scholarly journals An overview of speech recognition and its challenges

2015 ◽  
Vol 1 (1) ◽  
pp. 91-100
Author(s):  
Banumathi A C ◽  
Chandra E

Speech Recognition means converting Speech into Text. This Emerging Technology makes all the field of use as more sophisticated one. The impact of this revolutionary Technology has shown its wide range of usage in all tasks. Almost all the Technical devices use the Speech recognition as their part of their project. Speech Recognition Technology used in fields like computers, artificial Intelligence, Medical , Healthcare, Smart Phones, etc., This paper provides a glimpse of the challenges that is faced by the speech recognition systems in many applications and the approaches taken to fulfill it.

2015 ◽  
Vol 7 (2) ◽  
pp. 53-78 ◽  
Author(s):  
Lionel Prat ◽  
Cheryl Baker ◽  
Nhien An Le-Khac

Recently, the integration of geographical coordinates into a picture has become more and more popular. Indeed almost all smartphones and many cameras today have a built-in GPS receiver that stores the location information in the Exif header when a picture is taken. Although the automatic embedding of geotags in pictures is often ignored by smart phone users as it can lead to endless discussions about privacy implications, these geotags could be really useful for investigators in analysing criminal activity. Currently, there are many free tools as well as commercial tools available in the market that can help computer forensics investigators to cover a wide range of geographic information related to criminal scenes or activities. However, there are not specific forensic tools available to deal with the geolocation of pictures taken by smart phones or cameras. In this paper, an image scanning and mapping tool for investigators is proposed and developed. This tool scans all the files in a given directory and then displays particular photos based on optional filters (date/time/device/localisation…) on Google Map. The file scanning process is not based on the file extension but its header. This tool can also show efficiently to users if there is more than one image on the map with the same GPS coordinates, or even if there are images with no GPS coordinates taken by the same device in the same timeline. Moreover, this new tool is portable; investigators can run it on any operating system without any installation. Another useful feature is to be able to work in a read-only environment, so that forensic results will not be modified. This tool's real-world application is also presented and evaluated in this paper.


2020 ◽  
pp. 1-12
Author(s):  
Duan Ran ◽  
Wang Yingli ◽  
Qin Haoxin

Artificial intelligence speech recognition technology is an important direction in the field of human-computer interaction. The use of speech recognition technology to assist teachers in the correction of spoken English pronunciation in teaching has certain effects and can help students without being constrained by places, time and teachers. Based on artificial intelligence speech recognition technology, this paper improves and analyzes speech recognition algorithms, and uses effective algorithms as the system algorithms of artificial intelligence models. Meanwhile, based on phoneme-level speech error correction, after introducing the basic knowledge, construction and training of acoustic models, the basic process of speech cutting, including the front-end processing of speech and the extraction of feature parameters, is elaborated. In addition, this study designed a control experiment to verify and analyze the artificial intelligence speech recognition correction model. The research results show that the method proposed in this paper has a certain effect.


2019 ◽  
Vol 6 (1) ◽  
pp. 205395171986054 ◽  
Author(s):  
Heike Felzmann ◽  
Eduard Fosch Villaronga ◽  
Christoph Lutz ◽  
Aurelia Tamò-Larrieux

Transparency is now a fundamental principle for data processing under the General Data Protection Regulation. We explore what this requirement entails for artificial intelligence and automated decision-making systems. We address the topic of transparency in artificial intelligence by integrating legal, social, and ethical aspects. We first investigate the ratio legis of the transparency requirement in the General Data Protection Regulation and its ethical underpinnings, showing its focus on the provision of information and explanation. We then discuss the pitfalls with respect to this requirement by focusing on the significance of contextual and performative factors in the implementation of transparency. We show that human–computer interaction and human-robot interaction literature do not provide clear results with respect to the benefits of transparency for users of artificial intelligence technologies due to the impact of a wide range of contextual factors, including performative aspects. We conclude by integrating the information- and explanation-based approach to transparency with the critical contextual approach, proposing that transparency as required by the General Data Protection Regulation in itself may be insufficient to achieve the positive goals associated with transparency. Instead, we propose to understand transparency relationally, where information provision is conceptualized as communication between technology providers and users, and where assessments of trustworthiness based on contextual factors mediate the value of transparency communications. This relational concept of transparency points to future research directions for the study of transparency in artificial intelligence systems and should be taken into account in policymaking.


2016 ◽  
Vol 40 (4) ◽  
pp. 504-517 ◽  
Author(s):  
Laina Y. Bay-Cheng ◽  
Anne E. Bruns

Reflecting the wide range of consensual unwanted sexual experiences, researchers often have contrasting views of the impact of these incidents on young women. Some scholars support a normalizing view of these as fairly harmless and ordinary aspects of relationships, akin to other forms of willing compromises between partners. Other researchers problematize unwanted sexual experiences, framing them in terms of gender inequalities and detrimental effects. In the current study, we were interested in how young women themselves characterized their unwanted sexual experiences and whether these accounts varied according to a woman’s social location. We interviewed 41 young women (18–22 years old) from three groups: affluent undergraduates, low-income undergraduates, and low-income nonstudents. Almost all of the affluent undergraduates framed their unwanted sexual experiences in normalizing terms, representing such events as relatively harmless incidents and outgrowths of developmental experimentation. In contrast, the low-income students and nonstudents both articulated more ambivalent positions and were more inclined to link their experience to sources of vulnerability, including personal adversity (e.g., trauma, social, and material insecurity) and social norms and stigma. Participants’ sexual histories, life circumstances, and standpoints at the intersection of gender and class were reflected in their experiences of unwanted sex, reinforcing that contextualized analyses and interventions are essential to advancing women’s sexual rights and well-being. Online slides for instructors who want to use this article for teaching are available on PWQ 's website at http://pwq.sagepub.com/supplemental


Proceedings ◽  
2019 ◽  
Vol 30 (1) ◽  
pp. 18
Author(s):  
Jannes Stolte ◽  
Gudrun Schwilch

As soil formation is an extremely slow process, soil can be considered a non-renewable resource. Soils should thus be adequately protected and conserved to ensure that soil functions are not lost or diminished. Soil functions are, however, threatened by a wide range of processes. Europe’s soil resources may continue to degrade due to changes in climate, land use and other human activities. The challenge is to prevent degradation and its adverse effects on soil functions and ecosystem services, and even improve the ability of soil to perform its functions. The soil degradation processes are complex and all parts of Europe are affected by one or more soil threats to some degree. There is a lack of knowledge on, a large uncertainty in, and lack of quantitative information on understanding the interrelationships between soil threats, soil threat and soil functions, and soil and ecosystem services. A major challenge in clarifying these relationships is how to integrate information and to analyse the key interactions. To bridge this gap, we have made an approach based on a review and expert knowledge to understand and describe those interrelations. This has been described in qualitative terms, and showed that the soil functions ‘biomass production’ is affected by almost all threats, whereas the threat ‘biodiversity decline’ has a major negative impact on all functions. It also showed that both soil biodiversity and soil erosion are more or less affected by almost all other soil threats. In the RECARE project, various prevention and remediation measures were trialed. Changes in manageable soil and other natural capital properties were measured and quantified, and a methodology to assess changes in ecosystem services was developed. Overall, the results showed positive on the impacts of the measures on ecosystem services. Although methodological challenges remain, the assessment served as an input to a stakeholder valuation of ecosystem services at local and sub-national levels. Although these activities are steps towards a soil remediation strategy, there is a need for further research on the mentioned issues in order to achieve an improved overview of existing information on soil degradation at the European scale, their interactions, and effects on ecosystem services. In addition, the lack of legally binding targets limits the impact that existing policies have on reducing soil threats and protecting soil function, although various EU policy instruments have shown positive impacts even in absence of binding targets for Member States.


2012 ◽  
Vol 3 (4) ◽  
pp. 40-55 ◽  
Author(s):  
Dongsong Zhang ◽  
Hsien-Ming Chou ◽  
Lina Zhou

The pervasiveness of mobile handheld devices and advancement in real-time continuous speech recognition technology has opened up a wide range of research opportunities in human-computer interaction for those devices. On the one hand, there has been an increasing amount of research on developing user-friendly speech recognition solutions and applications for mobile handheld devices. On the other hand, there are many distinct challenges in mobile speech recognition. Aiming to gain a good understanding of this emerging yet challenging area and provide a research map, this paper presents a state-of-the-art overview of this field. We will discuss three main architectures of mobile speech recognition systems, analyze their strengths and weaknesses, introduce some major research issues in the field, and highlight a number of major applications of speech recognition on handheld devices. The authors will also shed some light into important future research issues as a road map for researchers and practitioners.


2020 ◽  
Author(s):  
Adel Belharet ◽  
Urmila Bharathan ◽  
Benjamin Dzingina ◽  
Neha Madhavan ◽  
Charul Mathur ◽  
...  

Artificial intelligence and machine learning have found a wide range of business applications, but their impact is only just starting to be seen in project management.This study explores how our existing PM profession will change to be more suitable to AI inputs; and how project management will be forced to change because of the advent of AI, along with concrete, succinct and precise recommendations backed by demonstrable reasoning.


2021 ◽  
Vol 2136 (1) ◽  
pp. 012048
Author(s):  
Xuan Zhou

Abstract Speech recognition, as one of the key artificial intelligence technologies in modern development, plays an important role in any aspect. However, there are still problems in practical application, such as poor anti-interference and low degree of perfection. Therefore, this paper aims at the content of existing computer speech recognition technology, grasps fuzzy mathematical algorithm, and analyzes how to use this algorithm to better study computer speech recognition.


2019 ◽  
Vol 8 (3) ◽  
pp. 6259-6268

With the advancements in the field of artificial intelligence, speech recognition based applications are becoming more and more popular in the recent years. Researchers working in many areas including linguistics, engineering, psychology, etc. have been trying to address various aspects relating to speech recognition in different natural languages around the globe. Although many interactive speech applications in "well-resourced" major languages are being developed, uses of these applications are still limited due to language barrier. Hence, researchers have also been concentrating to design speech recognition system in various under-resourced languages. Sylheti is one of such under-resourced languages primarily spoken in the Sylhet division of Bangladesh and also spoken in the southern part of Assam, India. This paper has two contributions: i) it presents a new speech database of isolated words for the Sylheti language, and ii) it presents speech recognition systems for the Sylheti language to recognize isolated Sylheti words by applying two variants of neural network classifiers. The performances of these recognition systems are evaluated with the proposed database and the observations are presented.


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