Improved Convolutional Neural Image Recognition Algorithm based on LeNet-5 by Lijie Zhou, Weihai Yu

“…Fruitful results have been achieved in image recognition, speech recognition, and natural language processing. Compared with traditional neural network, convolutional weight sharing, sparse connection, and pooling operations in convolutional neural network greatly reduce the number of training parameters, reduce size of feature map, simplify network model, and improve training efficiency. …”
Get full text

Enhancing balance and auditory function in bilateral vestibulopathy through otolithic vestibular stimulation: insights from a pilot study on cochlea-vestibular implant efficacy by Ángel Ramos-de-Miguel, Ángel Ramos-de-Miguel, Morgana Sluydts, Juan Carlos Falcón, Raquel Manrique-Huarte, Isaura Rodriguez, Andrzej Zarowski, Maurizio Barbara, Manuel Manrique, Silvia Borkoski, Joan Lorente, Marc Leblanc, Antonin Rambault, Erika Van Baelen, Carl Van Himbeeck, Alicia Huarte, Ángel Ramos Macías, Ángel Ramos Macías

“…Auditory function was assessed with pure-tone audiometry (PTA) and speech recognition at baseline, 3, and 9 months post-implantation. …”
Get full text

Cochlear Implantation in Single-Sided Deafness and Asymmetric Hearing Loss: 12 Months Follow-up Results of a European Multicenter Evaluation by Thomas Wesarg, Antje Aschendorff, Regina Baumgaertel, Julia Böttcher, Liesbeth De Coninck, Ingeborg Dhooge, Ann Dierckx, Thomas Klenzner, Philipp Schörg, Georg Sprinzl, Freya Swinnen, Nicolas Verhaert, Annelies Vermeiren, Simone Volpert, Andrzej Zarowski, Arne Ernst

“…Results: In both SSD and AHL subjects, CI significantly improved sound localization for sound sources on the implant side, and thus overall sound localization. Speech recognition in quiet with the implant ear improved significantly. …”
Get full text

A Review of Subsequence Time Series Clustering by Seyedjamal Zolhavarieh, Saeed Aghabozorgi, Ying Wah Teh

“…Subsequence time series clustering is used in different fields, such as e-commerce, outlier detection, speech recognition, biological systems, DNA recognition, and text mining. …”
Get full text

Vocal Communication Between Cobots and Humans to Enhance Productivity and Safety: Review and Discussion by Yuval Cohen, Maurizio Faccio, Shai Rozenes

“…Speech generation and speech recognition are pre-requisites for effective vocal communication. …”
Get full text

Experiments on Detection of Voiced Hesitations in Russian Spontaneous Speech by Vasilisa Verkhodanova, Vladimir Shapranov

“…One of the main focus areas in this field is automatic speech recognition (ASR) that enables the recognition and translation of spoken language into text by computers. …”
Get full text

On the Development of Speech Resources for the Mixtec Language by Santiago-Omar Caballero-Morales

“…This paper presents the development of the following resources for the Mixtec language: (1) a speech database of traditional narratives of the Mixtec culture spoken by a native speaker (labelled at the phonetic and orthographic levels by means of spectral analysis) and (2) a native speaker-adaptive automatic speech recognition (ASR) system (trained with the speech database) integrated with a Mixtec-to-Spanish/Spanish-to-Mixtec text translator. …”
Get full text

The function of ASR-generated live transcription in simultaneous interpreting: trainee interpreters’ perceptions from post-task interviews by Xiaoman Wang, Binhua Wang, Lu Yuan

“…Abstract This study explores whether live transcription generated with the technology of automatic-speech-recognition (ASR) can be used to facilitate simultaneous interpreting. …”
Get full text

After visibility: Data as a factor of production in Douyin e-commerce by Shuaishuai Wang

“…This involves measurements employing surveillance technologies that span image and speech recognition, keywords, performance metrics, and pricing algorithms. …”
Get full text

A Systematic Analysis of Various Word Sense Disambiguation Approaches by Chandra Ganesh, Sanjay K. Dwivedi, Satya Bhushan Verma, Manish Dixit

“…This paper also describes the various applications of WSD, such as information retrieval, machine translation, speech recognition, computational advertising, text processing, classification of documents and biometrics.…”
Get full text

Application of Perceptual Filtering Models to Noisy Speech Signals Enhancement by Novlene Zoghlami, Zied Lachiri

“…Using objective tests based on the perceptual quality PESQ score and the quality rating of signal distortion (SIG), noise distortion (BAK) and overall quality (OVRL), and subjective test based on the quality rating of automatic speech recognition (ASR), we demonstrate that our speech enhancement approach using filter banks modeling the human auditory system outperforms the conventional spectral modification algorithms to improve quality and intelligibility of the enhanced speech signal.…”
Get full text

English Audio Language Retrieval Based on Adaptive Speech-Adjusting Algorithm by Xiaoyan Feng, Yanfang Zhou

“…Experiments on number string and large vocabulary continuous speech recognition show that the algorithm is effective.…”
Get full text

A Classroom Emotion Recognition Model Based on a Convolutional Neural Network Speech Emotion Algorithm by Qinying Yuan

“…This network has a good effect on both object labeling and speech recognition. For the problem of extracting emotion features of whole-sentence speech, we propose an attention mechanism-based emotion recognition algorithm for variable-length speech and design a spatiotemporal attention module for the speech emotion algorithm and a convolutional channel attention module for the CNN network to reduce the contribution of the spatiotemporal data of the speech emotion algorithm and the unimportant parts of the CNN convolutional channel feature data in the subsequent recognition by the attention mechanism. …”
Get full text

Rolling Bearing Fault Diagnosis Based on STFT-Deep Learning and Sound Signals by Hongmei Liu, Lianfeng Li, Jian Ma

“…Stacked sparse autoencoders or other deep architectures have shown excellent performance in speech recognition, face recognition, text classification, image recognition, and other application domains. …”
Get full text

Artificial Intelligence Scribe and Large Language Model Technology in Healthcare Documentation: Advantages, Limitations, and Recommendations by Sarah A. Mess, MD, Alison J. Mackey, PhD, David E. Yarowsky, PhD

“…They use automatic speech recognition on the physician–patient interaction, generating a full medical note for the encounter, together with a draft follow-up e-mail for the patient and, often, recommendations, all within seconds or minutes. …”
Get full text

Cross-Attention Fusion of Visual and Geometric Features for Large-Vocabulary Arabic Lipreading by Samar Daou, Achraf Ben-Hamadou, Ahmed Rekik, Abdelaziz Kallel

“…It is an emerging research topic with many potential applications, such as human–machine interaction and enhancing audio-based speech recognition. Recent deep learning approaches integrate visual features from the mouth region and lip contours. …”
Get full text

A Hardware Accelerator for the Inference of a Convolutional Neural network by Edwin González, Walter D. Villamizar Luna, Carlos Augusto Fajardo Ariza

“… Convolutional Neural Networks (CNNs) are becoming increasingly popular in deep learning applications, e.g. image classification, speech recognition, medicine, to name a few. However, the CNN inference is computationally intensive and demanding a large among of memory resources. …”
Get full text

Digital technology and artificial intelligence issues in scientific works by A. N. Timokhovich, E. G. Samokhodkina, E. V. Samokhodkin, A. A. Elzon

“…The main semantic units, reflecting different aspects of the research field are digitalization; artificial intelligence (additional semantic units: knowledge representation, theorem proving, computer vision, robotics, machine learning, multi-agent systems, artificial intelligence tools); neural networks (additional semantic units: learning with a teacher, learning without a teacher, input data); strong or general artificial intelligence, weak or applied artificial intelligence; Marusya voice assistant, Alisa voice assistant, Siri voice assistant, Bixby voice assistant, Google Assistant; speech recognition, fingerprint recognition, human face identification. …”
Get full text

Survey on intellectual property protection for deep learning model by Xinya WANG, Guang HUA, Hao JIANG, Haijian ZHANG

“…With the rapid development of deep learning technology, deep learning models have been widely used in many fields such as image classification and speech recognition.Training a deep learning model relies on a large amount of data and computing power, thus selling the trained model or providing specific services (DLaaS, e.g.) has become a new business.However, the commercial interests of model trainers and the intellectual property rights of model developers may be violated if the model is maliciously stolen.With deep neural network watermarking becoming a new research topic, multimedia copyright protection techniques were used for deep learning model protection.Numerous methods have been proposed in this field and then a comprehensive survey is needed.the existing deep neural network watermarking methods were elaborated and summarized and the future research directions of this field were discussed.The overall framework of neural network watermarking was presented, whereby the basic concepts such as classification model and model backdoor were introduced.Secondly, the existing methods were divided into two types according to the mechanism of watermark embedding, one is to embed the watermark bits into the carrier of internal information of the network, and the other one uses the established backdoor mapping as the watermark.These two existing deep neural network watermarking methods were analyzed and summarized, and attacks to the watermarks were also introduced and discussed.By analyzing the white-box and black-box conditions in watermarking scenario, it comes to the conclusion that the model is difficult to be effectively protected when it is distributed in the white-box manner, and the neural network watermark defenses in the black-box distribution and black-box verification are both worthy for further research.…”
Get full text

Emei Martial Arts Promotion Model and Properties Based on Neural Network Technology by Cheng Xing, N.E. Zainal Abidin, Yudong Tang

“…In recent years, neural networks have made great progress in various fields, such as speech recognition, computer vision, and natural language understanding. …”
Get full text