शैडोइंग अभ्यास: Cambridge Ielts 16 Reading test 1 Passage 3 - वीडियो के साथ अंग्रेजी बोलना सीखें

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59 वाक्य
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3. The Future of Work According to a leading business consultancy,
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3-14% of the global workforce will need to switch to a different occupation within the next 10-15 years,
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and all workers will need to adapt as their occupations evolve alongside increasingly capable machines.
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Automation, or Embodied Artificial Intelligence, AI, is one aspect of the disruptive effects of technology on the labor market.
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Disembodied L, like the algorithms running in our smartphones, is another.
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Dr. Stella Pacitti from Cambridge Judge Business School believes
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that some of the most fundamental changes are happening as a result of the algorithmication of jobs
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that are dependent on data rather than on production, the so-called knowledge economy.
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Algorithms are capable of learning from data to undertake tasks that previously needed human judgment, such as reading legal contracts,
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analyzing medical scans, and gathering market intelligence.
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In many cases, they can outperform humans, says Pachidi.
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Organizations are attracted to using algorithms because they want to make choices based on what they consider as perfect information, as well as to reduce costs and enhance productivity.
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But these enhancements are not without consequences, says Pachidi.
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If routine cognitive tasks are taken over by AI, how do professions develop their future experts?
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She asks.
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One way of learning about a job is legitimate peripheral participation.
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A novice stands next to experts and learns by observation.
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If this isn't happening, then you need to find new ways to learn.
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Another issue is the extent to which the technology influences or even controls the workforce.
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For over two years, Puccini monitored a telecommunications company.
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The way telecom salespeople work is through personal and frequent contact with clients, using the benefit of experience to assess a situation and reach a decision.
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However, the company had started using an algorithm that defined
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when account managers should contact certain customers about which kinds of campaigns and what to offer them.
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The algorithm, usually built by external designers, often becomes the keeper of knowledge, she explains.
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In cases like this, Pachitti believes,
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a short-sighted view begins to creep into working practices whereby workers learn through the algorithm's eyes and become dependent on its instructions.
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Alternative explorations, where experimentation and human instinct lead to progress and new ideas, are effectively discouraged.
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Pachidi and colleagues even observed people developing strategies to make the algorithm work to their own advantage.
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We are seeing cases where workers feed the algorithm with false
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data to reach their targets she reports it's scenarios like these
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that many researchers are working to avoid their objective is to make ai technologies more trustworthy
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and transparent so that organizations
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and individuals understand how ai decisions are made in the meantime
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says pachidi We need to make sure we fully understand the dilemmas that this new world raises regarding expertise, occupational boundaries, and control.
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Economist Professor Hamish Lowe believes that the future of work will involve major transitions across the whole life course for everyone.
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The traditional trajectory of full-time education followed by full-time work followed by a pension retirement is a thing of the past, says Lowe.
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Instead, he envisages a multi-stage employment life, one where retraining happens across the life course,
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and where multiple jobs and no job happen by choice at different stages.
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On the subject of job losses, Mo believes the predictions are founded on a fallacy, it assumes that the number of jobs is fixed.
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If in 30 years, half of 100 jobs are being carried out by robots,
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that doesn't mean we are left with just 50 jobs for The number of jobs will increase.
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We would expect there to be 150 jobs.
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Dr. Ewan Mitkauhi at Cambridge's Centre for Business Research in King's College London agrees
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that apocalyptic views about the future of work are misguided.
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It's the laws that restrict the supply of capital to the job market, not the advent of new technologies that causes unemployment.
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His recently published research answers the question of whether automation, AI and robotics will mean a jobless future by looking at the causes of unemployment.
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it.
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History is clear that change can mean redundancies, but social policies can tackle this through retraining and redeployment.
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He adds, if there is going to be changed to jobs as a result of AI
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and robotics then I'd like to see governments seizing the opportunity to improve policy to enforce good job security.
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We can reprogram the law to prepare for a fairer future of work and leisure.
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McGauhe's findings are a call to arms to leaders of organizations, governments and banks to preempt for coming changes with bold new policies that guarantee full employment,
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fair incomes and a thriving economic democracy.
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The promises of these new technologies are astounding.
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They deliver humankind the capacity to live in a way that nobody could have once imagined humans.
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Just as the Industrial Revolution brought people past subsistence agriculture and the corporate revolution enabled mass production,
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a third revolution has been pronounced.
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But it will not only be one of technology.
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The next revolution will be social.

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इस पाठ की शब्दावली और बोलने के सुझाव

यह C1 स्तर का स्पीकिंग पाठ वीडियो “Cambridge Ielts 16 Reading test 1 Passage 3” पर आधारित है। सबसे ज़्यादा दोहराए गए शब्द ये हैं: algorithm, pachidi, believes, revolution, technologies। इस वीडियो में शैडोइंग के लिए 59 वाक्य और 839 शब्द हैं। बोला गया हिस्सा 5:47 लंबा है। वक्ता लगभग 145 शब्द प्रति मिनट की स्थिर गति से बोलता है, जो शैडोइंग के लिए आरामदायक है। केवल 77% शब्द अंग्रेज़ी के 3,000 सबसे आम शब्दों में से हैं, इसलिए शब्दावली कठिन है।

इस वीडियो की मुख्य शब्दावली

वीडियो के 15 सबसे कठिन शब्द, उच्चारण और अर्थ के साथ:

शब्दउच्चारणअर्थ
algorithm संज्ञा/ˈælɡəɹɪðm̩/अल्गोरिद्म
robotics संज्ञा/ɹoʊˈbɑ.tɪks/रोबॉटिक्स
automation संज्ञा/ˌɔ.təˈmeɪ.ʃən/स्वचालन
fallacy संज्ञा/ˈfæl.ə.si/मिथ्या
salesperson संज्ञाविक्रेता
trustworthy विशेषण/ˈtɹʌst.wɜː.ði/निष्ठावान
trajectory संज्ञा/tɹəˈd͡ʒɛktəɹi/प्रक्षेपवक्र
enhancement संज्ञा/ɪnˈhæns.mənt/वृद्धि, वर्धन
advent क्रिया/ˈæd.vɛnt/आगमन
thrive क्रिया/θɹajv/फलना
dilemma संज्ञा/daɪˈlɛmə/दुविधा, संशय
analyze क्रिया/ˈæn.əˌlaɪz/विश्लेषण करना
instinct संज्ञा/ˈɪn.stɪŋkt/फ़ितरत, वृत्ति
researcher संज्ञा/ˈɹiˌsɝ.t͡ʃɚ/शोधकर्ता, शोधक
leisure संज्ञा/ˈlɛʒə(ɹ)/अवकाश, फ़ुर्सत

ध्यान देने योग्य उच्चारण

वक्ता 3 बार संक्षिप्त रूपों का प्रयोग करता है, जैसे doesn't, I'd, isn't। इन्हें वैसे ही छोटा बोलें जैसा आप सुनते हैं।

  • “th” की ध्वनियाँ: algorithm /ˈælɡəɹɪðm̩/, trustworthy /ˈtɹʌst.wɜː.ði/, thrive /θɹajv/
  • “sh” और “zh” की ध्वनियाँ: automation /ˌɔ.təˈmeɪ.ʃən/, experimentation /ɪkˌspɛɹ.ə.mənˈteɪ.ʃən/, telecommunication /ˌtɛləkəˌmjunɪˈkeɪʃən/, occupational /ɑkjuˈpeɪʃənəl/, leisure /ˈlɛʒə(ɹ)/
  • लंबे शब्द — बलाघात सही रखें: automation /ˌɔ.təˈmeɪ.ʃən/, apocalyptic /əˈpɒ.kə.lɪp.tɪk/, consultancy /kənˈsʌl.tən.si/, disembodied /dɪsɪmˈbɒdiːd/, experimentation /ɪkˌspɛɹ.ə.mənˈteɪ.ʃən/

हिंदी भाषियों के लिए मुश्किल ध्वनियाँ:

  • /v/ और /w/ का फ़र्क़ — /v/ में ऊपर के दाँत निचले होंठ को छूते हैं, /w/ में होंठ गोल होते हैं: workforce /ˈwɝk.foɹs/, disruptive /dɪsˈɹʌptɪv/, envisage /ɛnˈvɪzɪd͡ʒ/, novice /ˈnɑvɪs/, trustworthy /ˈtɹʌst.wɜː.ði/
  • /z/ — इसे “ज” (/dʒ/) न बनाएँ: envisage /ɛnˈvɪzɪd͡ʒ/, seize /ˈsiːz/, analyze /ˈæn.əˌlaɪz/, observe /əbˈzɜːv/, expertise /ˌɛkspɜːˈtiːz/
  • शब्द की शुरुआत में s + व्यंजन — पहले “इ” न जोड़ें: smartphone /ˈsmɑɹtfoʊn/, scan /skæn/

इस वीडियो से अभ्यास कैसे करें

  1. पहले बिना बोले पूरा वीडियो एक बार सुनें और जो शब्द नहीं आते उन्हें लिख लें।
  2. सामान्य गति पर एक-एक वाक्य की शैडोइंग करें और हर वाक्य तब तक दोहराएँ जब तक आपकी लय वक्ता से न मिल जाए।
  3. अपनी आवाज़ रिकॉर्ड करें और मूल से तुलना करें, ख़ासकर algorithm, robotics, automation जैसे शब्दों पर ध्यान दें।

शैडोइंग तकनीक क्या है?

शैडोइंग (Shadowing) एक विज्ञान-समर्थित भाषा सीखने की तकनीक है जो मूल रूप से पेशेवर दुभाषिया प्रशिक्षण के लिए विकसित की गई थी। विधि सरल लेकिन शक्तिशाली है: आप मूल अंग्रेज़ी ऑडियो सुनते हैं और तुरंत इसे ज़ोर से दोहराते हैं — जैसे वक्ता की छाया 1-2 सेकंड की देरी से। शोध से पता चलता है कि यह उच्चारण सटीकता, स्वर, लय, जुड़ी हुई ध्वनियाँ, सुनने की समझ और बोलने की प्रवाहशीलता में काफ़ी सुधार करता है।

शैडोइंग तकनीक: पूरी चरण-दर-चरण गाइड पढ़ें →