John Field has made the case for micro-listenings which are “examples of the same word/phrases in different voices and contexts” (John Field 2013, New directions in second language listening:rethinking the Comprehension Approach presentation, slide 13) that can be replayed easily.
Such listenings helps to develop a learner’s decoding skills. These micro-listenings can be embedded into a task that includes say transcription exercises.
An easy way to get such micro-listenings automatically is to use Videogrep. This tool allows you to search a subtitle file for a word, a grammatical form or hypernym and then able to make a new super cut/edited video containing your search word/grammatical form/hypernym.
I have a 1-to-1 adult student who is keen on motorbikes and wants to see a documentary film of the Isle of Man TT races called TT3D – Closer to the edge (yeah can u dig it, get your motor running, headout on…ah um back to post). He has yet to see it due to lack of time so as a way to take advantage of this interest I created a supercut video using Videogrep.
I initially fed the subtitle file into AntWordProfiler to see what word I could cut, I wanted one that was in the 1st 1000 of the GSL (general service list) but that did not have too many hits so get although very interesting (and I may well use that later) had 512 hits so was way too many for a micro-listen. Looking down the list I noticed set with 9 hits. I had read somewhere that set has the most meanings of any word in English.
Anyway this seemed ideal so here is the super cut of set:
Notice we have examples of upset, upsetting, settle so a great way to see if my student can distinguish these from the other uses.
Field recommends a task approach so one can set the instruction before first listen as: The clips have something in common what is it? and then before the subsequent listens one asks the student to transcribe what uses of set they hear.
I’ll report back here how the student got on when I can.
Thanks for reading.
The two students I have used #videogrep-ed micro-listenings with liked them a lot. There were some issues about difficulty of transcribing some of the clips which could put off less hardy souls.
Some notes on using videogrep – you can use regular expressions or regex to tighten up searches so for example if I just wanted uses of set and not upset, upsetting, settle I would use
\bset as the search term where \b is the regex for word boundary. Here is a list of regexes though I have yet to have a use for anything other than \b so far – http://www.pyregex.com/.
Also you will find you need to expand some clips which are cut early so add the command
--padding and a number measured in milliseconds so for example
--padding 500 would pad out the beginning and ends of clips by 500ms.
There is an (experimental) graphical interface version for the Apple OSX (103MB) useful for those not comfortable with using command line.