Results 11 to 20 of about 1,501,555 (284)
Improving Phoneme Sequence Recognition using Phoneme Duration Information in DNN-HSMM [PDF]
Journal of Artificial Intelligence and Data Mining, 2019 Improving phoneme recognition has attracted the attention of many researchers due to its applications in various fields of speech processing. Recent research achievements show that using deep neural network (DNN) in speech recognition systems ...
M. Asadolahzade Kermanshahi +1 more
doaj +3 more sources
Phoneme recognition using acoustic events [PDF]
3rd International Conference on Spoken Language Processing (ICSLP 1994), 1994 This paper presents a new approach to phoneme recognition using nonsequential sub--phoneme units. These units are called acoustic events and are phonologically meaningful as well as recognizable from speech signals. Acoustic events form a phonologically incomplete representation as compared to distinctive features.
Hübener, Kai, Carson-Berndsen, Julie
core +6 more sources
German Phoneme Recognition with Text-to-Phoneme Data Augmentation [PDF]
CoRR, 2022 In this study, we experimented to examine the effect of adding the most frequent n phoneme bigrams to the basic vocabulary on the German phoneme recognition model using the text-to-phoneme data augmentation strategy. As a result, compared to the baseline model, the vowel30 model and the const20 model showed an increased BLEU score of more than 1 point,
Dojun Park, Seohyun Park
core +5 more sources
Reverberant speech recognition: A phoneme analysis [PDF]
2014 IEEE Global Conference on Signal and Information Processing (GlobalSIP), 2014 We present a phoneme confusion analysis that models the impact of reverberation on automatic speech recognition performance by formulating the problem in a Bayesian framework. Our analysis under reverberant conditions shows the relative robustness to reverberation of each phoneme and also indicates that substitutions and deletions correspond to the ...
Peso Parada, P. +3 more
openaire +3 more sources
Phoneme and Sentence-Level Ensembles for Speech Recognition [PDF]
EURASIP Journal on Audio, Speech, and Music Processing, 2011 We address the question of whether and how boosting and bagging can be used for speech recognition. In order to do this, we compare two different boosting schemes, one at the phoneme level and one at the utterance level, with a phoneme-level bagging ...
Samy Bengio, Christos Dimitrakakis
doaj +3 more sources
A digital neural network approach to speech recognition [PDF]
, 1989 This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.This thesis presents two novel methods for isolated word speech recognition based on sub-word components.
Haider, Najmi Ghani
core +7 more sources
Shared genetics between ADHD and reading/language abilities: Genome-wide correlations, stratified enrichment, cross-trait association, and mendelian randomization. [PDF]
JCPP AdvAbstract Background Attention‐deficit/hyperactivity disorder (ADHD) and language/reading difficulties frequently co‐occur. The extent of shared genetic architecture remains incompletely defined. We investigated genome‐wide overlap between ADHD and four core skills: word reading, nonword reading, spelling, and phoneme awareness.
Zhao J +5 more
europepmc +2 more sources
PHONEME RECOGNITION AND CONFUSIONS IN PATIENTS WITH SENSORINEURAL HEARING LOSS [PDF]
Human Research in Rehabilitation, 2023 Hearing impaired listeners show different phoneme confusions during speech recognition testing. The aim of the study was to analyze phoneme recognition in patients with sensorineural hearing loss during word recognition testing with monosyllabic words,
Zora Jachova +3 more
doaj +1 more source
Frontiers in Psychology, 2022 Previous studies suggest a relationship between second-language learning and voice recognition processes, but the nature of such relation remains poorly understood. The present study investigates whether phoneme learning relates to voice recognition.
Begoña Díaz +3 more
doaj +1 more source
Information, 2021 Out-of-vocabulary (OOV) words are the most challenging problem in automatic speech recognition (ASR), especially for morphologically rich languages.
Eshete Derb Emiru +4 more
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