English Speech Research Articles

Online learning system for English speech automatic recognition based on hidden Markov model algorithm and conditional random field algorithm

E-learning provides a flexible way of learning, which can provide corresponding learning content and tasks according to students’ interests, abilities and learning progress, so that students can choose learning content and learning progress more independently. In traditional teaching methods, teachers need to spend a lot of time and energy to evaluate students’ learning. The e-learning system can automatically record students’ learning behavior and learning results, and give feedback and evaluation in time during the learning process. Automatic speech recognition systems have been widely applied in various fields, and the demand for more user-friendly and convenient user operating systems is becoming increasingly urgent. This article proposes an English automatic speech recognition system based on hidden Markov model algorithm and conditional random field algorithm to improve recognition accuracy and stability, and applies it to the computer field. Label inference and optimization for speech recognition were carried out using the conditional random field algorithm. By establishing the correlation between features and labels, label inference was performed on the speech signal, which was compared with existing speech recognition systems to evaluate whether the recognition accuracy and stability of the new system had been improved. The results show that the English automatic speech recognition system based on hidden Markov model algorithm and conditional random field algorithm exhibits high performance in terms of recognition accuracy and stability. Compared with traditional speech recognition systems, this system has made significant improvements in the application of computer science.

StereoHate: Toward identifying stereotypical bias and target group in hate speech detection

Abstract Though social media helps spread knowledge more effectively, it also stimulates the propagation of online abuse and harassment, including hate speech. It is crucial to prevent hate speech since it may have serious adverse effects on both society and individuals. Therefore, it is not only important for models to detect these speeches but to also output explanations of why a given text is toxic. While plenty of research is going on to detect online hate speech in English, there is very little research on low-resource languages like Hindi and the explainability aspect of hate speech. Recent laws like the “right to explanations” of the General Data Protection Regulation have spurred research in developing interpretable models rather than only focusing on performance. Motivated by this, we create the first interpretable benchmark hate speech corpus hate speech explanation (HHES) in the Hindi language, where each hate post has its stereotypical bias and target group category. Providing descriptions of internal stereotypical bias as an explanation of hate posts makes a hate speech detection model more trustworthy. Current work proposes a commonsense-aware unified generative framework, CGenEx, by reframing the multitask problem as a text-to-text generation task. The novelty of this framework is it can solve two different categories of tasks (generation and classification) simultaneously. We establish the efficacy of our proposed model (CGenEx-fuse) on various evaluation metrics over other baselines when applied to the Hindi HHES dataset. Disclaimer The article contains profanity, an inevitable situation for the nature of the work involved. These in no way reflect the opinion of authors.

Проблемы восприятия речи с признаками иноязычного акцента в современной англоязычной коммуникации

The article is devoted to the problems of perception of foreign-accented speech in modern English-language communication. The theoretical aspects of foreign language accent typology and potential difficulties of perception are considered. The article describes the course of preparation and conduct of an experiment on the auditory perception of East Asian and European accent types in English by Russian-speaking and foreign students. The results show that the typology of foreign accent phenomena in English speech of bilinguals according to the global regional standards is objectively perceived by the participants of the perception experiment, while identifying the speaker’s nationality within these standards is likely to be problematic. The proximity of one's own accent in non-native speech to the perceived one contributes to the success of communication.

The relationship between executive function, age of L2 acquisition and speech disfluencies in bilinguals

Disfluencies signal errors in speech processes. Research in typically fluent monolinguals indicates a correlation between disfluencies and specific executive function (EF), including cognitive flexibility, inhibitory control, working memory (WM), and attention. However, these relationships have not been systematically explored in bilinguals. This study investigates the relationship between these EF components, age of language acquisition and disfluencies in bilinguals. Two types of disfluencies were examined: stalling, where articulation is delayed until the speech plan is ready, and advancing, that is, the articulation of incomplete speech plans. A total of 120 English speech samples based on simulated job interviews from 20 typically fluent adult Spanish-English bilinguals were transcribed and coded for disfluencies. The Wechsler Adult Intelligence Scale Digit span was used to measure cognitive flexibility/inhibitory control, and the Delis-Kaplan Executive Function Color-Word Interference Test was used to assess WM/attention. Findings indicate correlations between stalling disfluencies and cognitive flexibility/inhibitory control, advancing disfluencies and WM/attention, and age of acquisition and both stalling and advancing disfluencies.

A Study on Speech Recognition by a Neural Network Based on English Speech Feature Parameters

In this study, from the perspective of English speech feature parameters, two feature parameters, the mel-frequency cepstral coefficient (MFCC) and filter bank (Fbank), were selected to identify English speech. The algorithms used for recognition employed the classical back-propagation neural network (BPNN), recurrent neural network (RNN), and long short-term memory (LSTM) that were obtained by improving RNN. The three recognition algorithms were compared in the experiments, and the effects of the two feature parameters on the performance of the recognition algorithms were also compared. The LSTM model had the best identification performance among the three neural networks under different experimental environments; the neural network model using the MFCC feature parameter outperformed the neural network using the Fbank feature parameter; the LSTM model had the highest correct rate and the highest speed, while the RNN model ranked second, and the BPNN model ranked worst. The results confirm that the application of the LSTM model in combination with MFCC feature parameter extraction to English speech recognition can achieve higher speech recognition accuracy compared to other neural networks.

The Analysis of Students’ Self-Confidence in Speaking Through English Speech Training at Pondok Pesantren Modern Rahmatul Asri Enrekang

This research aims to explore the students’ self-confidence in speaking English through speech training, and to know the impacts of English speech training on students’ self-confidence. The method used in this research is a qualitative descriptive method, with interview and observation as data instruments. The subjects of this research were female students in class IX MTSS at Pondok Pesantren Modern Rahmatul Asri Enrekang, with the 10 female students as the respondents in class IX MTSS Rahmatul Asri. In this research, the researcher analyzed data by collecting, reducing, presenting data and drawing conclusions. Based on the research results, it was found that students had a good self-confidence in speaking English through English speech training, and English speech training has good impacts on students’ self-confidence development, as evidenced by the results of interview and direct observation. It can be concluded that students can train and increase their confidence in English through English speech training. Keywords: Self-confidence, Speaking, English Speech.

Argument structure and semantic role analysis of English speech act verb order

This study is qualitative descriptive research that examines the English speech act verb “order” in English. The purpose of this study is to analyse the argument structure and its role in semantics. The type of data used in this study is secondary data sourced from the Corpus of Contemporary American English (COCA). The research instrument utilized in this study is a human instrument supported by hardware such as a computer, along with software such as Microsoft Word and Microsoft Excel, as well as note-taking tools like pen and paper. Data for this study was collected using the corpus linguistics method and observation methods with note-taking techniques. The data were analysed by using the macro role theory by van Vallin & Lapolla (1997). The study results indicate that the verb "order" can have two arguments, the actor argument and the undergoer argument, and each argument can have its semantic role. The actor argument can entail the semantic role of the agent, while the undergoer argument can entail the semantic role of the theme.

THE ROLE OF L1 PROSODY IN L2 VOWEL DURATION PRODUCTION: EVIDENCE FROM ASIAN LEARNERS OF ENGLISH

The pre-fortis clipping pattern refers to vowels being shorter before voiceless consonants compared to vowels before voiced consonants. This study examined whether first-language (L1) prosodic properties affect the production of this vowel duration pattern in second-language (L2) English speech. Native speakers of Mandarin Chinese, Vietnamese, Korean, and Japanese with varying English proficiency participated in a production experiment. Results showed that while speakers exhibited some pre-fortis clipping, there were no significant vowel lengthening patterns. Additional analysis revealed subtle differences based on the L1 prosody type. Native Mandarin and Vietnamese speakers, with lexical tone, had similar duration ratios. However, native Korean speakers, with no tone, showed less distinction in vowel duration by consonant voicing. Japanese speakers, with pitch accents, fell in the middle. The findings provide limited evidence that L1 prosody affects L2 vowel duration production. The results have implications for theories of L2 speech acquisition as well as pedagogical techniques when teaching English vowels.<p> </p><p><strong> Article visualizations:</strong></p><p><img src="/-counters-/soc/0711/a.php" alt="Hit counter" /></p>

Changes in the Syntactic Structure in English-Arabic Simultaneous Interpreting

Simultaneous interpreting represents a challenge for interpreters working between typologically distinct languages, like the English-Arabic language pair. The present study is conducted to explore transfers in passive voice verbs between English as the source language and Arabic as the target language in a corpus of an interpreted English speech and its corresponding Arabic counterpart. A mixed qualitative and quantitative approach is adopted in the present study to identify recurrences of passive voice verbs and to explore the ways of rendering them into Arabic. Translation shifts are identified according to Catford’s (1965) approach. The findings of the present study reveal that nearly half of the passive voice verbs found in the source text are rendered using active voice verbs in the target text. The findings also reveal that there are four other ways of rendering passive voice verbs, including using a noun phrase, omitting a part of a sentence or a sentence as a whole, using a noun, or maintaining the passive voice form of the source verb in the target sentence. The present study contributes to promoting practices that enrich the field of English-Arabic simultaneous interpreting. It also contributes to enriching the research domain with its findings that hold special significance as the passive voice verbs constitute a divergence point between the two languages.

The Texts Flow Structure of students' English speech Performance in the Seminar Course on ELT (Anthropolinguiistics approach)

The purpose of this paper is to describe (1) what are the text flow structures of the of students' English speech performance and (2) what is the non-text flow structure of the students' English speech performance in the Seminar on ELT course. Methods: This study was observed using an anthropolinguistic approach using analytical parameters, namely interconnection, valuability, and sustainability. A qualitative paradigm with an ethnographic model is used in this study by applying twelve steps both in interview and observation methods. Findings: The text flow structure of the of students' English speech performance has three important patterns, namely the introduction, body, and conclusion. It has the smallest elements called substructure. The substructure, there are greeting, question, and declarative sentences found in introduction. The substructure, there are transitional speech, guess, question, declarative, and explanatory sentences found in closing, and greeting closing found in closing part. In the non-text flow structure of the students' English speech performance found co-text and context elements, they are cultural, social, situational, and ideological contexts. In co-text found kinesics and prosemics. Conclusions: The text flow structure is the basic framework of a text in forming a coherent whole. The text and non-text flow structure is related to the text framework which is arranged regularly from beginning to end starting with the introduction into the conclusion. Both the text and non-text flow structures are very necessary to improve students’ ability to communicate well and creatively.

Impact of Japanese L1 Rhythm on English L2 Speech.

The study aimed to examine whether L1 speech rhythm affects L2 speech by assessing how the speech rhythm of Japanese L2 English speakers differed from native speakers. We chose Japanese and English because they differ markedly in the phonological properties that likely contribute to speech rhythm. Speech rhythm was measured by the variability of vowel and consonant intervals using rate-normalized rhythm metrics (VarcoV and VarcoC; nPVI-V and nPVI-C) and %V. The study utilized recordings of spoken sentences in English by 10 native Australian English speakers; and in English and also in Japanese by 10 native Japanese speakers (who had limited experience in speaking English). Experiment 1 compared the rhythm of L1 English (by measuring 1,750 vowels and 3,093 consonants from 20 sentences) and L1 Japanese (1,923 vowels and 2,097 consonants from 10 sentences). The results showed that for all measures, Japanese had reduced durational variability in both consonant and vowel intervals compared with English. In Experiment 2, we examined the rhythm characteristics of L1 and L2 English using 40 sentences (including the 20 in Experiment 1). The results showed that vowel and consonant intervals were less variable in L2 (Japanese English) than in L1 (Australian English) speech, mirroring the results of Experiment 1. Overall, the results are consistent with the proposal that L1 (Japanese) speech rhythm influenced L2 (English) speech.

ASPECTS OF RAPID SPEECH IN NONSTANDARD POOR ENGLISH SPEECH FORMS: A SOCIO-PHONETIC APPROACH

This paper investigates the socio-phonetic features of English rapid speech, focusing on how non-native speakers—like Nadia Murad—manage these features in high-stakes situations like her speech at the White House. Rapid speech usually involves changes like assimilation, elision, and the use of linking and intrusive sounds, which can be difficult for non-native speakers to understand and produce. The paper uses a qualitative methodology and focuses on socio-phonetic analysis to determine how Murad's speech differs from the norms of native speech. Murad's English communication may be less natural and fluid because, according to preliminary findings, her speech shows less phonological blending typical of native speech patterns. This work attempts to improve our knowledge of the way rapid speech affects non-native speakers and tries to provide information on phonetic training that can improve their ability to communicate effectively.

THE USE OF ENGLISH SPEECHES CHANNEL IN IMPROVING STUDENTS' LISTENING COMPREHENSION

This research aimed to find out whether English speeches channel improve the students’ listening comprehension at eleven grade in SMAN 1 Gowa. This research used quantitative method in type of pre-experimental research. The data was collected through pre-test, treatment and post-test. The population were the students of SMAN 1 Gowa and the sample were the X MIPA 4 in SMAN 1 Gowa. The sampling technique used in this research was purposive sampling technique.The research findings showed that the students’ scoring achievement before and after using English Speeches Channel was significantly different. The students’ pre-test mean score in terms of accuracy (Answering properly and correctly) was 63, 33 to be 80, 00 in post-test with 26, 46% improvement. Then, the mean score in terms of listening in specific information was 64, 44 to be 80, 28 in post-test with 24, 58% improvement. The t-test analysis showed that Sig. (2-tailed) is 0.000 which is smaller than α = 0.05. It means that there was a significant difference of students listening comprehension before and after using English Speeches Channel. Based on the findings, it can be concluded that English Speeches Channel was effective to improve students’ listening comprehension at the ten Grade of SMAN 1 Gowa in the Academic Year 2022/2023.

Using Speech Recognition Algorithms to Improve Listening Training in College English Listening Instruction

English listening proficiency plays a crucial role in language learning and communication. Speech recognition algorithms can significantly enhance listening training in college English instruction by providing personalized and interactive learning experiences. These algorithms can transcribe spoken English passages, allowing students to receive immediate feedback on their comprehension and pronunciation. Additionally, they can generate exercises tailored to individual proficiency levels, offering targeted practice in areas needing improvement. Incorporating speech recognition technology into listening instruction not only promotes active engagement but also enables instructors to track students' progress more effectively. This paper proposed a novel approach leveraging Generative Adversarial Networks (GANs) within an Optimized Edge Computing (OEC) framework to enhance College English Listening Instruction through speech recognition. Traditional methods for English listening instruction often face challenges in providing authentic and personalized learning experiences. To address these limitations, we harness the power of GANs to generate synthetic speech data that closely resembles real-world English speech patterns. By integrating GANs with OEC, we achieve efficient processing of speech data at the edge, minimizing latency and bandwidth consumption while ensuring real-time feedback and interaction. Through extensive experimentation and analysis, demonstrate the superiority of our GAN-OEC framework over traditional baseline models and other speech recognition algorithms. Results demonstrated that the proposed model achieves an average accuracy of 90.6%, a fluency score of 8.5 out of 10, and a pronunciation accuracy of 84.6%. These results highlight the transformative potential of GAN-OEC in revolutionizing English instruction and language learning outcomes in educational settings.

Research on the Effect of Introducing Speeches in English Classes on Improving Oral English Ability under the Background of Digital Teaching

This study investigates how classroom speech training can boost English speaking skills within digital teaching contexts. It reveals that incorporating the ISAS teaching method with English speech training in vocational college courses can significantly enhance students' communication skills, particularly in oral expression. The research employed various methods to demonstrate that classroom speeches effectively elevate students' English speaking proficiency, diversify teaching content and methods, and foster innovation in English speaking education at vocational colleges. Integrating teaching materials with topics relevant to the software field, along with using a range of expressive forms and techniques, aids in broadening students' perspectives, making English classes more practical and engaging, and bolstering their English application skills and professional competencies. The study also highlights the crucial role of teachers' instructional abilities and personal qualities in enriching students' English learning and skill development. It suggests that teachers integrate more speech-focused activities into regular instruction to advance students' comprehensive English capabilities.

The moderating role of L2 proficiency in the predictive power of L1 fluency on L2 utterance fluency

The current study examined the extent to which first language (L1) utterance fluency measures can predict second language (L2) fluency and how L2 proficiency moderates the relationship between L1 and L2 fluency. A total of 104 Japanese-speaking learners of English completed different argumentative speech tasks in their L1 and L2. Their speaking performance was analysed using measures of speed, breakdown, and repair fluency. L2 proficiency was operationalised as cognitive fluency. Two factor scores of cognitive fluency—linguistic resources and processing speed—were computed based on performance in a set of linguistic knowledge tests capturing vocabulary knowledge, morphosyntactic processing, and articulatory skills. A series of generalised linear mixed-effects models revealed small-to-moderate effect sizes for the predictive power of L1 utterance fluency measures on their L2 counterparts. Moderator effects of L2 proficiency were found only in speed fluency measures. The relationship between L1 and L2 speed fluency was weaker for L2 learners with wider L2 linguistic resources. Conversely, for those with faster L2 processing speed, the L1-L2 link tended to be stronger. These findings indicate that the L1-L2 fluency link is subject to the complex interplay of phonological differences between learners’ L1 and L2 and their L2 proficiency, offering implications for diagnostic speaking assessment.

İNGİLİS DİLİNDƏ OXUNUN NÖVLƏRİ VƏ ONLARIN TƏDRİSİ

Types of Reading and their Teaching in English Summary The development of reading skills in students plays an important role in the process of mastering the English language, because it is one of the foundations on which literate speech in English is built. It is important that reading instruction is based on teaching new ways of thinking and understanding about reading texts to students who master English as a foreign language. The main goal of the process of teaching reading and its types in English is to acquire important skills such as acquiring information in the language being taught and enriching motivational ideas and concepts. To achieve this goal, different types of reading in English classes should be properly implemented by teachers and the teaching of reading should help students acquire literary skills in English and new ways of thinking about texts. In this article, reading in English and its types, their correct implementation by teachers in classes, etc. issues are discussed. The article also talks about the tasks aimed at developing students' reading and comprehension skills, types of reading such as intensive reading, extensive reading, reading aloud, analytical reading and fluent reading, their implementation methods in English classes, and their theoretical and practical basis. Key words: reading, skills, types of reading, extensive reading, intensive reading, reading aloud, fluent reading, analytic reading, strategies

ƏVƏZLİK NİTQ HİSSƏSİ KİMİ AZƏRBAYCAN VƏ İNGİLİS DİLLƏRİ İLƏ MÜQAYİSƏLİ MÜSTƏVİDƏ

Pronoun as a Part of Speech in Azerbaijani and English on a Comparative Level Summary The article deals with the study of the reflexive voice in the English language. Considering the problem of the voice from the point of view of morphology, the author makes out if the combination “the verb+reflexive pronoun” is the from of the reflexive voice; from syntactical point of view if the mentioned combination is a single syntactical unit or a reflexive pronoun has an independent syntactical function in the sentence. Key Word: English language, personal, relative, relative, interrogative, reflexive pronouns

Influence of Talker and Accent Variability on Rapid Adaptation and Generalization to Non-Native Accented Speech in Younger and Older Adults

ABSTRACT Listeners can rapidly adapt to English speech produced by non-native speakers of English with unfamiliar accents. Prior work has shown that the type and number of talkers contained within a stimulus set may impact rate and magnitude of learning, as well as any generalization of learning. However, findings across the literature have been inconsistent, with relatively little study of these effects in populations of older listeners. In this study, adaptation and generalization to unfamiliar talkers with familiar and unfamiliar accents are studied in younger normal-hearing adults and older adults with and without hearing loss. Rate and magnitude of adaptation are modeled using both generalized linear mixed-effects regression and generalized additive mixed-effects modeling. Rate and magnitude of adaptation were not impacted by increasing the number of talkers and/or varying the consistency of non-native English accents across talkers. Increasing the number of talkers did strengthen generalization of learning for a talker with a familiar non-native accent, but not for an unfamiliar accent. Aging alone did not diminish adaptation or generalization. These findings support prior evidence of a limited benefit for talker variability in facilitating generalization of learning for non-native accented speech, and extend the findings to older adults.

Automatic speaker and age identification of children from raw speech using sincNet over ERB scale

This paper presents the newly developed non-native children’s English speech (NNCES) corpus to reveal the findings of automatic speaker and age recognition from raw speech. Convolutional neural networks (CNN), which have the ability to learn low-level speech representations, can be fed directly with raw speech signals instead of using traditional hand-crafted features. Moreover, the filters that were learned using standard CNNs appeared to be noisy because they consider all elements of each filter. In contrast, sincNet can be able to generate more meaningful filters simply by replacing the first convolutional layer by a sinc-layer in standard CNNs. The low and high cutoff frequencies of the rectangular band-pass filter are the only parameters that can be learned in sincNet, which has the potential to extract significant speech cues from the speaker, such as pitch and formants. In this work, the sincNet model is significantly changed by switching from baseline Mel scale initializations to equivalent rectangular bandwidth (ERB) initializations, which has the added benefit of allocating additional filters in the lower region of the spectrum. Additionally, it needs to be highlighted that the novel sincNet model is well suited to identify the age of the children. The investigations on both read and spontaneous speech tasks in speaker identification, gender independent & dependent age-group identification of children outperform the baseline models with varying relative improvements in terms of accuracy.