Using Vision and Speech Features for Automated Prediction of Performance Metrics in Multimodal Dialogs

ETS Research Report Series - United States
doi 10.1002/ets2.12146
Full Text
Abstract

Available in full text

Date
Authors
Publisher

Wiley

Related search

Automatic Identification of Experts and Performance Prediction in the Multimodal Math Data Corpus Through Analysis of Speech Interaction

2013English

Performance Metrics for the Prediction of Link and Path Availability in VANETs

2009English

Novel Nonlinear Prediction Based Features for Spoofed Speech Detection

2016English

Enhancing the Performance of Multimodal Automated Border Control Systems

2016English

Image-Based Prediction of Imaging and Vision Performance

Journal of the Optical Society of America A: Optics and Image Science, and Vision
Pattern RecognitionOpticsMolecular Physics,Computer VisionOpticalAtomicMagnetic MaterialsMedicineElectronic
2007English

Neural Embedding-Based Metrics for Pre-Retrieval Query Performance Prediction

Lecture Notes in Computer Science
Computer ScienceTheoretical Computer Science
2020English

An Investigation of Features for Fundamental Frequency Pattern Prediction in Electrolaryngeal Speech Enhancement

2019English

DWT Features Performance Analysis for Automatic Speech Recognition of Urdu

SpringerPlus
Multidisciplinary
2014English

Audio Segmentation for Speech Recognition Using Segment Features

Advances in Intelligent Systems and Computing
ControlSystems EngineeringComputer Science
2014English

Amanote Research

Note-taking for researchers

Follow Amanote

© 2024 Amaplex Software S.P.R.L. All rights reserved.

Privacy PolicyRefund Policy