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    • #17027
      Dagmar Munn

      In my column, Adding My Voice to a Valuable Study, I wrote about how about a speech study that I am participating in. I was among the first 100, and besides going through the various vocal tests, our feedback helped streamline the process. Now, here’s good news – – the study sponsors are ready to increase participation numbers to 250 and, eventually 1000.

      I wrote about one of the study’s goals: to help AI voice-activation software become better at recognizing ALS voices. But another goal is to use the data to help in the early detection of speech issues.  I recommend everyone considers signing up to participate – – the study protocol is easy, quick, and can be done at home on your computer.

      Here is some detailed information from study sponsor Everything ALS:

      We are looking for individuals diagnosed or candidates with Amyotrophic Lateral Sclerosis (ALS) as well as healthy participants between 18 and 100 years of age.

      Our study is motivated by the need for early detection and improved prognostic accuracy of ALS using advanced computational technology and speech data (audio, video). By participating in this study, you will contribute to a growing large ALS data set and further advance current knowledge relating to the decline in speech production due to ALS while also improving the performance of this technology.

      The approach will be to perform an analysis of online audio/video recordings.: The study activity involves the use of Modality.ai Inc.’s web-based software that collects speech audio and video data and then uses AI and machine learning algorithms to analyze facial and speech metrics.

      Data collection can be conducted anywhere you feel comfortable (e.g., your home). Each session will last approximately 20 minutes. Participants are welcome to do multiple sessions if interested.

      If you are interested in participating: EverythingALS Website:  https://www.everythingals.org/research

      Shot descriptive video:  https://youtu.be/hDXtCTQ–MM 

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