Zobrazeno 1 - 10
of 400
pro vyhledávání: '"Triphone"'
Autor:
L. Joyprakash Singh, Bronson Syiem
Publikováno v:
International Journal of Speech Technology. 24:419-424
Building a conventional automatic speech recognition (ASR) system based on hidden Markov model (HMM)/deep neural network (DNN) makes the system complex as it requires various modules such as acoustic, lexicon, linguistic resources, language models et
Autor:
Jyoti Guglani, A. N. Mishra
Publikováno v:
International Journal of Speech Technology. 24:41-45
This paper demonstrates the effect of incorporating Deep Neural Network techniques in speech recognition systems. Speech recognition through hybrid Deep Neural Networks on the Kaldi toolkit for the Punjabi language is implemented. Performance of the
Autor:
Radhika Rajeev Nair, K. Jeeva Priya, Mayuka Srinivasan, Karra Venkata Lakshmi Sri, Deepa Gupta
Publikováno v:
Procedia Computer Science. 171:2476-2485
This paper discusses an automatic speech recognition (ASR) system in Hindi. The language models and acoustic models are built using the open source toolkit Kaldi. A significant portion of the corpus built for this work pertains to the medical domain,
Publikováno v:
International Journal of Speech Technology. 23:141-147
Collecting phonetically balanced text corpus is an important step to develop automatic speech recognition and text-to-speech systems. A corpus should have a small number of sentences but contains all phonetic units, such as monophone, triphone, and p
Autor:
Volodymyr Blintsov, Sergey Nuzhniy
Publikováno v:
Східно-Європейський журнал передових технологій; Том 6, № 9 (102) (2019): Інформаційно-керуючі системи; 28-38
Восточно-Европейский журнал передовых технологий; Том 6, № 9 (102) (2019): Информационно-управляющие системы; 28-38
Eastern-European Journal of Enterprise Technologies; Том 6, № 9 (102) (2019): Information and controlling system; 28-38
Eastern-European Journal of Enterprise Technologies, Vol 6, Iss 9 (102), Pp 28-38 (2019)
Восточно-Европейский журнал передовых технологий; Том 6, № 9 (102) (2019): Информационно-управляющие системы; 28-38
Eastern-European Journal of Enterprise Technologies; Том 6, № 9 (102) (2019): Information and controlling system; 28-38
Eastern-European Journal of Enterprise Technologies, Vol 6, Iss 9 (102), Pp 28-38 (2019)
Assessment of the level of speech information protection from leakage through acoustic and vibration channels is carried out according to international and national standards and in compliance with regulatory documents. To assess its security level,
Autor:
Siyuan Feng, Tan Lee
Publikováno v:
IEEE/ACM Transactions on Audio, Speech, and Language Processing. 27:2000-2011
This research addresses the problem of acoustic modeling of low-resource languages for which transcribed training data is absent. The goal is to learn robust frame-level feature representations that can be used to identify and distinguish subword-lev
Publikováno v:
IEEE Transactions on Consumer Electronics. 65:188-194
Speech-based interfaces are convenient and intuitive, and therefore, strongly preferred by Internet of Things (IoT) devices for human–computer interaction. Pre-defined keywords are typically used as a trigger to notify devices for inputting the sub
Publikováno v:
International Journal of Speech Technology. 22:205-217
Spoken term detection (STD) refers to discovering all occurrences of a given term in a set of speech utterances. One of the well-known approaches for the STD system is the phone lattice search (PLS) that produces a phone-based lattice of speech utter
Autor:
Josafa Aguiar, Jonathan A. Zea
Publikováno v:
2021 Second International Conference on Information Systems and Software Technologies (ICI2ST).
The goal of this ASR system is to be able to recognize audio queries that request static translation of a given Spanish word into a specified language. We call this ASR system as the Spanish Poliglota. The pronunciation dictionary for the language mo
Autor:
Nancy F. Chen, Richeng Duan
Publikováno v:
ICASSP
Acoustic modeling for child speech is challenging due to the high acoustic variability caused by physiological differences in the vocal tract. The dearth of publicly available datasets makes the task more challenging. In this work, we propose a featu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::11d365742e824dc70366bfa251bb2c56
http://arxiv.org/abs/2102.11488
http://arxiv.org/abs/2102.11488