ProTS Voiceover revised

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Project Main Details

ProTS Voiceover revised  
1minute voice over for flash product demonstration. We would like a straight forward voice, not extremely excited but not very dull. This is for a helathcare product
2010-05-18 16:35:07 GMT
2010-05-25 23:00:00 (GMT -07:00) Mountain Time (US & Canada) 
Yes (click here to learn more about Voice123's SmartCast)
0 direct invitation(s) have been sent by the voice seeker resulting in 0 audition(s) and/or proposal(s) so far.
Voice123 SmartCast is seeking 20 auditions and/or proposals for this project (approx.) Invitations sent by SmartCast have resulted in 0 audition(s) and/or proposal(s) so far.

Project Parameters

The Voice Actor should be located in:
Fixed - USD 200
Training, business presentations, sales, and web sites
1 minute
English - USA and Canada
Senior Male
• Audio files must be delivered via email
• Deliver edited and finished voice tracks
The Voice Actor should have at least 10 years of experience in the voice industry.
This is a non-union project

Script Details

Sample script below provided by the voice seeker for auditions. 
Inside the mass spectrometer’s ion source, a laser generates ions from molecules in the sample.

Ions travel down the flight tube at different velocities depending on their mass-to-charge ratio.

The arrival time of ions at the detector, which is correlated with their mass-to-charge ratio, is displayed as a mass spectrum, a plot of the ions’ mass-to-charge ratio and the number of ions detected.

For each sample, hundreds of individual mass spectra are collected and combined to generate a single averaged spectrum.
ProTS then estimates and subtracts background, estimates noise, and normalizes the averaged spectrum.

Using proprietary reference points, ProTS aligns the spectrum along the mass-to-charge axis.

The normalized and aligned spectrum can then be reliably compared with spectra from other individuals.

ProTS data analysis, supervised learning, and proprietary methodologies are used to compare spectra across clinically relevant populations and identify features which distinguish the groups. For example, Group A might represent patients who respond to a particular therapy; group B, those who do not.

The selected features are then incorporated into a novel classifier algorithm, a test which evaluates the spectra from multiple analyses of a patient sample and assigns that sample to one of the two predetermined groups. 
Please note that you should only use the script or your recording of it for auditioning purposes. The script is property, unless otherwise specified, of the voice seeker and it is protected by international copyright laws.

Voice-Seeker Details

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