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“USING TECHNOLOGY (AI, VR OR SPEECH RECOGNITION) IN
TEACHING SPEAKING SKILLS”.
Iminova Shaxnoza Baxadirovna
English teacher at ASIFL;
Sobirov Ilhomjon
Student at ASIFL;
https://doi.org/10.5281/zenodo.15679259
Annotation.
The article looks at how emerging technologies like artificial
intelligence (AI), virtual reality (VR), and speech recognition are transforming
the way people interact with the world around them. It emphasizes the
increasing presence of AI in everyday life, from personalized assistants to
decision-making tools in healthcare and education. Meanwhile, speech
recognition is portrayed as a tool for accessibility, empowering individuals with
disabilities to communicate more freely and navigate digital environments.
Through real-world examples and expert insights, the article argues that while
these technologies present exciting opportunities, they also raise ethical and
privacy concerns that must be addressed. Ultimately, the article presents
technology not just as a tool, but as a force shaping the future of human
interaction, productivity, and society at large.
Key words:
Technology advancements, learner-centred, artificial
intelligence, pedagogical implications, effectiveness, communication skills.
Introduction.
Technological advancements are transforming the landscape
of language education, particularly in the area of speaking skills, which are
traditionally difficult to develop without immersive, real-time feedback.
Speaking involves complex cognitive processes, including pronunciation,
fluency, vocabulary usage, and interactional competence (Bygate, 2009).
Traditional classroom methods often fall short due to time constraints, limited
individual feedback, and performance anxiety. The integration of AI, VR, and
speech recognition offers new possibilities to overcome these limitations. This
article investigates how these technologies are currently being applied in
language education, focusing specifically on speaking development. It further
explores their impact on learner autonomy, motivation, and accessibility, and
discusses the challenges associated with their use.
Artificial Intelligence (AI) in Speaking Instruction.
AI-driven platforms are increasingly employed in language learning
environments. Applications such as ELSA Speak, Duolingo, and Rosetta Stone use
AI to provide real-time pronunciation feedback, adaptive lesson paths, and error
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correction. AI systems analyze phonetic patterns, intonation, and stress to assess
spoken performance and suggest improvements (Nguyen et al., 2021).
Research supports the effectiveness of AI in promoting speaking
proficiency. For example, Li and Lan (2020) found that AI-based feedback
enhanced learner accuracy and increased self-correction rates. Moreover, AI
enables personalized learning, a key principle in SLA, by adapting to the
learner’s pace, level, and learning style.
However, AI also raises concerns related to algorithmic bias and data
privacy. Inaccurate assessment of non-native accents and over-reliance on
standard pronunciation norms can discourage learners from diverse linguistic
backgrounds. Therefore, developers must ensure inclusivity in training datasets
and transparency in evaluation algorithms.
Virtual Reality (VR) and Immersive Speaking Practice.
VR offers immersive, contextualized environments for language learners to
engage in simulated conversations and role-playing scenarios. Unlike traditional
digital resources, VR engages multiple senses and allows learners to "practice"
speaking in situational contexts such as restaurants, airports, or workplaces.
Studies show that VR increases learner engagement, reduces speaking
anxiety, and improves vocabulary retention and oral fluency (Liu et al., 2022). It
is aligned with constructivist learning theory, where knowledge is built through
interaction with realistic tasks (Vygotsky, 1978). For instance, Mondly VR offers
learners real-life conversation settings with immediate feedback and task-based
speaking goals.
The main limitations of VR include high costs of hardware (headsets and
computing power), limited accessibility in lower-income regions, and the need
for teacher training. Moreover, prolonged VR use may cause cognitive overload
or discomfort (Rupp et al., 2019). These barriers must be addressed to ensure
equitable access to immersive language tools.
Speech Recognition and Pronunciation Feedback.
Speech recognition technology underlies many digital tools used for
pronunciation and fluency training. It allows learners to interact with voice-
based AI systems and receive feedback on pronunciation, rhythm, and stress
patterns. Google Speech-to-Text API, Microsoft Azure Speech Services, and
proprietary tools in apps like Babbel and Speakly are examples of this
technology in action.
According to McCrocklin (2016), speech recognition supports autonomous
learning by providing immediate, non-judgmental feedback, which reduces
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anxiety and encourages repeated practice. It also allows learners to visualize
pitch and intonation through waveform and spectrogram analysis, reinforcing
phonological awareness.
Nonetheless, challenges remain in recognizing diverse accents, managing
code-switching, and accurately interpreting prosodic variation. Instructors must
combine these tools with guided instruction to help learners interpret feedback
meaningfully and develop communicative competence beyond phonetic
accuracy.
Pedagogical Implications.
The integration of AI, VR, and speech recognition into language classrooms
reflects a shift toward blended and technology-enhanced learning models. These
tools should be used to supplement rather than replace human interaction.
Teachers play a crucial role in mediating technology use, ensuring it aligns with
curriculum goals and learner needs.
Moreover, educators must receive adequate training in both the operation
and pedagogical integration of these tools. Curriculum designers should ensure
that tasks using technology are communicative, context-rich, and learner-
centered, avoiding overly mechanical drills or rote repetition.
Conclusion.
In conclusion, AI, VR, and speech recognition technologies offer
transformative potential for teaching and learning speaking skills. They provide
personalized, immersive, and interactive opportunities for practice that are
difficult to replicate in traditional settings. However, their effectiveness depends
on thoughtful integration, ethical design, and equitable access.
Future research should explore long-term outcomes of using these tools in
diverse contexts, including their effect on learner motivation, retention, and
intercultural communication skills. As we move toward more digital learning
environments, balancing technological innovation with human pedagogy will be
critical to developing confident, competent speakers.
References:
1. Bygate, M. (2009). Teaching and testing speaking. In Long, M. H. & Doughty, C.
J. (Eds.), The Handbook of Language Teaching. Wiley-Blackwell.
2. Li, Z., & Lan, Y. J. (2020). The effectiveness of AI-based pronunciation
instruction on EFL learners' speaking skills. Computer Assisted Language
Learning, 33(7), 652–672.
3. Liu, M., Liu, S., & Bui, T. (2022). Immersive learning with VR in L2 education: A
meta-analysis. ReCALL, 34(2), 124–142.
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4. McCrocklin, S. A. (2016). Pronunciation learner autonomy: The potential of
automatic speech recognition. System, 57, 25–42.
5. Nguyen, P., Wang, Y., & Pham, T. (2021). Artificial intelligence in English
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