Multimodal interaction

Multimodal interaction provides the user with multiple <a href="/facts/Modality_(human%E2%80%93computer_interaction)/KzL4uqMm">modes of interacting</a> with a system. A multimodal interface provides several distinct tools for <a href="/facts/Input_and_output/WQTE8Jas">input and output</a> of data.
Multimodal <a href="/facts/Human-computer_interaction/EkmIxGCx">human-computer interaction</a> involves natural communication with virtual and physical environments. It facilitates free and natural communication between users and automated systems, allowing flexible input (speech, handwriting, gestures) and output (<a href="/facts/Speech_synthesis/ceTczTv9">speech synthesis</a>, graphics). Multimodal fusion combines inputs from different modalities, addressing ambiguities.
Two major groups of multimodal interfaces focus on alternate input methods and combined input/output. Multiple input modalities enhance usability, benefiting users with impairments. Mobile devices often employ <a href="/facts/XHTML%2BVoice/2XXtyXzI">XHTML+Voice</a> for input. <a href="/facts/Multimodal_biometric_system/MgTbyA0r">Multimodal biometric systems</a> use multiple biometrics to overcome limitations. <a href="/facts/Multimodal_sentiment_analysis/ejwvmVSr">Multimodal sentiment analysis</a> involves analyzing text, audio, and visual data for sentiment classification. <a href="/facts/GPT-4/MuXdd4sW">GPT-4</a>, a multimodal <a href="/facts/Language_model/FntSpg0j">language model</a>, integrates various modalities for improved language understanding. Multimodal output systems present information through visual and auditory cues, using touch and olfaction. Multimodal fusion integrates information from different modalities, employing recognition-based, decision-based, and hybrid multi-level fusion.
Ambiguities in multimodal input are addressed through prevention, a-posterior resolution, and approximation resolution methods.

Multimodal interaction open-in-new

Multimodal interaction