Statistical analysis of Hindi BTEC speech database

Arora, Sunita; Arora, Krishan; Aggarwal, Swati

doi:10.1109/icsda.2012.6422480

Cited by 4 publications

(3 citation statements)

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“…We captured the TLS handshakes generated by the four most popular browsers: Chrome, Safari, Internet Explorer, and Firefox [57]. To account for older versions, differing operating systems, and varying mobile hardware, we generated and captured handshakes in different environments using BrowserStack [4], a cloud service that provides developers with a variety of virtual machines for testing websites. 2 We analyzed the non-ephemeral parameters advertised in the TLS handshakes, finding that each browser family selects a unique set of options, and that these options differ from those used by both common libraries (e.g., OpenSSL) and popular interception products.…”

Section: A Web Browsersmentioning

confidence: 99%

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The Security Impact of HTTPS Interception

Durumeric

Springall

et al. 2017

Proceedings 2017 Network and Distributed System Security Symposium

122

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As HTTPS deployment grows, middlebox and antivirus products are increasingly intercepting TLS connections to retain visibility into network traffic. In this work, we present a comprehensive study on the prevalence and impact of HTTPS interception. First, we show that web servers can detect interception by identifying a mismatch between the HTTP User-Agent header and TLS client behavior. We characterize the TLS handshakes of major browsers and popular interception products, which we use to build a set of heuristics to detect interception and identify the responsible product. We deploy these heuristics at three large network providers: (1) Mozilla Firefox update servers, (2) a set of popular e-commerce sites, and (3) the Cloudflare content distribution network. We find more than an order of magnitude more interception than previously estimated and with dramatic impact on connection security. To understand why security suffers, we investigate popular middleboxes and clientside security software, finding that nearly all reduce connection security and many introduce severe vulnerabilities. Drawing on our measurements, we conclude with a discussion on recent proposals to safely monitor HTTPS and recommendations for the security community. Permission to freely reproduce all or part of this paper for noncommercial purposes is granted provided that copies bear this notice and the full citation on the first page. Reproduction for commercial purposes is strictly prohibited without the prior written consent of the Internet Society, the first-named author (for reproduction of an entire paper only), and the author's employer if the paper was prepared within the scope of employment.

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Section: A Web Browsersmentioning

confidence: 99%

“…Products from twelve vendors inject a new root certificate and actively intercept TLS connections. 4 We list the products that intercept connections in Figure 4. 5…”

Section: B Fingerprinting Security Productsmentioning

confidence: 99%

The Security Impact of HTTPS Interception

Durumeric

Springall

et al. 2017

Proceedings 2017 Network and Distributed System Security Symposium

122

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“…much likely to be spoken by tourists travelling to other countries. In prior works, the corpus has been quantitatively evaluated and statistically analyzed in languages like Japanese [2] and Hindi [3]. The statistical analysis presented in this paper, is carried out on the Bengali translated version of the BTEC and is being reported for the first time.…”

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confidence: 99%

Bengali Basic Travel Expression Corpus: A statistical analysis

Khan

Basu

et al. 2014

2014 17th Oriental Chapter of the International Committee for the Co-Ordination and Standardization of Speech Databases and Ass

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The Japanese-English aligned Basic Travel Expression Corpus (BTEC) has been used as a basic dataset for development of real-world Speech-to-Speech Translation (S2ST) systems in related prior studies. This paper presents a detailed statistical analysis on the Bengali translated BTEC text and its phonetic transcriptions for development of English-Bengali speech translation applications in travel domain. In different level of analysis hierarchy, the study focuses on the lexical and phonetical status of the analyzed corpus based on frequency spectrums, estimated population size, coverage ratio, goodness of fit of Large Number of Rare Events (LNRE) model and transition patterns . The experimental observations provide necessary insights on sufficiency of the analyzed corpus with respect to the travel domain as well as for building basic components of English-Bengali S2ST system.The Universal Speech Translation Advanced Research (U ST AR) Consortium is an international research consortium comprised of 29 institutes from 23 countries (as of June, 2014) across the world. It provides a uniform framework for pursuing collaborative research; sharing resources and developing infrastructures and resources for building web based speech-to speech translation (S2ST) applications in English to native languages of the respective participating institutes. Under the same framework, since 2014, Centre for Development of Advanced Computing, Kolkata (in India) is developing resources and components required for English to Bengali speech translation focusing on the travel domain. As the prime common dataset to build the language specific components of cross language S2ST applications under U-ST AR framework, the Basic Travel Expression Corpus (BTEC) has been used and translated into several native languages by the respective member institutes.As reported in earlier studies, the BTEC, developed by Advanced Telecommunication Research (ATR) laboratory, Japan, is an English-Japanese aligned corpus [1,2]. It is qualitatively well-examined, consistent and having wide coverage of travel and tourism related basic expressions. These expressions are highly oriented towards real world conversations on various topics like transportation, travel activities, sight-seeing, shopping, dining, staying, asking help in trouble, basic queries, greetings etc. much likely to be spoken by tourists travelling to other countries. In prior works, the corpus has been quantitatively evaluated and statistically analyzed in languages like Japanese [2] and Hindi [3]. The statistical analysis presented in this paper, is carried out on the Bengali translated version of the BTEC and is being reported for the first time. To introduce Bengali language, it is good to mention here that Bengali belongs to the eastern Indo-Aryan branch of the Indo-European family of languages. It is the official state language of East Indian state West Bengal and the national language of Bangladesh. As per Wiki, it is one of the most spoken languages, ranked seventh in world. II. PREPARING B EN...

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