Page 387 - Konferensiya to'plami - 1 (ASR)

Krashen (1982) introduced the Input Hypothesis, emphasizing that exposure to
comprehensible language input aids in language learning. This theory supports the
effectiveness of technology-assisted learning tools.
Piller (2017) examined how language barriers contribute to social and
workplace inequalities, stressing the need for improved communication tools.
Zheng & Warschauer (2018) explored the role of digital tools in second-
language acquisition, highlighting how mobile applications enhance learners’
speaking confidence.
Technology-Assisted Language Learning
Godwin-Jones (2015) discussed the rise of mobile-assisted language learning
(MALL) and how smartphones provide real-time language support.
Dizon (2020) evaluated AI chatbots such as Duolingo and Google Assistant in
spoken communication, concluding that while beneficial, they lack human-like
interaction capabilities.
McCarthy (2016) investigated speech recognition software like Google Voice
and Siri, emphasizing their role in improving pronunciation and fluency.
This study builds upon existing research to assess the effectiveness of language
tools in overcoming speaking barriers, focusing on real-world applications and
limitations.

METHODOLOGY
This research adopts a qualitative and comparative analysis approach to
examine the effectiveness of language tools in overcoming speaking barriers. The
study includes the following components:
1. Case Studies – Real-life examples of individuals using language tools for
communication are analyzed to understand their practical applications and
impact.
2. Tool Evaluation – The accuracy and efficiency of various language tools,
including translation software (Google Translate, DeepL), AI chatbots (ChatGPT,
Duolingo), and speech recognition systems (Google Voice, Siri), are assessed.
3. Surveys and Interviews – Feedback is collected from language learners,
educators, and professionals to evaluate their experiences and perspectives on
language tools.
4. Comparative Analysis – The strengths and weaknesses of different language
tools are examined in real-world communication scenarios to determine their
effectiveness and limitations.
The research relies on primary sources, including user data and reports from
technology developers, and secondary sources, such as academic articles on
language learning, artificial intelligence applications, and digital communication
technologies.

DISCUSSION AND RESULTS
Language tools play a crucial role in facilitating spoken communication across
various fields, including education, business, and daily social interactions. These tools
help individuals overcome language barriers by providing real-time translation,
pronunciation assistance, and interactive language learning experiences. One of the
most widely used language tools is translation software, such as Google Translate and 385
Deep . These tools offer instant translation services, allowing users to communicate

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