Learning Models for English Speech Recognition

Recognizing the Emotional State Changes in Human Utterance by a Learning Statistical Method based on Gaussian Mixture Model

Speech is one of the most opulent and instant methods to express emotional characteristics of human beings, which conveys the cognitive and semantic concepts among humans. In this study, a statistical-based method for emotional recognition of speech signals is proposed, and a learning approach is introduced, which is based on the statistical model to classify internal feelings of the utterance....

A Comparative Study of Gender and Age Classification in Speech Signals

Accurate gender classification is useful in speech and speaker recognition as well as speech emotion classification, because a better performance has been reported when separate acoustic models are employed for males and females. Gender classification is also apparent in face recognition, video summarization, human-robot interaction, etc. Although gender classification is rather mature in a...

Structured-based Curriculum Learning for End-to-end English-Japanese Speech Translation

Sequence-to-sequence attentional-based neural network architectures have been shown to provide a powerful model for machine translation and speech recognition. Recently, several works have attempted to extend the models for end-to-end speech translation task. However, the usefulness of these models were only investigated on language pairs with similar syntax and word order (e.g., English-French...

Speaker Independent Speech Recognition Using Hidden Markov Models for Persian Isolated Words

Speaker Independent Speech Recognition Using Hidden Markov Models for Persian Isolated Words

Using deep neural networks to improve proficiency assessment for children English language learners

We investigated the use of context-dependent deep neural network hidden Markov models, or CD-DNN-HMMs, to improve speech recognition performance for a better assessment of children English language learners (ELLs). The ELL data used in the present study was obtained from a large language assessment project administered in schools in a U.S. state. Our DNN-based speech recognition system, built u...