Hi Amie,
It occurs to me that maybe an improved version (we can probably work on this rather quickly) of the tokenized text stimulus would be the best solution for your designs? The tokenized text stimulus has a "singleton" mode that displays one word/token at a time. You will essentially enter your sequences as a list of "tokens", where blank screens are just an empty string as a token. Then, FF can "play" the sequence for you, simulating the effect you want within a single stimulus.
The "improvement" that needs to be done is to allow a different duration for each token. Right now, the tokenized text stimulus takes a single number for "token_duration", but that can be easily expanded to accept a list of timings.
This wouldn't work for studies where user response is only allowed when the "target" token appears, but since you are just collecting audio recordings passively, you'll just collect a longer recording.
The huge benefit is that you can now create all trials in a single block now, and randomize them properly. Right?
It occurs to me that maybe an improved version (we can probably work on this rather quickly) of the tokenized text stimulus would be the best solution for your designs? The tokenized text stimulus has a "singleton" mode that displays one word/token at a time. You will essentially enter your sequences as a list of "tokens", where blank screens are just an empty string as a token. Then, FF can "play" the sequence for you, simulating the effect you want within a single stimulus.
The "improvement" that needs to be done is to allow a different duration for each token. Right now, the tokenized text stimulus takes a single number for "token_duration", but that can be easily expanded to accept a list of timings.
This wouldn't work for studies where user response is only allowed when the "target" token appears, but since you are just collecting audio recordings passively, you'll just collect a longer recording.
The huge benefit is that you can now create all trials in a single block now, and randomize them properly. Right?