Results 11 to 20 of about 243 (116)
Use of Automation Technologies and Data Mining in Speech Recognition for Autism. [PDF]
Pipeline analyzes clinical and naturalistic speech using LENA, wav2vec 2.0, and foundation‐model ASR (Whisper) to enable scalable ASD detection and severity estimation. Future work integrates benchmarking, privacy‐preserving collaboration (federated learning), and explainable, edge‐ready AI for clinically credible assessment and longitudinal monitoring.
Mao R, Zhu Y.
europepmc +2 more sources
AI‐Powered Speech Analysis: Automating Transcription, Embeddings, and Deep Learning for Early Alzheimer's Detection [PDF]
Abstract Background Spontaneous speech is a promising, non‐invasive, cost‐effective biomarker. LLM vector embeddings capture semantic and contextual patterns. This study transcribed audio, generated embeddings, and trained machine learning models to classify AD patients versus healthy controls.
Zhou D, Qian Z.
europepmc +2 more sources
TELL 2.0: Interpretable speech biomarkers for dementia in research and clinical applications
Abstract Background Launched in early 2023, the Toolkit to Examine Lifelike Language (TELL) is a web app designed to gather voice samples and extract speech biomarkers for dementia. Its initial version enhanced clinical evaluations across diverse regions, including under‐resourced countries.
Franco Javier Ferrante +14 more
wiley +3 more sources
HPB SmartNotes: The impact of artificial intelligence on surgeon workload in the outpatient office
In this study, we aimed to evaluate the feasibility, linguistic accuracy, and coherence of medical notes generated by the integration of an automatic speech recognition system (ASR) and a generative pre-trained transformer (GPT) in an outpatient surgical
Rodrigo Antonio Gasque +6 more
doaj +1 more source
Speech Recognition and Synthesis Models and Platforms for the Kazakh Language
With the rapid development of artificial intelligence and machine learning technologies, automatic speech recognition (ASR) and text-to-speech (TTS) have become key components of the digital transformation of society.
Aidana Karibayeva +3 more
doaj +1 more source
Estimación de incertidumbre para un sistema de reconocimiento de voz
Whisper es un sistema de reconocimiento de voz diseñado por la compañía OpenAI, dicho sistema ha sido entrenado con 680,000 horas de datos supervisados multilingües y multitarea recopilados de la web.
Walter Morales-Muñoz +1 more
doaj +1 more source
ABSTRACT Aim Children born to mothers with chronic Hepatitis B virus (HBV) infection are at substantial risk of developing chronic HBV‐infection without appropriate perinatal post‐exposure treatment. This study aimed to explore midwives' and public health nurses' (PHNs) experiences with HBV‐post‐exposure treatment for infants and identify factors ...
Brita Askeland Winje +4 more
wiley +1 more source
ABSTRACT The location of public services impacts children's living and service‐reception conditions, as well as the work of child welfare service providers. Against the background of growing inequality and segregation in Sweden, this article explores the work of child welfare services when located in the urban periphery.
Tobias Jansson, Kajsa Nolbeck
wiley +1 more source
ABSTRACT This article investigates how TikTok Shop reproduces the e‐commerce model of Douyin Shop against a backdrop of divergent regulatory challenges and geopolitical distrust. One of the strategic changes we observe in TikTok Shop is the shift of consumer goods suppliers from local merchants to China‐based sellers.
Shuaishuai Wang, Jing Meng, Yitong Li
wiley +1 more source
Chef Dalle: Transforming Cooking with Multi-Model Multimodal AI
In an era where dietary habits significantly impact health, technological interventions can offer personalized and accessible food choices. This paper introduces Chef Dalle, a recipe recommendation system that leverages multi-model and multimodal human ...
Brendan Hannon +3 more
doaj +1 more source

