Voice Commands
Voice Commands - Related Videos
04:04
Asthma Detection Research Based on Voice Signal Processing and Machine Learning
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2025
This study employed voice signal analysis and machine learning methods, utilizing MATLAB to extract distinctive voice features for non-invasive early detection of asthma. The Support Vector Machine (SVM) and Random Forest (RF) algorithms demonstrated comparable performance in terms of overall classification accuracy, although SVM may achieve a better balance between sensitivity and specificity.
09:09
Foreign Accent and Forensic Speaker Identification in Voice Lineups: The Influence of Acoustic Features Based on Prosody
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2024
This research aimed to make a comparison between L1-L2-English and L1-L2 Portuguese to check how much the effect of a foreign accent accounts for both metrics and prosodic-acoustic parameters, as well as for the choice of the target voice in a voice lineup.
04:40
Augmented Reality-Based Visualization of a Resected Tumor Specimen
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2026
Source:Carly Fassler1, Liyu Huang1, Kavita Prasad1, Jiayi Xu2, Guansen Tong2, Jie Ying Wu2, Michael C. Topf1,31Department of Otolaryngology – Head and Neck Surgery, Vanderbilt University Medical Center.2Computer Science Department, Vanderbilt University.3Vanderbilt University School of Engineering, Vanderbilt University.This video demonstrates using augmented reality (AR) for tumor resection, where a 3D-scanned tumor specimen is visualized as a hologram on a head-mounted display. Surgeons can...
10:13
Hemi-laryngeal Setup for Studying Vocal Fold Vibration in Three Dimensions
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Cited by 12 •
2017
This paper introduces a protocol for the preparation of hemi-larynx specimens facilitating a multi-dimensional view of vocal fold vibration, in order to investigate various biophysical aspects of voice production in humans and non-human mammals.
09:38
Quantitative Assessment of Cortical Auditory-tactile Processing in Children with Disabilities
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Cited by 8 •
2014
Objective and easy measurement of sensory processing is extremely difficult in nonverbal or vulnerable pediatric patients. We developed a new methodology to quantitatively assess infants and children's cortical processing of light touch, speech sounds, and the multisensory processing of the 2 stimuli, without requiring active subject participation or causing discomfort in vulnerable patients.
FAQs
Specialized biomedical and cancer-related terms may challenge speech recognition when the system does not interpret them accurately. This makes terminology an important factor in determining whether a spoken instruction becomes the intended text and action. Researchers should therefore include validation when using voice-controlled workflows, particularly for database searches, protocol navigation, or records containing sensitive experimental information.
Each stage contributes a different function: the microphone captures the speech, automatic speech recognition produces text, and natural language processing identifies the intended command. A problem in interpretation can affect the requested operation or response. Understanding this sequence helps researchers identify where accuracy and validation matter when voice commands interact with cancer research software, records, or connected devices.
Voice-based interaction can reduce the need to operate software through physical controls, which may help researchers access digital systems while handling samples or instruments. It can also support accessibility by offering an alternative way to interact with technology. These benefits depend on reliable recognition and appropriate handling of biomedical information, so convenience does not remove the need for validation or privacy safeguards.
Predefined operations connect an interpreted instruction to a specific response or task, such as entering data, searching a database, navigating a protocol, or opening an imaging or experimental record. This structure gives the system a bounded action to perform rather than requiring unrestricted interpretation. In cancer research, clearly defined operations can make the intended workflow easier to control and evaluate.
A typical workflow begins when the researcher speaks an instruction into a microphone. The system converts the audio into text, determines the intended command, and initiates the associated operation or response. The researcher can apply this sequence to data entry, searches, protocol navigation, or record access while working with samples or instruments, with validation remaining important for accurate use.
The core setup includes a microphone, software capable of speech recognition and language interpretation, and a digital system or connected device that can perform predefined operations. Depending on the workflow, the accessible resources may include databases, protocols, imaging records, or experimental records. Their usefulness depends on how accurately the system handles the spoken terminology and requested task.
They are useful when researchers need to enter information, search databases, navigate protocols, or access imaging and experimental records while handling samples or instruments. The approach can improve workflow efficiency by reducing interruptions to those activities. Because these records may contain sensitive biomedical data, researchers must also consider privacy, terminology accuracy, and validation when applying the interface.