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DNN-HMM based Automatic Speech Recognition for HRI Scenarios
(2018)
In this paper, we propose to replace the classical black box integration of automatic speech recognition technology in HRI applications with the incorporation of the HRI environment representation and modeling, and the ...
Automatic speech-to-text transcription in an ecuadorian radio broadcast context
(SPRINGER VERLAG, 2017-09-19)
A key element to enable the analysis and accessing to radio broadcast content is the development of automatic speech-to-text systems. The building of these systems has been possible given the current available of different ...
Automatic speech-to-text transcription in an ecuadorian radio broadcast context
(SPRINGER VERLAG, 2018)
Audio-Visual Automatic Speech Recognition Using PZM, MFCC and Statistical Analysis
Audio-Visual Automatic Speech Recognition (AV-ASR) has become the most promising research area when the audio signal gets corrupted by noise. The main objective of this paper is to select the important and discriminative ...
ASR in classroom today: Automatic visualization of conceptual network in science classrooms
(Springer, 2017)
Automatic Speech Recognition (ASR) field has improved substantially in the last years. We are in a point never saw before, where we can apply such algorithms in non-ideal conditions such as real classrooms. In these scenarios ...
Non-linear Dynamics Characterization from Wavelet Packet Transform for Automatic Recognition of Emotional Speech
(SpringerGrupo de Investigación en Telecomunicaciones Aplicadas (GITA)Basilea, Suiza, 2023)
Robust and fast vowel recognition using optimum-path forest
(2010-11-08)
The applications of Automatic Vowel Recognition (AVR), which is a sub-part of fundamental importance in most of the speech processing systems, vary from automatic interpretation of spoken language to biometrics. State-of-the-art ...
Multi-objective optimisation of wavelet features for phoneme recognition
(Institution of Engineering and Technology, 2016-03)
State-of-the-art speech representations provide acceptable recognition results under optimal conditions, though their performance in adverse conditions still needs to be improved. In this direction, many advances involving ...
Robust Automatic Speech Recognition Employing Phoneme-Dependent Multi-Environment Enhanced Models based Linear Normalization-Edición Única
(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2015)