Ethnic diversity in elearning voice over
One of the things I’m often asked by elearning clients is how to handle ethnic diversity in a project that requires voice over (VO) audio. Their end-client might envisage people of various ethnic backgrounds playing the roles of the characters in their training scenarios and the project manager needs to find a voice for each. In order to offer a solution, we first need to establish what precisely the end-client is looking for.
To my mind, there are two options, so my first question to the elearning project manager is: do you want characters who are, for example, first-generation American, but second-generation Asian, African, etc? i.e. they are American and therefore speak perfect English with an American accent. Or do you want characters who are from a variety of countries around the world and who speak English as a second language very clearly, but with their native accents? These are two very different requests.
Let’s deal with the first one because it’s the easiest to arrange from the point-of-view of the elearning project manager and VO studio.
Imagine our training scenario involves five characters as follows:
• an Asian male
• an African female
• a Hispanic female
• an Eastern European male
• an Indian female
All of these characters will be represented in the training course by stock photography, all of which has been preapproved by the end-client. Looking at the images of these characters, the elearning project manager’s initial request to the studio might be that they need all of the above: an Asian male VO; an African female VO; etc. But if the end-client envisaged all of these characters with diverse ethnic backgrounds as being first-generation Americans, then they’re American and are just going to sound as such. So here, the task becomes not so much one of finding VO talent with diverse ethnic backgrounds, as one of finding VO talent who sound like they could be the people represented in the images. Maybe the photographed male who looks Asian is around 25, so the studio just has to find a male VO who sounds around 25 and whose voice could plausibly be that of the person in the photo. As we’re looking for something much less specific here, the task is much easier. It becomes more about finding VOs who sound like they could be the people in the photos, rather than finding VOs with specific ethnic backgrounds. This means that the photos in the training course, rather than the voices, will be responsible for depicting diversity in the elearning.
Now let’s look at the second option, where the situation is quite different. Let’s say we’re depicting the same five characters in the training scenario, but this time, the end-client has specified that they want VOs who are natives to those backgrounds. From a VO selection point of view, this is a very different request. Here, the studio has to source five VOs from those regions, who can speak perfect English, but with their native accent. This is a tougher challenge for the studio and not as straight-forward as it may appear. For example, the studio might know a Chinese VO who performs very well when speaking in his native tongue. This VO might have excellent conversational English, but when it comes to voicing a project in English, he might not be as proficient as he is when voicing in Chinese. From the studio’s perspective, a different vetting process is required for there is a fine line between such a VO having a strong accent and being intelligible. Also, when recording, the recording session director will have to decide which mispronunciations are acceptable, given the accent, and which mispronunciations are so alien as to be unintelligible and distracting to the listener. The director will also have to take into account that the training’s audience might also be so diverse such that many course-users will have English as a second language, too and therefore may have trouble with strong accents from regions of the world other than their own. However, once this project is complete, it will be both the VO audio and the character photographs that establish the ethnic diversity within its scenarios.
As you can gather, while neither of these options presents insurmountable challenges to elearning project managers and studios, it is very important to establish early in development what level of diversity your client has in mind for its training scenarios.