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PLEASE NOTE:

This page displays a non-functioning prototype of the Online Video Analyser OVA. The purpose is to illustrate the design and explain the purpose of the tool, how it is intended to function, and how the results can be interpreted.

The OVA Online Video Analyser and all materials presented on this page are the intellectual property of Henriette Arndt and their use or exploitation in any way without permission is strictly prohibited

ONLINE VIDEO
ANALYSER

OVA analyses the vocabulary and overall language difficulty to help you find something to watch that's just right for you. 

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WHAT IS OVA?

OVA judges the difficulty of the language in online videos by using linguistic text analysis. Unlike similar available tools that require users to input the full text for analysis, OVA makes it easy to analyse spoken language in online videos through automatic subtitle extraction. OVA presents the results of the language analysis in a way that is easy to understand for English language learners. 

The analysis mostly focuses on the words that appear in each video. This is because vocabulary is a good predictor of overall difficulty and plays an important role in all four language skills—reading, writing, listening, and speaking. Linguistic researchers consider vocabulary the key to understanding and producing language. Read on to find out more about the meaning of the different metrics used by OVA.

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THE PERCENTAGE SCORE

The percentage score indicates the overall difficulty of an analysed video (0% = easiest; 100% = most difficult). This score combines different ways of assessing vocabulary (such as lexical diversity and vocabulary profiling).

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CEFR
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THE CEFR LEVEL

The Common European Framework of Reference for Languages describes what learners can do at different stages of studying a language in terms of speaking, listening, reading, and writing. The framework describes six levels of proficiency, with A1 and A2 referring to beginner, B1 and B2 to intermediate, and C1 and C2 to advanced learners. Two additional levels are included which refer to use of undergraduate-level (D1) and higher academic language (D2). 

OVA uses the CEFR levels to give you an idea of how proficient you need to be in English in order to understand a particular video. For example, if you are a lower-intermediate learner, you may wish to find videos at the B1 level and below. If you don’t know your own CEFR level of proficiency, you can take a look at the official self-assessment grid, or take one of the many placement tests that are available online (e.g., DIALANG). 

EVP

ENGLISH VOCABULARY PROFILE

The English Vocabulary Profile (EVP) is a list of words and phrases in English that learners at each of the six CEFR levels [link to earlier section] should know. OVA compares the words that occur in a given video to the EVP list and lets you know how much of the vocabulary learners at each CEFR level can expect to understand. Research has found that you should know at least 90% of the words in a spoken text in order to understand its meaning.  

 

You can see an example of OVA’s analysis in the graph on the left. This shows that a beginner learner (A1 level) would understand about 69% of the words in this video, a learner with elementary (A2 level) skills would understand about 83%, etc. The analysis suggests that this video would be most appropriate for a learner at intermediate level (B1) or above, who is likely to know more than 90% of the vocabulary. 

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ACADEMIC WORD LIST

In addition to the English Vocabulary Profile, OVA searches videos for words which appear in the Academic Word List (AWL). The AWL is a collection of words that often appear in academic texts but not so much in everyday writing or speech. OVA shows you the percentage of words in a video which are part of the AWL because this can help you understand how formal, or academic, the language used in this video is. 

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UNLISTED WORDS

Finally, OVA also tells you what percentage of words in the video don’t appear in the English Vocabulary Profile (EVP) or in the Academic Word List (AWL). These might include:

  • Rare words that are not often used in everyday language

  • Specialist words which are specific to a certain subject area or profession (e.g., science or medicine)

  • Slang words or very informal language

  • Other items that the OVA analyser cannot yet recognize (e.g., #hashtags or parts of a URL that is mentioned in a video)

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