Understanding accents and their role in language learning

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Accents are a fascinating aspect of language that can reveal a lot about a person's background and experiences. For language learners, accents often become a central focus, sometimes to the detriment of more important language skills. In this post, we’ll explore what accents are, why people have them, and why intelligibility is more important than mastering an accent.

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What are accents?

An accent is a distinctive way of pronouncing words that is characteristic of a particular region, social group, or native language. It involves variations in phonetics, intonation and rhythm. For example, a person from London might speak English with a different accent compared to someone from Edinburgh.

Accents are natural and inevitable; everyone has one. They are influenced by various factors, including geography, culture and exposure to other languages. When you learn a new language, your native language influences your pronunciation.

Depending on your accent, you may pronounce some sounds in certain ways that aren't reflected in another language, or perhaps certain sounds or words don't even exist in your first language. For example in Japanese, there is no /L/ sound, so a native Japanese speaker might struggle to pronounce the word "love" with an accurate /L/ sound.

Another example is . They often use clicks in their language, which is not found in many other languages, making it difficult for non-native speakers to imitate and learn. For anyone who has to make a sound they aren't used to, it can be initially difficult as the mouth has to move in a way unfamiliar to the speaker.

There is even a discussion on whether physical aspects affect accent, such as the shape of your teeth, tongue and oral posture (the way your teeth rest together and tongue sits in your mouth). There are also many other physical factors that are under debate on whether they impact voice/accent.

Why do people have accents?

People have accents for several reasons:

  1. Geographical influence: The region where a person grows up significantly affects their accent. Even within the same country, accents can vary widely from one city or town to another.
  2. Cultural factors: Cultural background plays a role in shaping how people speak. For instance, social norms and traditions can influence speech patterns and pronunciations.
  3. Native language impact: Your first language has a profound impact on how you pronounce sounds in a new language. Certain sounds may not exist in your native language, making them harder to replicate accurately in another.
  4. Exposure and practice: The amount of exposure and practice you have with a new language can affect your accent. Regular interaction with fluent speakers can help you adopt more native-like pronunciations. If you spend a lot of time around foreign media you may start picking up accents from there.

Have you ever spoken to someone and you feel like they're mimicking your accent? or that you're subconsciously mimicking theirs? This can be due to the ', when a person adopts and mimics things such as gestures or voice of the person they are in conversation with. This is seen as a subconscious way to build rapport and connection with others.

Why do accents matter?

Accents matter because they are a core part of our identity and how we relate to the world. For language learners, accents can be a source of pride or frustration.

However, it’s essential to understand that having a foreign accent is perfectly normal and not a barrier to effective communication. In fact, accents add diversity and richness to language and should be embraced.

Why intelligibility is more important than mastering an accent

In the context of language learning, intelligibility—being understood by others—should be your primary goal rather than eliminating or changing your accent. Here’s why:

  1. Effective communication: The main aim of learning a new language is to communicate effectively. If others can understand you clearly, your accent becomes less important.
  2. Reduced pressure: Focusing on intelligibility rather than perfecting an accent reduces stress and makes the learning process more enjoyable. You can concentrate on expanding your vocabulary and improving grammar instead.
  3. Cultural acceptance: Many native speakers are accustomed to hearing various accents and can understand them without difficulty. They appreciate the effort you put into learning their language, regardless of your accent.
  4. Retaining your identity: Trying to eliminate your accent may mean losing part of your cultural identity. Embracing your accent shows others that you are proud of where you come from and can open the door to meaningful conversations about culture and diversity.
  5. Practical progress: Concentrating on intelligibility allows you to make practical progress in real-world situations, such as ordering food, asking for directions, or participating in conversations.

Tips for improving intelligibility

  • Listen and mimic: Spend time listening to fluent speakers and try to mimic their intonation and rhythm.
  • Practice pronunciation: Focus on pronouncing key sounds correctly.
  • Record yourself: Recording your speech and comparing it to fluent speakers can help you identify areas for improvement.
  • Seek Feedback: Don’t hesitate to ask fluent speakers for feedback on your pronunciation and clarity. It's the best way to determine your intelligibility.

Be proud of your accent

Accents are a natural part of language and identity. While they can influence how we are perceived, they should not be a major concern for language learners. Instead, focus on being understood and enjoying the process of learning a new language. Remember, an accent is not a flaw; it’s your blueprint.

Read out blog posts 'What does it mean to be fluent in English?' and 'Understanding dialects in the English language'

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    Can computers really mark exams? Benefits of ELT automated assessments

    By ÃÛÌÒapp Languages

    Automated assessment, including the use of Artificial Intelligence (AI), is one of the latest education tech solutions. It speeds up exam marking times, removes human biases, and is as accurate and at least as reliable as human examiners. As innovations go, this one is a real game-changer for teachers and students. 

    However, it has understandably been met with many questions and sometimes skepticism in the ELT community – can computers really mark speaking and writing exams accurately? 

    The answer is a resounding yes. Students from all parts of the world already take AI-graded tests.  and VersantÌýtests – for example – provide unbiased, fair and fast automated scoring for speaking and writing exams – irrespective of where the test takers live, or what their accent or gender is. 

    This article will explain the main processes involved in AI automated scoring and make the point that AI technologies are built on the foundations of consistent expert human judgments. So, let’s clear up the confusion around automated scoring and AI and look into how it can help teachers and students alike. 

    AI versus traditional automated scoring

    First of all, let’s distinguish between traditional automated scoring and AI. When we talk about automated scoring, generally, we mean scoring items that are either multiple-choice or cloze items. You may have to reorder sentences, choose from a drop-down list, insert a missing word- that sort of thing. These question types are designed to test particular skills and automated scoring ensures that they can be marked quickly and accurately every time.

    While automatically scored items like these can be used to assess receptive skills such as listening and reading comprehension, they cannot mark the productive skills of writing and speaking. Every student's response in writing and speaking items will be different, so how can computers mark them?

    This is where AI comes in. 

    We hear a lot about how AI is increasingly being used in areas where there is a need to deal with large amounts of unstructured data, effectively and 100% accurately – like in medical diagnostics, for example. In language testing, AI uses specialized computer software to grade written and oral tests. 

    How AI is used to score speaking exams

    The first step is to build an acoustic model for each language that can recognize speech and convert it into waveforms and text. While this technology used to be very unusual, most of our smartphones can do this now. 

    These acoustic models are then trained to score every single prompt or item on a test. We do this by using human expert raters to score the items first, using double marking. They score hundreds of oral responses for each item, and these ‘Standards’ are then used to train the engine. 

    Next, we validate the trained engine by feeding in many more human-marked items, and check that the machine scores are very highly correlated to the human scores. If this doesn’t happen for any item, we remove it, as it must match the standard set by human markers. We expect a correlation of between .95-.99. That means that tests will be marked between 95-99% exactly the same as human-marked samples. 

    This is incredibly high compared to the reliability of human-marked speaking tests. In essence, we use a group of highly expert human raters to train the AI engine, and then their standard is replicated time after time.  

    How AI is used to score writing exams

    Our AI writing scoring uses a technology called . LSA is a natural language processing technique that can analyze and score writing, based on the meaning behind words – and not just their superficial characteristics. 

    Similarly to our speech recognition acoustic models, we first establish a language-specific text recognition model. We feed a large amount of text into the system, and LSA uses artificial intelligence to learn the patterns of how words relate to each other and are used in, for example, the English language. 

    Once the language model has been established, we train the engine to score every written item on a test. As in speaking items, we do this by using human expert raters to score the items first, using double marking. They score many hundreds of written responses for each item, and these ‘Standards’ are then used to train the engine. We then validate the trained engine by feeding in many more human-marked items, and check that the machine scores are very highly correlated to the human scores. 

    The benchmark is always the expert human scores. If our AI system doesn’t closely match the scores given by human markers, we remove the item, as it is essential to match the standard set by human markers.

    AI’s ability to mark multiple traits 

    One of the challenges human markers face in scoring speaking and written items is assessing many traits on a single item. For example, when assessing and scoring speaking, they may need to give separate scores for content, fluency and pronunciation. 

    In written responses, markers may need to score a piece of writing for vocabulary, style and grammar. Effectively, they may need to mark every single item at least three times, maybe more. However, once we have trained the AI systems on every trait score in speaking and writing, they can then mark items on any number of traits instantaneously – and without error. 

    AI’s lack of bias

    A fundamental premise for any test is that no advantage or disadvantage should be given to any candidate. In other words, there should be no positive or negative bias. This can be very difficult to achieve in human-marked speaking and written assessments. In fact, candidates often feel they may have received a different score if someone else had heard them or read their work.

    Our AI systems eradicate the issue of bias. This is done by ensuring our speaking and writing AI systems are trained on an extensive range of human accents and writing types. 

    We don’t want perfect native-speaking accents or writing styles to train our engines. We use representative non-native samples from across the world. When we initially set up our AI systems for speaking and writing scoring, we trialed our items and trained our engines using millions of student responses. We continue to do this now as new items are developed.

    The benefits of AI automated assessment

    There is nothing wrong with hand-marking homework tests and exams. In fact, it is essential for teachers to get to know their students and provide personal feedback and advice. However, manually correcting hundreds of tests, daily or weekly, can be repetitive, time-consuming, not always reliable and takes time away from working alongside students in the classroom. The use of AI in formative and summative assessments can increase assessed practice time for students and reduce the marking load for teachers.

    Language learning takes time, lots of time to progress to high levels of proficiency. The blended use of AI can:

    • address the increasing importance of formative assessmentÌýto drive personalized learning and diagnostic assessment feedback 

    • allow students to practice and get instant feedback inside and outside of allocated teaching time

    • address the issue of teacher workload

    • create a virtuous combination between humans and machines, taking advantage of what humans do best and what machines do best. 

    • provide fair, fast and unbiased summative assessment scores in high-stakes testing.

    We hope this article has answered a few burning questions about how AI is used to assess speaking and writing in our language tests. An interesting quote from Fei-Fei Li, Chief scientist at Google and Stanford Professor describes AI like this:

    “I often tell my students not to be misled by the name ‘artificial intelligence’ — there is nothing artificial about it; A.I. is made by humans, intended to behave [like] humans and, ultimately, to impact human lives and human society.â€

    AI in formative and summative assessments will never replace the role of teachers. AI will support teachers, provide endless opportunities for students to improve, and provide a solution to slow, unreliable and often unfair high-stakes assessments.

    Examples of AI assessments in ELT

    At ÃÛÌÒapp, we have developed a range of assessments using AI technology, including  is aimed at those who need to prove their level of English for a university place, a job or a visa. It uses AI to score tests and results are available within five days.