If there is no connection no grasp of the material so as to place the proper inflection where it belongs, what is spoken is cold and completely non-engaging. Until such a time where the algorithms behind synthesized speech are able to "understand" and contextualize the words (which, to a computer are just more ones and zeroes), it will never be able to add the NATURAL engagement factor called inflection where it's supposed to be and, thus, will never reach the effectiveness level of human speech. And it makes those listening more prone to continue listening. We do these things automatically and it turns our speech into music. When we speak among ourselves, we add inflection without thinking about it, placing importance on some words, less on others, a smile here, some compassion there, a sudden burst of excited whisper, the occasional dramatic pause to build anticipation or allow a point to sink in before moving on, etc. People you know, even people you don't know. Here's a practice exercise for everyone: spend some time listening to people engaged in conversation. It seems that proponents of text-to-speech don't understand that inflection NATURAL inflection is the key, and synthesized speech, no matter that the "voice" may sound so human-like, will never be able to place correct inflection where needed and not where it is not needed. When the goal is to get to the finish line faster, we don't use cheaper fuel. It would seem to me, that if a company's goal was to maximize employee performance, the LAST place they'd consider cutting costs would be the tools and methods used to achieve that goal. I wonder if any company who uses eLearning has done an analysis to compare the money spent on producing the learning content against whether there was a marked improvement in employee performance.
Success is measured in what people remember and are able to apply. Thus, eLearning success cannot be measured by the quantity of material that was produced in X number of hours or that X number of dollars were saved. In instruction, it is hoped that learners will be able to use what they learned to better their performance. In the case of commercials, advertisers hope to motivate people to buy their product or service.
#IVONA VOICE INFLECTION TV#
And, just like TV and radio commercials, success hinges squarely on whether the message is able to not only grab but hold the attention of the listener/viewer/learner so that they will ABSORB what they saw and/or heard, and that they will also RETAIN that information so that they can later APPLY it. The goal of instruction of any kind is to either simply share information or to change behavior/performance. It is solely out of concern over results. It is not at all because I'm a voice-over/narrator that I am opposed to the use of text-to-speech technology. txt file and copy / paste the batch line into terminal. Easy to pick up by the file size of the output. It only fails if there's a funny character or the text file is missing. Copying and pasting multiple lines will do it multiple times. Say -v lee -f /Users/sflowers/Desktop/Dropbox/projectname/production/scratch_audio_scenarios/s1_c1.txt -o /Users/sflowers/Desktop/Dropbox/ projectname /production/scratch_audio_scenarios/s1_c1.aiffĬopying and pasting this line into terminal will grab the text file and output an audio file in the voice I've selected. The batch template lines look something like this: Then I setup a batch file for terminal to automatically generate the outputs.
#IVONA VOICE INFLECTION PLUS#
txt file for each bit of audio (on the plus side, I have found a way to use this as a transcript feeder). It takes a little bit to set up my transcript input files, I haven't automated that part yet.īasically, when the script is approved, I generate a. Pretty neat trick I use to batch each file using terminal.
#IVONA VOICE INFLECTION MAC#
I've switched over entirely from other TTS programs to Mac voices.
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