CC BY
0SCIENCE SHINE
INTERNATIONAL SCIENTIFIC JOURNAL
THE ROLE OF ARTIFICIAL INTELLIGENCE TECHNOLOGY IN IMPROVING SPEAKING SKILLS
Abdugaffarova Arofat Shamsiddinovna
arofatabdugaffarova9071 @gmail.com
Abstract: This article provides data about how artificial intelligence improves speaking skills. It offers several benefits of Artificial Intelligence (AI) in improving speaking ability such as personalized learning experiences, Natural language processing, real-time feedback on fluency and pronunciation, Speech Therapy, and Confidence Building. Moreover, answers questions about why AI is important in improving speaking skills.
Keywords: AI, personalized learning, interactive, error correction, chatbots, Speech Therapy, confidence Building, Natural language processing.
Introduction. In today's globalized world, the ability to communicate effectively is more important than ever. Whether for personal growth, professional success, or academic achievement, strong speaking skills can open many doors. However, improving these skills can be a challenge for many individuals, especially when consistent practice and personalized feedback are hard to come by. Artificial Intelligence (AI) is stepping in to revolutionize this area, offering innovative tools to help people improve their speaking abilities more efficiently than traditional methods.
Research methods. In this article use a mixed-methods approach, incorporating both qualitative and quantitative data collection techniques to evaluate the effectiveness of AI technology in improving speaking skills. This approach allows for a comprehensive understanding of how AI impacts language learning and the learner's experience.
SCIENCE SHINE
INTERNATIONAL SCIENTIFIC JOURNAL
Results and discussion. One of the most significant ways AI improves speaking skills is by offering personalized learning experiences. Traditional language learning programs and speaking practice tools often adopt a one-size-fits-all approach. AI, on the other hand, can tailor lessons based on the learner's individual needs. It can analyze a user's strengths, weaknesses, and progress, and then suggest targeted exercises to address specific areas. For example, if someone struggles with pronunciation, AI-based systems can identify the problematic sounds and provide focused practice on those.
Natural Language Processing (NLP) In our increasingly digital world, the ability for machines to understand and interact with human language is becoming more crucial than ever. Natural Language Processing (NLP), a field that lies at the intersection of artificial intelligence, linguistics, and computer science, empowers machines to process, analyze, and respond to human language in a meaningful way. From chatbots and voice assistants to automated translation services, NLP is reshaping the way we interact with technology. Natural Language Processing (NLP) is a branch of artificial intelligence focused on enabling computers to understand, interpret, and generate human language. The primary goal of NLP is to bridge the gap between human communication and computer understanding by teaching machines how to interpret the complexities of natural languages—complete with their ambiguities, contextual nuances, and cultural influences. Human languages are incredibly complex, with words often having multiple meanings depending on the context, diverse grammatical structures, and idiomatic expressions. NLP seeks to overcome these challenges by employing a range of techniques to decipher the meaning behind text or speech.
Despite its many successes, NLP faces several challenges that make it difficult for machines to fully replicate human language understanding:
SCIENCE SHINE
INTERNATIONAL SCIENTIFIC JOURNAL
• Ambiguity: Human languages are often ambiguous. A single word can have multiple meanings, and context is key to understanding which meaning is intended.
• Context Understanding: Machines find it difficult to grasp the broader context that might be apparent to a human reader. Sarcasm, irony, and cultural references can be particularly challenging to interpret accurately.
• Complex Grammar: Natural languages are often inconsistent, with irregular rules and numerous exceptions. Making sense of complex sentence structures requires sophisticated algorithms.
• Multilingual Processing: The diversity of languages around the world adds another layer of complexity. NLP models must be trained to understand not only different languages but also dialects, slang, and idiomatic expressions that vary by region.
Recent advances in NLP have been driven by deep learning and transformer-based architectures. Technologies like BERT (Bidirectional Encoder Representations from Transformers) and GPT (Generative Pre-trained Transformer) have significantly improved language understanding and generation capabilities. These models can handle more complex language tasks, understand the context better, and generate more human-like responses. The rise of large language models like GPT-4 has also enabled sophisticated text generation, allowing machines to create articles, answer questions, and engage in more nuanced dialogue. These models learn by analyzing vast amounts of text data, enabling them to understand the subtleties of human language and produce coherent, contextually appropriate responses.
The future of NLP looks promising as researchers continue to overcome existing challenges and improve machine understanding of language. The development of multimodal NLP-which integrates text, images, and even sounds—will help machines better understand the context and meaning behind communication. Additionally, efforts to build more inclusive NLP models that support underrepresented languages
SCIENCE SHINE
INTERNATIONAL SCIENTIFIC JOURNAL
and dialects will be crucial in making AI accessible globally. Another focus will be on ethical considerations, ensuring that NLP systems are transparent and unbiased, and respecting users' privacy. This is crucial as these technologies become more integrated into our daily lives. Natural Language Processing is a powerful technology that is changing how humans interact with machines. From chatbots to translation services, NLP has applications in nearly every aspect of our digital interactions. Despite the challenges it faces, continued advancements in this field are making machines increasingly proficient in understanding and generating human language. As NLP becomes more sophisticated, we can expect even more intuitive, effective, and meaningful interactions between humans and machines, ultimately making technology more accessible and responsive to our needs.
Real-Time Feedback on Pronunciation and Fluency. Learning a new language often comes with its own set of challenges, especially when it comes to speaking clearly and fluently. For many learners, improving pronunciation and fluency requires practice, repetition, and corrective feedback-elements that are often difficult to obtain without consistent access to native speakers or skilled instructors. Fortunately, advances in Artificial Intelligence (AI) have made it possible to provide real-time feedback on pronunciation and fluency, giving language learners an effective and accessible way to enhance their speaking skills.
AI technologies use a combination of speech recognition, natural language processing (NLP), and machine learning to analyze and evaluate a learner's speech in real-time. This technology allows AI to convert spoken language into text. AI applications listen to a user's voice, transcribing spoken words while paying attention to pronunciation, pitch, intonation, and speed. NLP helps AI systems understand the context of what is being said. It helps in identifying the correct meaning, even if the learner mispronounces words, making the evaluation more comprehensive. AI compares the learner's pronunciation with that of native speakers, identifying
SCIENCE SHINE
INTERNATIONAL SCIENTIFIC JOURNAL
discrepancies. Machine learning algorithms are trained with thousands of voice samples, allowing the system to detect subtle deviations in pronunciation and provide specific feedback. AI evaluates aspects like speaking pace, pauses, and rhythm to determine a learner's fluency. It measures whether a speaker sounds natural or stilted, providing insights into areas where improvements are needed.
AI's real-time feedback on pronunciation and fluency is transforming language education. Here are some key ways it is being utilized:
1. Language Learning Apps and Platforms. Language learning apps like ELSA Speak, Rosetta Stone, and Duolingo are leveraging AI to provide real-time corrections and guidance. For instance, ELSA Speak uses AI to analyze pronunciation and offers detailed feedback on individual sounds, stress patterns, and intonation. Learners can practice phrases, receive instant corrections, and repeat until they master specific sounds.
2. Virtual Tutors. Virtual tutors powered by AI can simulate conversations in real-life contexts, such as ordering food at a restaurant or making travel arrangements. These tutors provide instant feedback on how naturally a learner is speaking. By highlighting errors in pronunciation or identifying unnatural pauses, virtual tutors help learners improve their overall speaking fluency in practical situations.
3. Speech Therapy and Accent Reduction. AI-based tools are also being used in speech therapy to help individuals improve their pronunciation and overcome speech disorders. Accent reduction programs use AI to compare learners' speech with native speakers, identifying subtle pronunciation differences that may contribute to a heavy accent. By focusing on these differences, learners can work towards clearer and more native-like pronunciation.
Speech Therapy and Confidence Building. AI technology is also making strides in areas like speech therapy. For individuals with speech impediments or other
SCIENCE SHINE
INTERNATIONAL SCIENTIFIC JOURNAL
communication challenges, AI tools can offer structured, consistent practice and personalized therapy plans. Systems like Speech Blubs and other AI-powered speech apps analyze speech patterns and suggest exercises to help users overcome difficulties. These tools provide a low-pressure environment where individuals can practice without the fear of judgment, making the process of overcoming speech challenges more approachable and effective.
In addition to technical feedback, many AI-driven platforms are designed to boost a speaker's confidence. Public speaking apps like Orai use AI to track key metrics such as pacing, filler word usage, and audience engagement. With consistent practice, users can gradually become more confident speakers, better equipped to engage an audience.
Enhancing Language Learning and Cultural Nuances. AI is also instrumental in improving speaking skills by exposing learners to different languages and cultural contexts. For example, AI-driven language learning platforms like Duolingo and Babbel offer interactive speaking exercises that mimic real-world conversations, helping learners practice speaking in different scenarios. AI algorithms can simulate various accents, dialects, and cultural nuances, which enables learners to become more adaptable speakers, prepared to interact with people from diverse backgrounds. Additionally, AI-based virtual assistants like Siri, Alexa, and Google Assistant provide users with opportunities to practice conversational speaking. Though not specifically designed for language learning, these AI assistants can help learners practice speaking in real-world situations, improving their fluency and conversational skills in the process.
AI in Professional and Academic Speaking. In the professional world, AI tools are helping individuals refine their speaking abilities to succeed in business, leadership, and academic settings. Many professionals need to present ideas clearly and persuasively, whether in board meetings, conferences, or job interviews. AI-
SCIENCE SHINE
INTERNATIONAL SCIENTIFIC JOURNAL
based public speaking apps, like Yoodli, offer features like speech evaluation and mock presentation feedback. These tools assess the speaker's clarity, persuasiveness, and ability to connect with an audience, allowing professionals to refine their delivery. For students, AI-driven tools like presentation feedback software and debate platforms can help improve public speaking skills. By tracking performance metrics and offering suggestions for improvement, AI ensures students are well-prepared for oral exams, presentations, and other speaking engagements.
Conclusion
AI technology is pivotal in transforming how people improve their speaking skills. Through personalized learning, real-time feedback, and tools designed for specific challenges like pronunciation or speech therapy, AI is making it easier for individuals to become effective communicators. As AI continues to evolve, it will offer even more advanced solutions, ensuring that everyone—whether learning a new language, improving public speaking, or overcoming speech challenges benefit from cutting-edge, accessible tools to enhance their speaking abilities.
References:
1. Amin, M. Y. M. (2023). AI and Chat GPT in Language Teaching: Enhancing EFL classroom support and transforming assessment techniques. International Journal of Higher Education Pedagogies, 4(4), 1-15. https://doi.org/10.33422/ijhep.v4i4.554
2. Annamalai, N., Rashid, R. A., Hashmi, U. M., Mohamed, M., Alqaryouti, M. H. & Sadeq, A. E. (2023). Using chatbots for English language learning in higher education. Computers & Higher Education: Artificial Intelligence 5. https://doi.org/10.1016/i. caeai.2023.100153
m
SCIENCE SHINE
INTERNATIONAL SCIENTIFIC JOURNAL
3. Qakmak, F. (2022). Chatbot-human interaction and its effects on EFL pupils' L2 speaking performance and anxiety. Novitas-ROYAL (Research on Youth and Language), 16(2), 113-131.
4. Candelon, F., Krayer, L., Saran Rajendran, R. & Zuluaga Martinez, D. (2023). How people can create - and destroy - value with generative AI. Available at: https://www.bcg.com/publications/2023/ how people-create-and-destroy-value-with-gen-ai
5. Chen, C.-H., Koong, C.-S. & Liao, C. (2022). Influences of integrating dynamic assessment into a speech recognition learning design to support pupils' English speaking skills, learning anxiety and cognitive load. Educational Technology & Society, 25(1), 1-14.
6. Chen, Y.-L., Hsu, C.-C., Lin, C.-Y. & Hsu, H.-H. (2022). Robot-assisted language learning: Integrating artificial intelligence and virtual reality into English tour guide practice. Education Sciences, 12, 437. https://doi.org/10.3390/educsci12070437
7. Chon, Y. V., Shin, D. & Kim, G. E. (2021). Comparing L2 learners' writing against parallel machine-translated texts: Raters' assessment, linguistic complexity and errors. System, 96, 102408. https://doi.org/10.1016/j. system.2020.102408
8. Chu, S-T., Hwang, G-J., Chien, S-Y., & Chang, S-C. (2023). Incorporating teacher intelligence into digital games: An expert system-guided self-regulated learning approach to promoting EFL students'.
