AIMC Topic: Voice

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Transformer-based transfer learning on self-reported voice recordings for Parkinson's disease diagnosis.

Scientific reports
Deep learning (DL) techniques are becoming more popular for diagnosing Parkinson's disease (PD) because they offer non-invasive and easily accessible tools. By using advanced data analysis, these methods improve early detection and diagnosis, which i...

How to identify patient perception of AI voice robots in the follow-up scenario? A multimodal identity perception method based on deep learning.

Journal of biomedical informatics
OBJECTIVES: Post-discharge follow-up stands as a critical component of post-diagnosis management, and the constraints of healthcare resources impede comprehensive manual follow-up. However, patients are less cooperative with AI follow-up calls or may...

How do older adults react to social robots' offspring-like voices.

Social science & medicine (1982)
Social robots are being developed as a technological solution to alleviate older adults' loneliness due to separation from their offspring. This study explores how and why offspring-like voices affect older adults' acceptance of social robots from an...

HiddenSinger: High-quality singing voice synthesis via neural audio codec and latent diffusion models.

Neural networks : the official journal of the International Neural Network Society
Recently, denoising diffusion models have demonstrated remarkable performance among generative models in various domains. However, in the speech domain, there are limitations in complexity and controllability to apply diffusion models for time-varyin...

A Nanoparticle-Based Artificial Ear for Personalized Classification of Emotions in the Human Voice Using Deep Learning.

ACS applied materials & interfaces
Artificial intelligence and human-computer interaction advances demand bioinspired sensing modalities capable of comprehending human affective states and speech. However, endowing skin-like interfaces with such intricate perception abilities remains ...

A dual-region speech enhancement method based on voiceprint segmentation.

Neural networks : the official journal of the International Neural Network Society
Single-channel speech enhancement primarily relies on deep learning models to recover clean speech signals from noise-contaminated speech. These models establish a mapping relationship between noisy and clean speech. However, considering the sparse d...

COPDVD: Automated classification of chronic obstructive pulmonary disease on a new collected and evaluated voice dataset.

Artificial intelligence in medicine
BACKGROUND: Chronic obstructive pulmonary disease (COPD) is a severe condition affecting millions worldwide, leading to numerous annual deaths. The absence of significant symptoms in its early stages promotes high underdiagnosis rates for the affecte...

Co-designing the integration of voice-based conversational AI and web augmentation to amplify web inclusivity.

Scientific reports
The Web has become an essential resource but is not yet accessible to everyone. Assistive technologies and innovative, intelligent frameworks, for example, those using conversational AI, help overcome some exclusions. However, some users still experi...

Detection of Parkinson disease using multiclass machine learning approach.

Scientific reports
Parkinson's Disease (PD) is a prevalent neurological condition characterized by motor and cognitive impairments, typically manifesting around the age of 50 and presenting symptoms such as gait difficulties and speech impairments. Although a cure rema...

AI Detection of Glottic Neoplasm Using Voice Signals, Demographics, and Structured Medical Records.

The Laryngoscope
OBJECTIVE: This study investigated whether artificial intelligence (AI) models combining voice signals, demographics, and structured medical records can detect glottic neoplasm from benign voice disorders.