Log in

Relevant bibliographies by topics / ASR-system / Journal articles

To see the other types of publications on this topic, follow the link: ASR-system.

Journal articles on the topic 'ASR-system'

Author: Grafiati

Published: 30 May 2022

Last updated: 31 July 2025

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles

Select a source type:

Consult the top 50 journal articles for your research on the topic 'ASR-system.'

Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.

You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.

Browse journal articles on a wide variety of disciplines and organise your bibliography correctly.

1

de Steiger, Richard N., Jacqueline R. Hang, Lisa N. Miller, Stephen E. Graves, and David C. Davidson. "Five-Year Results of the ASR XL Acetabular System and the ASR Hip Resurfacing System." Journal of Bone and Joint Surgery-American Volume 93, no. 24 (2011): 2287–93. http://dx.doi.org/10.2106/jbjs.j.01727.

Full text

APA, Harvard, Vancouver, ISO, and other styles

2

Udofia, Paul Moses. "A Critical and Optimal Location for an Autonomous Security Robot in Niger Delta, Nigeria." Advanced Materials Research 403-408 (November 2011): 4944–48. http://dx.doi.org/10.4028/www.scientific.net/amr.403-408.4944.

Full text

Abstract:

Autonomous Security robots (ASR) can be used to provide security where and when it is too hazardous to the human security guards. The paper is suggesting the introduction/incorporation of ASR into the Niger Delta security system (NDSS). Critical points (where ASR are needed) within the zones are identified based on the past security records. These records served as baseline data which regression lines are generated and produced into some future dates. How many ASR are required at a particular time in the system? Is the number feasible? What are the likely obstructions of the project? These are

APA, Harvard, Vancouver, ISO, and other styles

3

Qian, Zhaopeng, Li Wang, Shaochuan Zhang, Chan Liu, and Haijun Niu. "Mandarin Electrolaryngeal Speech Recognition Based on WaveNet-CTC." Journal of Speech, Language, and Hearing Research 62, no. 7 (2019): 2203–12. http://dx.doi.org/10.1044/2019_jslhr-s-18-0313.

Full text

Abstract:

Purpose The application of Chinese Mandarin electrolaryngeal (EL) speech for laryngectomees has been limited by its drawbacks such as single fundamental frequency, mechanical sound, and large radiation noise. To improve the intelligibility of Chinese Mandarin EL speech, a new perspective using the automatic speech recognition (ASR) system was proposed, which can convert EL speech into healthy speech, if combined with text-to-speech. Method An ASR system was designed to recognize EL speech based on a deep learning model WaveNet and the connectionist temporal classification (WaveNet-CTC). This s

APA, Harvard, Vancouver, ISO, and other styles

4

Lin, Yu-Yi, Wei-Zhong Zheng, Wei Chung Chu, et al. "A Speech Command Control-Based Recognition System for Dysarthric Patients Based on Deep Learning Technology." Applied Sciences 11, no. 6 (2021): 2477. http://dx.doi.org/10.3390/app11062477.

Full text

Abstract:

Voice control is an important way of controlling mobile devices; however, using it remains a challenge for dysarthric patients. Currently, there are many approaches, such as automatic speech recognition (ASR) systems, being used to help dysarthric patients control mobile devices. However, the large computation power requirement for the ASR system increases implementation costs. To alleviate this problem, this study proposed a convolution neural network (CNN) with a phonetic posteriorgram (PPG) speech feature system to recognize speech commands, called CNN–PPG; meanwhile, the CNN model with Mel

APA, Harvard, Vancouver, ISO, and other styles

5

Fontan, Lionel, Isabelle Ferrané, Jérôme Farinas, et al. "Automatic Speech Recognition Predicts Speech Intelligibility and Comprehension for Listeners With Simulated Age-Related Hearing Loss." Journal of Speech, Language, and Hearing Research 60, no. 9 (2017): 2394–405. http://dx.doi.org/10.1044/2017_jslhr-s-16-0269.

Full text

Abstract:

Purpose The purpose of this article is to assess speech processing for listeners with simulated age-related hearing loss (ARHL) and to investigate whether the observed performance can be replicated using an automatic speech recognition (ASR) system. The long-term goal of this research is to develop a system that will assist audiologists/hearing-aid dispensers in the fine-tuning of hearing aids. Method Sixty young participants with normal hearing listened to speech materials mimicking the perceptual consequences of ARHL at different levels of severity. Two intelligibility tests (repetition of w

APA, Harvard, Vancouver, ISO, and other styles

6

Neri, Ambra, Catia Cucchiarini, and Helmer Strik. "The effectiveness of computer-based speech corrective feedback for improving segmental quality in L2 Dutch." ReCALL 20, no. 2 (2008): 225–43. http://dx.doi.org/10.1017/s0958344008000724.

Full text

Abstract:

AbstractAlthough the success of automatic speech recognition (ASR)-based Computer Assisted Pronunciation Training (CAPT) systems is increasing, little is known about the pedagogical effectiveness of these systems. This is particularly regrettable because ASR technology still suffers from limitations that may result in the provision of erroneous feedback, possibly leading to learning breakdowns. To study the effectiveness of ASR-based feedback for improving pronunciation, we developed and tested a CAPT system providing automatic feedback on Dutch phonemes that are problematic for adult learners

APA, Harvard, Vancouver, ISO, and other styles

7

Hai, Xinhe, Kaviya Aranganadin, Cheng-Cheng Yeh, et al. "A Self-Evaluated Bilingual Automatic Speech Recognition System for Mandarin–English Mixed Conversations." Applied Sciences 15, no. 14 (2025): 7691. https://doi.org/10.3390/app15147691.

Full text

Abstract:

Bilingual communication is increasingly prevalent in this globally connected world, where cultural exchanges and international interactions are unavoidable. Existing automatic speech recognition (ASR) systems are often limited to single languages. However, the growing demand for bilingual ASR in human–computer interactions, particularly in medical services, has become indispensable. This article addresses this need by creating an application programming interface (API)-based platform using VOSK, a popular open-source single-language ASR toolkit, to efficiently deploy a self-evaluated bilingual

APA, Harvard, Vancouver, ISO, and other styles

8

Phuengrod, Siriluk, Panita Wannapiroon, and Prachyanun Nilsook. "Distributed Communicative Language Training Platform Using Automatic Speech Recognition Technology for Smart University." International Journal of Emerging Technologies in Learning (iJET) 18, no. 24 (2023): 96–111. http://dx.doi.org/10.3991/ijet.v18i24.40619.

Full text

Abstract:

The purpose of this research is to achieve the following objectives: 1) Synthesize documents and international research on the characteristics of a smart university. 2) Synthesize the processes of distributed communicative language training (DCLT). 3) Design the system architecture of a DCLT platform that utilizes automatic speech recognition (ASR) technology for a smart university. 4) Evaluate the appropriateness of a DCLT platform that utilizes ASR technology for a smart university. Nine experts were selected for this research. They were required to have more than five years of relevant expe

APA, Harvard, Vancouver, ISO, and other styles

9

Si, Mei, Omar Cobas, and Michael Fababeir. "Lexical Error Guard: Leveraging Large Language Models for Enhanced ASR Error Correction." Machine Learning and Knowledge Extraction 6, no. 4 (2024): 2435–46. http://dx.doi.org/10.3390/make6040120.

Full text

Abstract:

Error correction is a vital element in modern automatic speech recognition (ASR) systems. A significant portion of ASR error correction work is closely integrated within specific ASR systems, which creates challenges for adapting these solutions to different ASR frameworks. This research introduces Lexical Error Guard (LEG), which leverages the extensive pre-trained knowledge of large language models (LLMs) and employs instructional learning to create an adaptable error correction system compatible with various ASR platforms. Additionally, a parameter-efficient fine-tuning method is utilized u

APA, Harvard, Vancouver, ISO, and other styles

10

Hamidi, Mohamed, Hassan Satori, Ouissam Zealouk, and Naouar Laaidi. "Estimation of ASR Parameterization for Interactive System." International Journal of Natural Computing Research 10, no. 1 (2021): 28–40. http://dx.doi.org/10.4018/ijncr.2021010103.

Full text

Abstract:

In this study, the authors explore the integration of speaker-independent automatic Amazigh speech recognition technology into interactive applications to extract data remotely from a distance database. Based on the combined interactive voice response (IVR) and automatic speech recognition (ASR) technologies, the authors built an interactive speech system to allow users to interact with the interactive system through voice commands. The hidden Markov models (HMMs), Gaussian mixture models (GMMs), and Mel frequency spectral coefficients (MFCCs) are used to develop a speech system based on the t

APA, Harvard, Vancouver, ISO, and other styles

11

Gunson, Catherine S. "The ASR Hip Resurfacing System: my experience." Medical Journal of Australia 194, no. 12 (2011): 661–62. http://dx.doi.org/10.5694/j.1326-5377.2011.tb03157.x.

Full text

APA, Harvard, Vancouver, ISO, and other styles

12

Liu, Kai-Wei, and Anal K. Mukhopadhyay. "A kinetic-based ASR aggregate classification system." Construction and Building Materials 68 (October 2014): 525–34. http://dx.doi.org/10.1016/j.conbuildmat.2014.07.005.

Full text

APA, Harvard, Vancouver, ISO, and other styles

13

Jalalvand, Shahab, Matteo Negri, Daniele Falavigna, Marco Matassoni, and Marco Turchi. "Automatic quality estimation for ASR system combination." Computer Speech & Language 47 (January 2018): 214–39. http://dx.doi.org/10.1016/j.csl.2017.06.003.

Full text

APA, Harvard, Vancouver, ISO, and other styles

14

Chen, Sin-Horng, Jyh-Her Yang, Chen-Yu Chiang, Ming-Chieh Liu, and Yih-Ru Wang. "A New Prosody-Assisted Mandarin ASR System." IEEE Transactions on Audio, Speech, and Language Processing 20, no. 6 (2012): 1669–84. http://dx.doi.org/10.1109/tasl.2012.2187192.

Full text

APA, Harvard, Vancouver, ISO, and other styles

15

G, Thimmaraja Yadava, G. Nagaraja B, Yogesh Kumaran S, C. Ramachandra A, and M. Arun Kumar N. "Development of Small Vocabulary Continuous Speech-to-Text System for Kannada Language/Dialects." Indian Journal of Science and Technology 15, no. 45 (2022): 2476–81. https://doi.org/10.17485/IJST/v15i45.1884.

Full text

Abstract:

Abstract <strong>Objectives:</strong> To develop a speech-to-text (STT) system using Kaldi speech recognition toolkit for continuous Kannada language/dialects. <strong>Methods:</strong> A continuous Kannada speech data is collected from 100 speakers/farmers of Karnataka state in field. The lexicon/dictionary and set of phonemes for Kannada language/dialects are created and transcribed the collected speech data using transcriber tool. The ASR models are developed at different phoneme levels using Kaldi. <strong>Findings:</strong> In this work, an effort is made to devel

APA, Harvard, Vancouver, ISO, and other styles

16

Zhang, Long, Ziping Zhao, Chunmei Ma, et al. "End-to-End Automatic Pronunciation Error Detection Based on Improved Hybrid CTC/Attention Architecture." Sensors 20, no. 7 (2020): 1809. http://dx.doi.org/10.3390/s20071809.

Full text

Abstract:

Advanced automatic pronunciation error detection (APED) algorithms are usually based on state-of-the-art automatic speech recognition (ASR) techniques. With the development of deep learning technology, end-to-end ASR technology has gradually matured and achieved positive practical results, which provides us with a new opportunity to update the APED algorithm. We first constructed an end-to-end ASR system based on the hybrid connectionist temporal classification and attention (CTC/attention) architecture. An adaptive parameter was used to enhance the complementarity of the connectionist tempora

APA, Harvard, Vancouver, ISO, and other styles

17

Kelley, Van, Michael Turco, Neil Deeds, Christina Petersen, and Chris Canonico. "Assessment of subsidence risk associated with aquifer storage and recovery in the Coastal Lowlands Aquifer System, Houston, Texas, USA." Proceedings of the International Association of Hydrological Sciences 382 (April 22, 2020): 487–91. http://dx.doi.org/10.5194/piahs-382-487-2020.

Full text

Abstract:

Abstract. In the Houston, Texas region, groundwater use is regulated by the Harris-Galveston Subsidence District (District) because of historical regional subsidence from groundwater development. The District regulates groundwater production in the Coastal Lowlands Aquifer System (CLAS) to mitigate subsidence through the implementation of District Groundwater Regulatory Plan. The District has successfully reduced groundwater pumping as a percent of demand regionally while controlling subsidence through the implementation of alternative water supplies. Aquifer Storage and Recovery (ASR) is an a

APA, Harvard, Vancouver, ISO, and other styles

18

Perero-Codosero, Juan M., Fernando M. Espinoza-Cuadros, and Luis A. Hernández-Gómez. "A Comparison of Hybrid and End-to-End ASR Systems for the IberSpeech-RTVE 2020 Speech-to-Text Transcription Challenge." Applied Sciences 12, no. 2 (2022): 903. http://dx.doi.org/10.3390/app12020903.

Full text

Abstract:

This paper describes a comparison between hybrid and end-to-end Automatic Speech Recognition (ASR) systems, which were evaluated on the IberSpeech-RTVE 2020 Speech-to-Text Transcription Challenge. Deep Neural Networks (DNNs) are becoming the most promising technology for ASR at present. In the last few years, traditional hybrid models have been evaluated and compared to other end-to-end ASR systems in terms of accuracy and efficiency. We contribute two different approaches: a hybrid ASR system based on a DNN-HMM and two state-of-the-art end-to-end ASR systems, based on Lattice-Free Maximum Mut

APA, Harvard, Vancouver, ISO, and other styles

19

Gellatly, Andrew W., and Thomas A. Dingus. "Speech Recognition and Automotive Applications: Using Speech to Perform in-Vehicle Tasks." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 42, no. 17 (1998): 1247–51. http://dx.doi.org/10.1177/154193129804201715.

Full text

Abstract:

An experiment was conducted to investigate the effects of automatic speech recognition (ASR) system design, driver input-modality, and driver age on driving performance during in-vehicle task execution and in-vehicle task usability. Results showed that ASR system design (i.e., recognition accuracy and recognition error type) and driver input-modality (i.e., manual or speech) significantly affected certain dependent measures. However, the differences found were small, suggesting that less than ideal ASR system design/performance can be considered for use in automobiles without substantially imp

APA, Harvard, Vancouver, ISO, and other styles

20

Ogasawara, Hiroshi, Akiko Hasegawa, Emi Kanda, Takenori Miki, Kaneyoshi Yamamoto, and Akira Ishihama. "Genomic SELEX Search for Target Promoters under the Control of the PhoQP-RstBA Signal Relay Cascade." Journal of Bacteriology 189, no. 13 (2007): 4791–99. http://dx.doi.org/10.1128/jb.00319-07.

Full text

Abstract:

ABSTRACT RstBA, a two-component regulatory system of Escherichia coli with an unidentified regulatory function, is under the control of a Mg2+-sensing PhoQP two-component system. In order to identify the network of transcription regulation downstream of RstBA, we isolated a set of RstA-binding sequences from the E. coli genome by using the genomic SELEX system. A gel mobility shift assay indicated the binding of RstA to two SELEX DNA fragments, one including the promoter region of asr (acid shock RNA) and another including the promoter for csgD (a regulator of the curli operon). Using a DNase

APA, Harvard, Vancouver, ISO, and other styles

21

Székely, Tamás, András Liker, Robert P. Freckleton, Claudia Fichtel, and Peter M. Kappeler. "Sex-biased survival predicts adult sex ratio variation in wild birds." Proceedings of the Royal Society B: Biological Sciences 281, no. 1788 (2014): 20140342. http://dx.doi.org/10.1098/rspb.2014.0342.

Full text

Abstract:

Adult sex ratio (ASR) is a central concept in population demography and breeding system evolution, and has implications for population viability and biodiversity conservation. ASR exhibits immense interspecific variation in wild populations, although the causes of this variation have remained elusive. Using phylogenetic analyses of 187 avian species from 59 families, we show that neither hatching sex ratios nor fledging sex ratios correlate with ASR. However, sex-biased adult mortality is a significant predictor of ASR, and this relationship is robust to 100 alternative phylogenetic hypotheses

APA, Harvard, Vancouver, ISO, and other styles

22

ZENG, LINGZAO, and JIANLONG LI. "RESIDUAL APERIODIC STOCHASTIC RESONANCE IN LÉVY NOISE." Fluctuation and Noise Letters 10, no. 02 (2011): 223–29. http://dx.doi.org/10.1142/s0219477511000508.

Full text

Abstract:

We investigate the effect of Lévy noise on the noise-induced residual aperiodic stochastic resonance (ASR). It is shown that, the residual ASR still exists when the noise is Lévy distributed. However, it is reduced by Lévy noise compared to that in the Gaussian noise with the same intensity. It is also shown that, the minimum bit error rate (BER) of the Lévy-noise-induced ASR is slightly higher than that of the Gaussian-noise-induced ASR, which indicates that tuning system parameters is a better approach to get the optimal performance.

APA, Harvard, Vancouver, ISO, and other styles

23

Singh, Satyanand. "High level speaker specific features modeling in automatic speaker recognition system." International Journal of Electrical and Computer Engineering (IJECE) 10, no. 2 (2020): 1859. http://dx.doi.org/10.11591/ijece.v10i2.pp1859-1867.

Full text

Abstract:

Spoken words convey several levels of information. At the primary level, the speech conveys words or spoken messages, but at the secondary level, the speech also reveals information about the speakers. This work is based on the high-level speaker-specific features on statistical speaker modeling techniques that express the characteristic sound of the human voice. Using Hidden Markov model (HMM), Gaussian mixture model (GMM), and Linear Discriminant Analysis (LDA) models build Automatic Speaker Recognition (ASR) system that are computational inexpensive can recognize speakers regardless of what

APA, Harvard, Vancouver, ISO, and other styles

24

Satyanand, Singh, and Singh Pragya. "High level speaker specific features modeling in automatic speaker recognition system." International Journal of Electrical and Computer Engineering (IJECE) 10, no. 2 (2020): 1859–67. https://doi.org/10.11591/ijece.v10i2.pp1859-1867.

Full text

Abstract:

Spoken words convey several levels of information. At the primary level, the speech conveys words or spoken messages, but at the secondary level, the speech also reveals information about the speakers. This work is based on the high-level speaker-specific features on statistical speaker modeling techniques that express the characteristic sound of the human voice. Using Hidden Markov model (HMM), Gaussian mixture model (GMM), and Linear Discriminant Analysis (LDA) models build Automatic Speaker Recognition (ASR) system that are computational inexpensive can recognize speakers regardless of what

APA, Harvard, Vancouver, ISO, and other styles

25

Bhattacharjee, Mrinmoy, Petr Motlicek, Srikanth Madikeri, et al. "Minimum effort adaptation of automatic speech recognition system in air traffic management." European Journal of Transport and Infrastructure Research 24, no. 4 (2025): 133–53. https://doi.org/10.59490/ejtir.2024.24.4.7531.

Full text

Abstract:

Advancements in Automatic Speech Recognition (ASR) technology is exemplified by ubiquitous voice assistants such as Siri and Alexa. Researchers have been exploring the application of ASR for Air Traffic Management (ATM) systems. Initial prototypes utilized ASR to pre-fill aircraft radar labels and achieved a technological readiness level before industrialization (TRL6). However, accurately recognizing infrequently used but highly informative domain-specific vocabulary is still an issue. This includes waypoint names specific to each airspace region and unique airline designators, e.g., “dexon”

APA, Harvard, Vancouver, ISO, and other styles

26

Kim, Seoyoung, Yeon Su Park, Dakyeom Ahn, Jin Myung Kwak, and Juho Kim. "Is the Same Performance Really the Same?: Understanding How Listeners Perceive ASR Results Differently According to the Speaker's Accent." Proceedings of the ACM on Human-Computer Interaction 8, CSCW1 (2024): 1–22. http://dx.doi.org/10.1145/3641008.

Full text

Abstract:

Research suggests that automatic speech recognition (ASR) systems, which automatically convert speech to text, show different performances according to various input classes (e.g., accent, age), requiring attention to building fairer AI systems that would perform similarly across various input classes. However, would an AI system with the same performance regardless of input classes really be perceived as fair enough? To this end, we investigate how listeners perceive the ASR system of the same result differently according to whether the speaker is a native speaker (NS) or a non-native speaker

APA, Harvard, Vancouver, ISO, and other styles

27

Woś, Adam, and Andrzej Szosland. "A prototype ASR system for vehicles with pneumatic braking system." Archives of Automotive Engineering/ Archiwum Motoryzacji 54, no. 4 (2013): 75–84. http://dx.doi.org/10.5604/1234754x.1066759.

Full text

APA, Harvard, Vancouver, ISO, and other styles

28

Bhardwaj, Vivek, Vinay Kukreja, and Amitoj Singh. "Usage of Prosody Modification and Acoustic Adaptation for Robust Automatic Speech Recognition (ASR) System." Revue d'Intelligence Artificielle 35, no. 3 (2021): 235–42. http://dx.doi.org/10.18280/ria.350307.

Full text

Abstract:

Most of the automatic speech recognition (ASR) systems are trained using adult speech due to the less availability of the children's speech dataset. The speech recognition rate of such systems is very less when tested using the children's speech, due to the presence of the inter-speaker acoustic variabilities between the adults and children's speech. These inter-speaker acoustic variabilities are mainly because of the higher pitch and lower speaking rate of the children. Thus, the main objective of the research work is to increase the speech recognition rate of the Punjabi-ASR system by reduci

APA, Harvard, Vancouver, ISO, and other styles

29

Miao, Yuantian, Minhui Xue, Chao Chen, et al. "The Audio Auditor: User-Level Membership Inference in Internet of Things Voice Services." Proceedings on Privacy Enhancing Technologies 2021, no. 1 (2021): 209–28. http://dx.doi.org/10.2478/popets-2021-0012.

Full text

Abstract:

AbstractWith the rapid development of deep learning techniques, the popularity of voice services implemented on various Internet of Things (IoT) devices is ever increasing. In this paper, we examine user-level membership inference in the problem space of voice services, by designing an audio auditor to verify whether a specific user had unwillingly contributed audio used to train an automatic speech recognition (ASR) model under strict black-box access. With user representation of the input audio data and their corresponding translated text, our trained auditor is effective in user-level audit

APA, Harvard, Vancouver, ISO, and other styles

30

Kim, June-Woo, Hyekyung Yoon, and Ho-Young Jung. "Improved Spoken Language Representation for Intent Understanding in a Task-Oriented Dialogue System." Sensors 22, no. 4 (2022): 1509. http://dx.doi.org/10.3390/s22041509.

Full text

Abstract:

Successful applications of deep learning technologies in the natural language processing domain have improved text-based intent classifications. However, in practical spoken dialogue applications, the users’ articulation styles and background noises cause automatic speech recognition (ASR) errors, and these may lead language models to misclassify users’ intents. To overcome the limited performance of the intent classification task in the spoken dialogue system, we propose a novel approach that jointly uses both recognized text obtained by the ASR model and a given labeled text. In the evaluati

APA, Harvard, Vancouver, ISO, and other styles

31

Hatala, Zulkarnaen. "Langkah Praktis Membangun Sistem Pengenalan Suara dengan HTK." JSAI (Journal Scientific and Applied Informatics) 2, no. 2 (2019): 149–53. http://dx.doi.org/10.36085/jsai.v2i2.314.

Full text

Abstract:

Dipaparkan prosedur untuk mengembangkan Sistem Pengenalan Suara otomatis, Automatic Speech Recognition System (ASR) untuk kasus online recognition. Prosedur ini secara cepat dan efisien membangun ASR menggunakan Hidden Markov Toolkit (HTK). Langkah-langkah praktis ini dipaparkan secara jelas untuk mengimplementasikan ASR dengan daftar kata sedikit (Small Vocabulary) dalam contoh kasus pengenalan digit Bahasa Indonesia. Dijelaskan beberapa teknik meningkatkan performansi seperti cara mengatasi noise, pengejaan ganda dan penerapan Principle Component Analysis. Hasil akhir berupa Word Error Rate

APA, Harvard, Vancouver, ISO, and other styles

32

Sirora, Leslie Wellington, and Mainford Mutandavari. "A Deep Learning Automatic Speech Recognition Model for Shona Language." International Journal of Innovative Research in Computer and Communication Engineering 12, no. 09 (2024): 1–14. http://dx.doi.org/10.15680/ijircce.2024.1209019.

Full text

Abstract:

This study presented the development of a deep learning-based Automatic Speech Recognition (ASR) system for Shona, a low-resource language characterized by unique tonal and grammatical complexities. The research aimed to address the challenges posed by limited training data, a lack of labelled data, and the intricate tonal nuances present in Shona speech, with the objective of achieving significant improvements in recognition accuracy compared to traditional statistical models. Motivated by the limitations of existing approaches, the research addressed three key questions. Firstly, it explored

APA, Harvard, Vancouver, ISO, and other styles

33

Rendle, Emma Jane, and Mark Davidson. "AN EVALUATION OF THE PHYSICAL IMPACT AND STRUCTURAL INTEGRITY OF A GEOTEXTILE SURF REEF." Coastal Engineering Proceedings 1, no. 33 (2012): 21. http://dx.doi.org/10.9753/icce.v33.structures.21.

Full text

Abstract:

Geotextile artificial surfing reefs (ASR) are being considered by coastal planners due to their multifunctional potential for coastal protection and habitat provision, as well as additional recreational amenity. However, little research exists on the impact of submerged geotextile structures on the physical marine environment. Europe’s first ASR was constructed in 2009 on the south coast of England in Boscombe and is the case study for this paper. This research investigates the claims regarding the structural resilience of an ASR, the modifications to the inshore wave climate and the shoreline

APA, Harvard, Vancouver, ISO, and other styles

34

Silber Varod, Vered, Ingo Siegert, Oliver Jokisch, Yamini Sinha, and Nitza Geri. "A cross-language study of speech recognition systems for English, German, and Hebrew." Online Journal of Applied Knowledge Management 9, no. 1 (2021): 1–15. http://dx.doi.org/10.36965/ojakm.2021.9(1)1-15.

Full text

Abstract:

Despite the growing importance of Automatic Speech Recognition (ASR), its application is still challenging, limited, language-dependent, and requires considerable resources. The resources required for ASR are not only technical, they also need to reflect technological trends and cultural diversity. The purpose of this research is to explore ASR performance gaps by a comparative study of American English, German, and Hebrew. Apart from different languages, we also investigate different speaking styles – utterances from spontaneous dialogues and utterances from frontal lectures (TED-like genre).

APA, Harvard, Vancouver, ISO, and other styles

35

Sužiede˙liene˙, Edita, Ke˛stutis Sužiede˙lis, Vaida Garbenčiute˙, and Staffan Normark. "The Acid-Inducible asr Gene inEscherichia coli: Transcriptional Control by thephoBR Operon." Journal of Bacteriology 181, no. 7 (1999): 2084–93. http://dx.doi.org/10.1128/jb.181.7.2084-2093.1999.

Full text

Abstract:

ABSTRACT Escherichia coli responds to external acidification (pH 4.0 to 5.0) by synthesizing a newly identified, ∼450-nucleotide RNA component. At maximal levels of induction it is one of the most abundant small RNAs in the cell and is relatively stable bacterial RNA. The acid-inducible RNA was purified, and the gene encoding it, designated asr (for acid shock RNA), mapped at 35.98 min on the E. coli chromosome. Analysis of the asr DNA sequence revealed an open reading frame coding for a 111-amino-acid polypeptide with a deduced molecular mass of approximately 11.6 kDa. According to computer-a

APA, Harvard, Vancouver, ISO, and other styles

36

Wang, Desheng, Yangjie Wei, Ke Zhang, Dong Ji, and Yi Wang. "Automatic Speech Recognition Performance Improvement for Mandarin Based on Optimizing Gain Control Strategy." Sensors 22, no. 8 (2022): 3027. http://dx.doi.org/10.3390/s22083027.

Full text

Abstract:

Automatic speech recognition (ASR) is an essential technique of human–computer interactions; gain control is a commonly used operation in ASR. However, inappropriate gain control strategies can lead to an increase in the word error rate (WER) of ASR. As there is a current lack of sufficient theoretical analyses and proof of the relationship between gain control and WER, various unconstrained gain control strategies have been adopted on realistic ASR systems, and the optimal gain control with respect to the lowest WER, is rarely achieved. A gain control strategy named maximized original signal

APA, Harvard, Vancouver, ISO, and other styles

37

Lin, Yi, Xianlong Tan, Bo Yang, Kai Yang, Jianwei Zhang, and Jing Yu. "Real-time Controlling Dynamics Sensing in Air Traffic System." Sensors 19, no. 3 (2019): 679. http://dx.doi.org/10.3390/s19030679.

Full text

Abstract:

In order to obtain real-time controlling dynamics in air traffic system, a framework is proposed to introduce and process air traffic control (ATC) speech via radiotelephony communication. An automatic speech recognition (ASR) and controlling instruction understanding (CIU)-based pipeline is designed to convert the ATC speech into ATC related elements, i.e., controlling intent and parameters. A correction procedure is also proposed to improve the reliability of the information obtained by the proposed framework. In the ASR model, acoustic model (AM), pronunciation model (PM), and phoneme- and

APA, Harvard, Vancouver, ISO, and other styles

38

Pinska-Chauvin, Ella, Hartmut Helmke, Jelena Dokic, Petri Hartikainen, Oliver Ohneiser, and Raquel García Lasheras. "Ensuring Safety for Artificial-Intelligence-Based Automatic Speech Recognition in Air Traffic Control Environment." Aerospace 10, no. 11 (2023): 941. http://dx.doi.org/10.3390/aerospace10110941.

Full text

Abstract:

This paper describes the safety assessment conducted in SESAR2020 project PJ.10-W2-96 ASR on automatic speech recognition (ASR) technology implemented for air traffic control (ATC) centers. ASR already now enables the automatic recognition of aircraft callsigns and various ATC commands including command types based on controller–pilot voice communications for presentation at the controller working position. The presented safety assessment process consists of defining design requirements for ASR technology application in normal, abnormal, and degraded modes of ATC operations. A total of eight f

APA, Harvard, Vancouver, ISO, and other styles

39

Raval, Deepang, Vyom Pathak, Muktan Patel, and Brijesh Bhatt. "Improving Deep Learning based Automatic Speech Recognition for Gujarati." ACM Transactions on Asian and Low-Resource Language Information Processing 21, no. 3 (2022): 1–18. http://dx.doi.org/10.1145/3483446.

Full text

Abstract:

We present a novel approach for improving the performance of an End-to-End speech recognition system for the Gujarati language. We follow a deep learning-based approach that includes Convolutional Neural Network, Bi-directional Long Short Term Memory layers, Dense layers, and Connectionist Temporal Classification as a loss function. To improve the performance of the system with the limited size of the dataset, we present a combined language model (Word-level language Model and Character-level language model)-based prefix decoding technique and Bidirectional Encoder Representations from Transfo

APA, Harvard, Vancouver, ISO, and other styles

40

Kamiński, Kamil A., and Andrzej P. Dobrowolski. "Automatic Speaker Recognition System Based on Gaussian Mixture Models, Cepstral Analysis, and Genetic Selection of Distinctive Features." Sensors 22, no. 23 (2022): 9370. http://dx.doi.org/10.3390/s22239370.

Full text

Abstract:

This article presents the Automatic Speaker Recognition System (ASR System), which successfully resolves problems such as identification within an open set of speakers and the verification of speakers in difficult recording conditions similar to telephone transmission conditions. The article provides complete information on the architecture of the various internal processing modules of the ASR System. The speaker recognition system proposed in the article, has been compared very closely to other competing systems, achieving improved speaker identification and verification results, on known cer

APA, Harvard, Vancouver, ISO, and other styles

41

Dua, Mohit, Rajesh Kumar Aggarwal, and Mantosh Biswas. "Optimizing Integrated Features for Hindi Automatic Speech Recognition System." Journal of Intelligent Systems 29, no. 1 (2018): 959–76. http://dx.doi.org/10.1515/jisys-2018-0057.

Full text

Abstract:

Abstract An automatic speech recognition (ASR) system translates spoken words or utterances (isolated, connected, continuous, and spontaneous) into text format. State-of-the-art ASR systems mainly use Mel frequency (MF) cepstral coefficient (MFCC), perceptual linear prediction (PLP), and Gammatone frequency (GF) cepstral coefficient (GFCC) for extracting features in the training phase of the ASR system. Initially, the paper proposes a sequential combination of all three feature extraction methods, taking two at a time. Six combinations, MF-PLP, PLP-MFCC, MF-GFCC, GF-MFCC, GF-PLP, and PLP-GFCC,

APA, Harvard, Vancouver, ISO, and other styles

42

Kawahara, Tatsuya. "Transcription System Using Automatic Speech Recognition for the Japanese Parliament (Diet)." Proceedings of the AAAI Conference on Artificial Intelligence 26, no. 2 (2012): 2224–28. http://dx.doi.org/10.1609/aaai.v26i2.18962.

Full text

Abstract:

This article describes a new automatic transcription system in the Japanese Parliament which deploys our automatic speech recognition (ASR) technology. To achieve high recognition performance in spontaneous meeting speech, we have investigated an efficient training scheme with minimal supervision which can exploit a huge amount of real data. Specifically, we have proposed a lightly-supervised training scheme based on statistical language model transformation, which fills the gap between faithful transcripts of spoken utterances and final texts for documentation. Once this mapping is trained, w

APA, Harvard, Vancouver, ISO, and other styles

43

Kim, Ji Youn. "Research Trends in the Evaluation and Treatment of Speech Disorders Using Automatic Speech Recognition (ASR)." Audiology and Speech Research 20, no. 4 (2024): 253–62. http://dx.doi.org/10.21848/asr.240159.

Full text

Abstract:

Purpose: The purpose of this study is to examine recent research trends regarding automatic speech recognition (ASR), which is used in the evaluation and intervention of speech disorders.Methods: Through a search engine, articles published in domestic journals were searched. A total of 27 papers were selected from the searched documents and analyzed according to the year, research subject, speech task, and ASR system.Results: The years with the most research was done in 2019~2021. The subjects who most frequently underwent speech evaluation and treatment using ASR system were those with dysart

APA, Harvard, Vancouver, ISO, and other styles

44

Mengke, Dalai, Yan Meng, and Péter Mihajlik. "Transliteration-Aided Transfer Learning for Low-Resource ASR: A Case Study on Khalkha Mongolian." Electronics 14, no. 6 (2025): 1137. https://doi.org/10.3390/electronics14061137.

Full text

Abstract:

Automatic Speech Recognition (ASR) systems have made consistent advancements, achieving notable improvements in state-of-the-art performance across various languages. However, their effectiveness often declines significantly in low-resource settings, where data and linguistic resources are limited. This paper addresses the challenges of ASR for a low-resource language, Khalkha Mongolian, by leveraging a transliteration-aided transfer learning approach. Specifically, it improves the ASR system for Khalkha Mongolian by transliterating text from a well-resourced Chakhar Mongolian (Uighur script)

APA, Harvard, Vancouver, ISO, and other styles

45

Jamil, Bushra, Saba Sultan, and Humaira Ijaz. "Design and Development of an Acoustic-Based Recongnition System Using DNN." Sukkur IBA Journal of Computing and Mathematical Sciences 8, no. 1 (2024): 32–42. http://dx.doi.org/10.30537/sjcms.v8i1.1400.

Full text

Abstract:

Automatic speech recognition is a process of using computers to convert voice signals produced by human speech into reasonable format i.e. text or command that conveys the same meaning as the speaker intended to do. Many researchers are working on various languages including English and other European languages like Spanish, German, and French etc. to develop an automated system for speech recognition (ASR). However, researchers on the development of ASR for the Urdu language have put very little effort. We have developed an Urdu speech recognition system using Deep Neural Network (DNN) on our

APA, Harvard, Vancouver, ISO, and other styles

46

Kumar, B. Sathis. "EVALUATION OF CAPTURING ARCHITECTURALLY SIGNIFICANT REQUIREMENTS." Asian Journal of Pharmaceutical and Clinical Research 10, no. 13 (2017): 122. http://dx.doi.org/10.22159/ajpcr.2017.v10s1.19589.

Full text

Abstract:

Every software development organization strives for customer satisfaction. It is universally accepted that the success of software development lies in the clear understanding of the client requirements. During requirement elicitation and analysis stage, the system analyst identifies the functional and non-functional requirements from the customer. Security, usability, reliability, performance, scalability and supportability are the significant quality attributes of a software system. These quality attributes are also referred as non-functional requirements. Only a few functional and quality at

APA, Harvard, Vancouver, ISO, and other styles

47

Satyanand, Singh, and Singh2 Pragya. "Kernal based speaker specific feature extraction and its applications in iTaukei cross language speaker recognition." TELKOMNIKA Telecommunication, Computing, Electronics and Control 18, no. 5 (2020): 2488~2497. https://doi.org/10.12928/TELKOMNIKA.v18i5.14655.

Full text

Abstract:

Extraction and classification algorithms based on kernel nonlinear features are popular in the new direction of research in machine learning. This research paper considers their practical application in the iTaukei automatic speaker recognition system (ASR) for cross-language speech recognition. Second, nonlinear speaker-specific extraction methods such as kernel principal component analysis (KPCA), kernel independent component analysis (KICA), and kernel linear discriminant analysis (KLDA) are summarized. The conversion effects on subsequent classifications were tested in conjunction with Gau

APA, Harvard, Vancouver, ISO, and other styles

48

Gong, Zhuo, Daisuke Saito, and Nobuaki Minematsu. "Entropy-Based Dynamic Rescoring with Language Model in E2E ASR Systems." Applied Sciences 12, no. 19 (2022): 9690. http://dx.doi.org/10.3390/app12199690.

Full text

Abstract:

Language models (LM) have played crucial roles in automatic speech recognition (ASR), whether as an essential part of a conventional ASR system composed of an acoustic model and LM, or as an integrated model to enhance the performance of novel end-to-end ASR systems. With the development of machine learning and deep learning, language modeling has made great progress in natural language processing applications. In recent years, efforts have been made to leverage the advantages of novel LM to ASR. The most common way to apply an integration is still shallow fusion because it can be easily imple

APA, Harvard, Vancouver, ISO, and other styles

49

Tejedor-García, Cristian, Valentín Cardeñoso-Payo, and David Escudero-Mancebo. "Automatic Speech Recognition (ASR) Systems Applied to Pronunciation Assessment of L2 Spanish for Japanese Speakers." Applied Sciences 11, no. 15 (2021): 6695. http://dx.doi.org/10.3390/app11156695.

Full text

Abstract:

General-purpose automatic speech recognition (ASR) systems have improved in quality and are being used for pronunciation assessment. However, the assessment of isolated short utterances, such as words in minimal pairs for segmental approaches, remains an important challenge, even more so for non-native speakers. In this work, we compare the performance of our own tailored ASR system (kASR) with the one of Google ASR (gASR) for the assessment of Spanish minimal pair words produced by 33 native Japanese speakers in a computer-assisted pronunciation training (CAPT) scenario. Participants in a pre

APA, Harvard, Vancouver, ISO, and other styles

50

Tasevski, Jovica, Milutin Nikolic, and Dragisa Miskovic. "Integration of an industrial robot with the systems for image and voice recognition." Serbian Journal of Electrical Engineering 10, no. 1 (2013): 219–30. http://dx.doi.org/10.2298/sjee1301219t.

Full text

Abstract:

The paper reports a solution for the integration of the industrial robot ABB IRB140 with the system for automatic speech recognition (ASR) and the system for computer vision. The robot has the task to manipulate the objects placed randomly on a pad lying on a table, and the computer vision system has to recognize their characteristics (shape, dimension, color, position, and orientation). The ASR system has a task to recognize human speech and use it as a command to the robot, so the robot can manipulate the objects.

APA, Harvard, Vancouver, ISO, and other styles

We offer discounts on all premium plans for authors whose works are included in thematic literature selections. Contact us to get a unique promo code!