihai Dascalu

“…In this study, we document how a large speech dataset enables researchers to train automatic speech recognition, speaker verification, and diarization models to automatically process students’ notes. …”
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Key technologies of AI in customer service system by Zheng WANG, Hua REN, Xuhai LU

“…In the customer service system structure,manual seats,work order processing and other links require a lot of manual operations and participation,the cost is high,the efficiency is relatively low,and there will still be a certain percentage of problems and failures that can’t be found and resolved.In the customer service system,the introduction of artificial intelligence technology can solve these problems to a certain extent,reduce costs and improve the overall efficiency and effectiveness of customer service.The key technologies which could be applied to the customer service system in AI were analyzed,including speech recognition,speech synthesis,and natural language processing.The application of new technology in the customer service system of the operator was discussed.The effect in practical application was illustrated by an example.…”
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Recognition of Emotions in Mexican Spanish Speech: An Approach Based on Acoustic Modelling of Emotion-Specific Vowels by Santiago-Omar Caballero-Morales

“…For this, a standard phoneme-based Automatic Speech Recognition (ASR) system was built with Hidden Markov Models (HMMs), where different phoneme HMMs were built for the consonants and emotion-specific vowels associated with four emotional states (anger, happiness, neutral, sadness). …”
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Big Data Deep Learning: Challenges and Perspectives by Xue-Wen Chen, Xiaotong Lin

“…It has gained huge successes in a broad area of applications such as speech recognition, computer vision, and natural language processing. …”
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Continuous speech speaker recognition based on CNN by Zhendong WU, Shucheng PAN, Jianwu ZHANG

“…In the last few years, with the constant improvement of the social life level, the requirement for speech recognition is getting higher and higher. GMM-HMM (Gaussian mixture-hidden Markov model) have been the main method for speaker recognition. …”
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Development and Beta Validation of an mHealth-Based Hearing Screener (SRESHT) for Young Children in Resource-Limited Countries: Pilot Validation Study by Vidya Ramkumar, Deepashree Joshi B, Anil Prabhakar, James W Hall, Ramya Vaidyanath

“…On familiarity check of 18 spondee words for speech recognition task among 20 children, 12 spondee words had the eligibility cutoff (85%) and a presentation level of 5 dB SL (re-pure tone threshold) was sufficient to achieve 80% psychometric function. …”
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RESEARCH ON DEEP NEURAL NETWORK LEARNING BASED ON IMPROVED BP ALGORITHM by HUANG Pei

“…Deep learning can make the computing model that contains a number of processing layers to learn the data that contains many levels of abstract representation.This kind of learning way in the most advanced speech recognition,visual object recognition,object detection and many other areas,such as biology,genetics and medicine brought significant improvement.Deep learning can find the complex structure of large data,and the convolution neural network as one of the important models of the depth study in the processing of voice,image,video and text,and other aspects of a new breakthrough.It is the use of BP algorithm to guide the machine how to get the error before the layer to adjust the parameters of this layer,so that these parameters are more conducive to the calculation of the model.In view of the shortcomings of traditional BP algorithm,a fast BP algorithm is proposed,which has the disadvantages of slow convergence speed and often falls into local minimum points.The improved convolutional neural network is used to validate the data set MNIST,English character recognition and medical image.The simulation results show the effectiveness of the proposed algorithm.…”
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THE REVIEW OF MECHANICAL FAULT DIAGNOSIS METHODS BASED ON CONVOLUTIONAL NEURAL NETWORK by WU DingHai, REN GuoQuan, WANG HuaiGuang, ZHANG YunQiang

“…The Convolutional Neural Network（ CNN） is a classic structure of deep learing and which is being widely and successfully used in the fields of computer vision,target detection,natural language processing,and speech recognition. Based on a detailed analysis of the current status and needs of mechanical system fault diagnosis,this paper introduces the structure of CNN,and summarizes the application of CNN in the field of mechanical faults from the aspects of input data type,network structure design and migration learning. …”
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Multiloop Parallelisation Using Unrolling and Fission by Yuet Ming Lam, José Gabriel F. Coutinho, Chun Hok Ho, Philip Heng Wai Leong, Wayne Luk

“…The approach is demonstrated using three applications: speech recognition, image processing, and the N-Body problem. …”
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