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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
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Phoneme and sentence-level ensembles for speech recognition [PDF]
, 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 ...
Dimitrakakis, Christos +5 more
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Attention-Based End-To-End Named Entity Recognition From Speech
, 2021 | openaire: EC/H2020/780069/EU//MeMADNamed entities are heavily used in the field of spoken language understanding, which uses speech as an input. The standard way of doing named entity recognition from speech involves a pipeline of two systems, where ...
Mikko Kurimo +5 more
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Gazi Üniversitesi Fen Bilimleri Dergisi, 2019 Speech is a paramount means of communication among humans, which makes recognition of the speech by computers is a study area of significance. In this research area, many studies have been carried out based on different languages.
Saadin OYUCU +2 more
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Trends in Hearing, 2020 Several studies have demonstrated that extended high frequencies (EHFs; >8 kHz) in speech are not only audible but also have some utility for speech recognition, including for speech-in-speech recognition when maskers are facing away from the listener ...
Allison Trine, Brian B. Monson
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Research Status and Prospect of Transformer in Speech Recognition
Jisuanji kexue yu tansuo, 2021 As a new deep learning algorithm framework, Transformer has attracted more and more researchers?? attention and has become a current research hotspot. Inspired by humans focusing on important things only, the self-attention mechanism in the Transformer ...
ZHANG Xiaoxu, MA Zhiqiang, LIU Zhiqiang, ZHU Fangyuan, WANG Chunyu
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Learning speech rate in speech recognition [PDF]
Interspeech 2015, 2015 A significant performance reduction is often observed in speech recognition when the rate of speech (ROS) is too low or too high. Most of present approaches to addressing the ROS variation focus on the change of speech signals in dynamic properties caused by ROS, and accordingly modify the dynamic model, e.g., the transition probabilities of the hidden
Xiangyu Zeng, Shi Yin, Dong Wang 0013
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SVMs for Automatic Speech Recognition: a Survey [PDF]
, 2007 Hidden Markov Models (HMMs) are, undoubtedly, the most employed core technique for Automatic Speech Recognition (ASR). Nevertheless, we are still far from achieving high-performance ASR systems.
Peláez-Moreno, Carmen +8 more
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A Formant Modification Method for Improved ASR of Children’s Speech
, 2022 Differences in acoustic characteristics between children’s and adults’ speech degrade performance of automatic speech recognition systems when systems trained using adults’ speech are used to recognize children’s speech.
Alku, Paavo +3 more
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EURASIP Journal on Audio, Speech, and Music Processing, 2021 The performance of speech recognition systems trained with neutral utterances degrades significantly when these systems are tested with emotional speech. Since everybody can speak emotionally in the real-world environment, it is necessary to take account
Masoud Geravanchizadeh +2 more
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