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

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

Audio classification using grasshopper‐ride optimization algorithm‐based support vector machine by Suryabhan Pratap Singh, Umesh Chandra Jaiswal

“…Abstract The accurate and robust detection of the audio has been widely grown as the speech technology in the area of audio forensics, speech recognition, and so on. However, in real time, it is a challenge to deal with the massive data arriving from distributed sources. …”
Get full text

Hearing in categories and speech perception at the "cocktail party". by Gavin M Bidelman, Fallon Bernard, Kimberly Skubic

“…We first show cocktail party speech recognition accuracy and speed decline with additional competing talkers and amidst forward compared to reverse maskers. …”
Get full text

An intrusion detection model based on Convolutional Kolmogorov-Arnold Networks by Zhen Wang, Anazida Zainal, Maheyzah Md Siraj, Fuad A. Ghaleb, Xue Hao, Shaoyong Han

“…Abstract The application of artificial neural networks (ANNs) can be found in numerous fields, including image and speech recognition, natural language processing, and autonomous vehicles. …”
Get full text

Logatome Discrimination in Cochlear Implant Users: Subjective Tests Compared to the Mismatch Negativity by Torsten Rahne, Michael Ziese, Dorothea Rostalski, Roland Mühler

“…This paper describes a logatome discrimination test for the assessment of speech perception in cochlear implant users (CI users), based on a multilingual speech database, the Oldenburg Logatome Corpus, which was originally recorded for the comparison of human and automated speech recognition. The logatome discrimination task is based on the presentation of 100 logatome pairs (i.e., nonsense syllables) with balanced representations of alternating “vowel-replacement” and “consonant-replacement” paradigms in order to assess phoneme confusions. …”
Get full text

Construction and Analysis of Emotion Computing Model Based on LSTM by Huiping Jiang, Rui Jiao, Zequn Wang, Ting Zhang, Licheng Wu

“…Long short-term memory (LSTM) processes the temporal characteristics of data and is mostly used for emotional text and speech recognition. Since an EEG involves a time series signal, this article mainly studied the introduction of LSTM for emotional EEG recognition. …”
Get full text

Philosophical Review of Artificial Intelligence for Society 5.0 by Ggaliwango, Marvin, Tamale, Micheal, Kanagwa, Benjamin, Jjingo, Daudi

“…Today, AI has reached new heights and has a wide range of applications, from playing complex games to language processing, speech recognition, and facial recog nition [1–3]. With its exponential growth and its increasing presence in an ever growing number of sectors, AI is well on its way to becoming a source of significant economic prosperity. …”
Get full text

Tibetan–Chinese speech-to-speech translation based on discrete units by Zairan Gong, Xiaona Xu, Yue Zhao

“…Abstract Speech-to-speech translation (S2ST) has evolved from cascade systems which integrate Automatic Speech Recognition (ASR), Machine Translation (MT), and Text-to-Speech (TTS), to end-to-end models. …”
Get full text

IDAS: Intelligent Driving Assistance System Using RAG by Hernandez-Salinas Bernardo, Juan Terven, E. A. Chavez-Urbiola, Diana-Margarita Cordova-Esparza, Julio-Alejandro Romero-Gonzalez, Amadeo Arguelles, Ilse Cervantes

“…In addition, this system incorporates speech recognition and speech synthesis capabilities, it can understand commands given in multiple languages, improving user experiences among diverse driver communities. …”
Get full text

User Experiences from L2 Children Using a Speech Learning Application: Implications for Developing Speech Training Applications for Children by Maria Uther, Anna-Riikka Smolander, Katja Junttila, Mikko Kurimo, Reima Karhila, Seppo Enarvi, Sari Ylinen

“…We investigated user experiences from 117 Finnish children aged between 8 and 12 years in a trial of an English language learning programme that used automatic speech recognition (ASR). We used measures that encompassed both affective reactions and questions tapping into the children' sense of pedagogical utility. …”
Get full text

Application of an active middle ear implant in congenital middle ear malformations: A contemporary review by Vagner Antonio Rodrigues da Silva, Henrique Furlan Pauna, Guilherme Correa Guimarães, Joel Lavinsky, Thomas E. Linder, Arthur Menino Castilho

“…VSB implantation resulted in mean hearing gain of 40.5 ± 7.1 dB in the air-conduction thresholds among the evaluated frequencies. The speech recognition index if the Floating Mass Transducer (FMT) was placed in the short process was 86.0% ± 9.6%, with significant difference when compared to long process coupling (p = 0.035) and the round window coupling (p =  0.048). …”
Get full text

Efficient nonlinear function approximation in analog resistive crossbars for recurrent neural networks by Junyi Yang, Ruibin Mao, Mingrui Jiang, Yichuan Cheng, Pao-Sheng Vincent Sun, Shuai Dong, Giacomo Pedretti, Xia Sheng, Jim Ignowski, Haoliang Li, Can Li, Arindam Basu

“…However, recurrent neural networks (RNN) that are widely used for speech-recognition and natural language processing have tasted limited success with this approach. …”
Get full text

Nerve‐Inspired Optical Waveguide Stretchable Sensor Fusing Wireless Transmission and AI Enabling Smart Tele‐Healthcare by Tianliang Li, Qian'ao Wang, Zichun Cao, Jianglin Zhu, Nian Wang, Run Li, Wei Meng, Quan Liu, Shifan Yu, Xinqin Liao, Aiguo Song, Yuegang Tan, Zude Zhou

“…A small circuit board is prepared to enable wireless signal transmission of the designed sensor, thereby improving the daily portability. A speech recognition and human‐machine interaction system, based on sensor signal acquisition, is constructed, and the convolutional neural network algorithm is integrated for disease assessment. …”
Get full text

Penentuan Filterbank Wavelet Menggunakan Algoritma Mean Best Basis untuk Ekstraksi Ciri Sinyal Suara Ber-Noise by Abdurahim Abdurahim, Syahroni Hidayat

“…Abstract Recently wavelet-based filterbanks as feature start extractors have been widely developed to replace the role of the Mel Frequency Cepstral Coefficient (MFCC) feature in automatic speech recognition systems. One of the wavelet feature filterbanks developed is Wavelet-Packet Cepstral Coefficient (WPCC). …”
Get full text