• Asia Pacific Journal of Corpus Research
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• v.2 no.2
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• pp.1-15
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• 2021

The study aims to explore the use of metadiscourse in the Bank Negara Malaysia Governor's speeches based on Hyland's Interpersonal Model of Metadiscourse. The corpus data consist of 343 speech texts, which were extracted from the Malaysian Corpus of Financial English (MacFE), amounting to 688,778 tokens. Adopting both quantitative and qualitative approaches to data analysis the study investigates (1) the overall use of metadiscourse in the Bank Negara Governor's speech texts and (2) the functions of the most prominent metadiscourse resources used and their functions in the speech texts. The findings reveal that the Governor's speech texts to be interactional rather than interactive, revealing a rich distribution of interactional metadiscourse resources, namely engagement markers, self-mention, hedges, boosters and attitude markers throughout the texts. The interactional metadiscourse resources function to establish speaker-audience engagement and alignment of views, as well as to express degree of uncertainty and certainty and attitudes. The study concludes that the speech texts are not merely informational or propositional, but rather interpersonal.

• English Language & Literature Teaching
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• v.15 no.3
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• pp.151-170
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• 2009

Recently speech texts have been increasingly used for English education because of their various advantages as language teaching and learning materials. The purpose of this paper is to analyze speech texts in a corpus-based lexical approach, and suggest some productive methods which utilize English speaking or writing as the main resource for the course, along with introducing the actual classroom adaptations. First, this study shows that a speech corpus has some unique features such as different selections of pronouns, nouns, and lexical chunks in comparison to a general corpus. Next, from a collocational perspective, the study demonstrates that the speech corpus consists of a wide variety of collocations and lexical chunks which a number of linguists describe (Lewis, 1997; McCarthy, 1990; Willis, 1990). In other words, the speech corpus suggests that speech texts not only have considerable lexical potential that could be exploited to facilitate chunk-learning, but also that learners are not very likely to unlock this potential autonomously. Based on this result, teachers can develop a learners' corpus and use it by chunking the speech text. This new approach of adapting speech samples as important materials for college students' speaking or writing ability should be implemented as shown in samplers. Finally, to foster learner's productive skills more communicatively, a few practical suggestions are made such as chunking and windowing chunks of speech and presentation, and the pedagogical implications are discussed.

• International Journal of Computer Science & Network Security
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• v.24 no.2
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• pp.25-30
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• 2024

Various new technologies and aiding instruments are always being introduced for the betterment of the challenged. This project focuses on aiding the mute in expressing their views and ideas in a much efficient and effective manner thereby creating their own place in this world. The proposed system focuses on using various gestures traced into texts which could in turn be transformed into speech. The gesture identification and mapping is performed by the Kinect device, which is found to cost effective and reliable. A suitable text to speech convertor is used to translate the texts generated from Kinect into a speech. The proposed system though cannot be applied to man-to-man conversation owing to the hardware complexities, but could find itself very much of use under addressing environments such as auditoriums, classrooms, etc

• Phonetics and Speech Sciences
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• v.9 no.3
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• pp.41-47
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• 2017

The purpose of this study is to examine how speakers use VOT and f0 to distinguish tense, lax, and aspirated stops in isolated sentence reading and paragraph readings. To do so, a total of 20 males between the ages of 20-25 years old were asked to read (1) isolated sentences, (2) information-oriented text and (3) emotional expressive texts in which the stop pronunciation's VOT value and f0 were measured thereafter. The main results are as follows. In the isolate sentence reading, lax stops, and aspirated stops were distinguished by both VOT and f0, but for the Korean men that read reading texts, VOT is not a cue to distinguish between lax and aspirated stops. In general, the VOT differences between lax stops and aspirated stops were smaller for information-oriented texts and emotional expressive texts than that of the isolate sentence reading. In the paragraph reading that induces a natural utterance, the f0 dependence is greater for the distinction between lax and aspirated stops.

• MALSORI
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• no.46
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• pp.51-64
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• 2003

In order to produce high quality synthesized speech, it is very important to get an accurate grapheme-to-phoneme conversion and prosody model from texts using natural language processing. Robust preprocessing for non-Korean characters should also be required. In this paper, we analyzed Korean texts using a morphological analyzer, part-of-speech tagger and syntactic chunker. We present a new grapheme-to-phoneme conversion method for Korean using a hybrid method with a phonetic pattern dictionary and CCV (consonant vowel) LTS (letter to sound) rules, for unlimited vocabulary Korean TTS. We constructed a prosody model using a probabilistic method and decision tree-based method. The probabilistic method atone usually suffers from performance degradation due to inherent data sparseness problems. So we adopted tree-based error correction to overcome these training data limitations.

• Proceedings of the KSPS conference
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• 2003.05a
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• pp.87-90
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• 2003

In order to produce high quality synthesized speech, it is very important to get an accurate grapheme-to-phoneme conversion and prosody model from texts using natural language processing. Robust preprocessing for non-Korean characters should also be required. In this paper, we analyzed Korean texts using a morphological analyzer, part-of-speech tagger and syntactic chunker. We present a new grapheme-to-phoneme conversion method, i.e. a dictionary-based and rule-based hybrid method, for unlimited vocabulary Korean TTS. We constructed a prosody model using a probabilistic method and decision tree-based method.

• MALSORI
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• no.47
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• pp.51-72
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• 2003

The purpose of this paper is to design Speech Database for Korean pronunciation education. For this purpose, I investigated types of speech errors of Korean-learners, made texts for recording, which involves all types of speech errors, and showed how to gather speech data and how to tag their informations. It's natural that speech data should include Korean-learners' speech and Korean people's speech, because Speech DB that I try to develop is for teaching Korean pronunciation to foreigners. So this DB should have informations about speakers and phonetic informations, which are about phonetic value of segments and intonation of sentences. The intonation of sentence varies with the type of sentence, the structure of prosodic units, the length of a prosodic unit and so on. For this reason, Speech DB must involve tags about these informations.

• Phonetics and Speech Sciences
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• v.7 no.2
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• pp.149-156
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• 2015

We propose a new method for automatic fluency scoring of English speaking tests spoken by nonnative speakers in a free-talking style. The proposed method is different from the previous methods in that it does not require the transcribed texts for spoken utterances. At first, an input utterance is segmented into a phone sequence by using a phone recognizer trained by using native speech databases. For each utterance, a feature vector with 6 features is extracted by processing the segmentation results of the phone recognizer. Then, fluency score is computed by applying support vector regression (SVR) to the feature vector. The parameters of SVR are learned by using the rater scores for the utterances. In computer experiments with 3 tests taken by 48 Korean adults, we show that speech rate, phonation time ratio, and smoothed unfilled pause rate are best for fluency scoring. The correlation of between the rater score and the SVR score is shown to be 0.84, which is higher than the correlation of 0.78 among raters. Although the correlation is slightly lower than the correlation of 0.90 when the transcribed texts are given, it implies that the proposed method can be used as a preprocessing tool for fluency evaluation of speaking tests.

• Speech Sciences
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• v.7 no.2
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• pp.209-224
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• 2000

This paper proposes an automatic detection method of intonational and accentual phrases in Korean standard continuous speech. We use the pause over 150 msec for detecting intonational phrases, and extract accentual phrases from the intonational phrases by analyzing syllables and pitch contours. The speech data for the experiment are composed of seven male voices and two female voices which read the texts of the fable 'the ant and the grasshopper' and a newspaper article 'manmulsang' in normal speed and in Korean standard variation. The results of the experiment shows that the detection rate of intonational phrases is 95% on the average and that of accentual phrases is 73%. This detection rate implies that we can segment the continuous speech into smaller units(i.e. prosodic phrases) by using the prosodic information and so the objects of speech recognition can narrow down to words or phrases in continuous speech.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.5
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• pp.2588-2609
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• 2019

Speech homomorphic encryption has become one of the key components in secure speech storing in the public cloud computing. The major problem of speech homomorphic encryption is the huge data expansion of speech cipher-text. To address the issue, this paper presents a speech homomorphic encryption scheme with less data expansion, which is a probabilistic statistics and addition homomorphic cryptosystem. In the proposed scheme, the original digital speech with some random numbers selected is firstly grouped to form a series of speech matrix. Then, a proposed matrix encryption method is employed to encrypt that speech matrix. After that, mutual information in sample speech cipher-texts is reduced to limit the data expansion. Performance analysis and experimental results show that the proposed scheme is addition homomorphic, and it not only resists statistical analysis attacks but also eliminates some signal characteristics of original speech. In addition, comparing with Paillier homomorphic cryptosystem, the proposed scheme has less data expansion and lower computational complexity. Furthermore, the time consumption of the proposed scheme is almost the same on the smartphone and the PC. Thus, the proposed scheme is extremely suitable for secure speech storing in public cloud computing.