Search Results for author:
Found 11 papers, 4 papers with code
Image Captioning with Integrated Bottom-Up and Multi-level Residual Top-Down Attention for Game Scene Understanding
However, little work has been done for game image captioning which has some unique characteristics and requirements.
Speaker Change Detection Using Features through A Neural Network Speaker Classifier
The mechanism proposed here is for real-time speaker change detection in conversations, which firstly trains a neural network text-independent speaker classifier using in-domain speaker data.
Sound
Neural Network Based Speaker Classification and Verification Systems with Enhanced Features
This work presents a novel framework based on feed-forward neural network for text-independent speaker classification and verification, two related systems of speaker recognition.
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Generation and Pruning of Pronunciation Variants to Improve ASR Accuracy
Speech recognition, especially name recognition, is widely used in phone services such as company directory dialers, stock quote providers or location finders.
PCA Method for Automated Detection of Mispronounced Words
This paper presents a method for detecting mispronunciations with the aim of improving Computer Assisted Language Learning (CALL) tools used by foreign language learners.
Adaptive Frequency Cepstral Coefficients for Word Mispronunciation Detection
New adaptive features have been developed and obtained through an adaptive warping of the frequency scale prior to computing the cepstral coefficients.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
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PCA/LDA Approach for Text-Independent Speaker Recognition
Various algorithms for text-independent speaker recognition have been developed through the decades, aiming to improve both accuracy and efficiency.
Accent Classification with Phonetic Vowel Representation
Previous accent classification research focused mainly on detecting accents with pure acoustic information without recognizing accented speech.
Domain Specific Author Attribution Based on Feedforward Neural Network Language Models
In this paper, we present a novel setup of a Neural Network Language Model (NNLM) and apply it to a database of text samples from different authors.
Improved Accent Classification Combining Phonetic Vowels with Acoustic Features
Researches have shown accent classification can be improved by integrating semantic information into pure acoustic approach.
Authorship Attribution Using a Neural Network Language Model
In practice, training language models for individual authors is often expensive because of limited data resources.
