A Speech Recognition Method Using Competitive and Selective Learning Neural Networks by Hu Guangrui Xu Xiong Yan Yonghong

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Harnessing the Multi-Phasal Nature of Speech-EEG for Enhancing Imagined Speech Recognition by Rini Sharon, Mriganka Sur, Hema Murthy

“…The findings indicate that the proposed multi-phase approach significantly enhances EEG-based speech recognition, achieving an accuracy gain of 18.2% for 25 cognitive units in continuous speech EEG over models reliant solely on single-phase data.…”
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Chinese semantic and phonological information-based text proofreading model for speech recognition by Meiyu ZHONG, Peiliang WU, Yan DOU, Yi LIU, Lingfu KONG

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Sparse group LASSO constraint eigenphone speaker adaptation method for speech recognition by Dan QU, Wen-lin ZHANG

“…Original eigenphone speaker adaptation method performed well when the amount of adaptation data was suffi-cient.However,it suffered from server overfitting when insufficient amount of adaptation data was provided.A sparse group LASSO(SGL) constraint eigenphone speaker adaptation method was proposed.Firstly,the principle of eigenphone speaker adaptation was introduced in case of hidden Markov model-Gaussian mixture model (HMM-GMM) based speech recognition system.Then,a sparse group LASSO was applied to estimation of the eigenphone matrix.The weight of the SGL norm was adjusted to control the complexity of the adaptation model.Finally,an accelerated proximal gradient method was adopted to solve the mathematic optimization.The method was compared with up-to-date norm algorithms.Experiments on an mandarin Chinese continuous speech recognition task show that,the performance of the SGL con-straint eigenphone method can improve remarkably the performance of the system than original eigenphone method,and is also superior to l₁、l₂-norm and elastic net constraint methods.…”
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Retracted: Emotional Interactive Simulation System of English Speech Recognition in Virtual Context by null Complexity

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End-to-end audiovisual speech recognition based on attention fusion of SDBN and BLSTM by Yiming WANG, Ken CHEN, Aihaiti ABUDUSALAMU

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Accents in Speech Recognition through the Lens of a World Englishes Evaluation Set by Miguel Del Río, Corey Miller, Ján Profant, Jennifer Drexler-Fox, Quinn Mcnamara, Nishchal Bhandari, Natalie Delworth, Ilya Pirkin, Migüel Jetté, Shipra Chandra, Peter Ha, Ryan Westerman

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Optimization Simulation of English Speech RecognitionAccuracy Based on Improved Ant Colony Algorithm by Lu Jing

“…This paper is aimed at the problems of low accuracy, long recognition time, and low recognition efficiency in English speech recognition. In order to improve the accuracy and efficiency of English speech recognition, an improved ant colony algorithm is used to deal with the dynamic time planning problem. …”
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Deep Neural Learning Adaptive Sequential Monte Carlo for Automatic Image and Speech Recognition by Patcharin Kamsing, Peerapong Torteeka, Wuttichai Boonpook, Chunxiang Cao

“…To enhance the performance of image classification and speech recognition, the optimizer is considered an important factor for achieving high accuracy. …”
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User Satisfaction for an Augmented Reality Application to Support Productive Vocabulary Using Speech Recognition by Nurhazarifah Che Hashim, Nazatul Aini Abd Majid, Haslina Arshad, Waqas Khalid Obeidy

“…The aim of this paper is to evaluate user satisfaction based on System Usability Scale (SUS) questionnaire on Augmented Reality (AR) application for productive vocabulary using speech recognition. There is still lack of research focus on user satisfaction towards the use of AR-based app using speech recognition for vocabulary learning in early education. …”
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Transforming English language learning: Advanced speech recognition with MLP-LSTM for personalized education by Myagmarsuren Orosoo, Namjildagva Raash, Mark Treve, Hassan Fareed M. Lahza, Nizal Alshammry, Janjhyam Venkata Naga Ramesh, Manikandan Rengarajan

Subjects: “…Speech recognition…”
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Deep Learning Methods for Arabic Autoencoder Speech Recognition System for Electro-Larynx Device by Zinah J. Mohammed Ameen, Abdulkareem Abdulrahman Kadhim

“…Recent advances in speech recognition have achieved remarkable performance comparable with human transcribers’ abilities. …”
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Usefulness of Automatic Speech Recognition Assessment of Children With Speech Sound Disorders: Validation Study by Do Hyung Kim, Joo Won Jeong, Dayoung Kang, Taekyung Ahn, Yeonjung Hong, Younggon Im, Jaewon Kim, Min Jung Kim, Dae-Hyun Jang

“…ObjectiveThis study aimed to compare the evaluation outcomes of SLPs and an automatic speech recognition (ASR) model using two standardized SSD assessments in South Korea, evaluating the ASR model’s performance. …”
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New Features Using Robust MVDR Spectrum of Filtered Autocorrelation Sequence for Robust Speech Recognition by Sanaz Seyedin, Seyed Mohammad Ahadi, Saeed Gazor

“…This paper presents a novel noise-robust feature extraction method for speech recognition using the robust perceptual minimum variance distortionless response (MVDR) spectrum of temporally filtered autocorrelation sequence. …”
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Retracted: Optimization Simulation of English Speech Recognition Accuracy Based on Improved Ant Colony Algorithm by null Complexity

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Age dependent deficits in speech recognition in quiet and noise are reflected in MGB activity and cochlear onset coding by Konrad Dapper, Stephan M. Wolpert, Jakob Schirmer, Stefan Fink, Etienne Gaudrain, Deniz Başkent, Wibke Singer, Sarah Verhulst, Christoph Braun, Ernst Dalhoff, Lukas Rüttiger, Matthias H.J. Munk, Marlies Knipper

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Retracted: A Russian Continuous Speech Recognition System Based on the DTW Algorithm under Artificial Intelligence by Journal of Robotics

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AFT-SAM: Adaptive Fusion Transformer with a Sparse Attention Mechanism for Audio–Visual Speech Recognition by Na Che, Yiming Zhu, Haiyan Wang, Xianwei Zeng, Qinsheng Du

Subjects: “…speech recognition…”
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Building Arabic Speech Recognition System Using HuBERT Model and Studying the Sources of Errors [Arabic] by Rima Sbih, Assef Jafar, Ali Kazem

Subjects: “…speech recognition…”
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Sistem Kontrol Perangkat Inframerah Menggunakan Speech Recognition dengan Spectrogram dan Convolutional Neural Network Berbasis Mikrokontroler by Irfan Muzakky Nurrizqy, Barlian Henryranu Prasetio, Rekyan Regasari Mardi Putri

“…The system can also run the speech recognition process with an average time of 0.105 seconds. …”
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