NeuroLex Labs
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About
NeuroLex Labs, acquired by Sonde Health, offers voice technologies for healthcare. Their products include SurveyLex, a voice-enabled survey platform, and Sonde One, a solution for safe return to work. They provide services like data collection, cleaning, featurization, machine learning, speaker diarization, and data labeling. They also curate voice datasets for voicemails, emotions, accents, genders, and various health conditions like depression, schizophrenia, and Parkinson's disease. The company offers a 14-day trial and has been featured in the Atlantic and by the American Psychiatric Association.
Platform
Task
Features
• speaker diarization
• data collection
• machine learning
• data cleaning
• voice-enabled survey platform
• monetization
• data labeling
• featurization
FAQs
How can I learn more about voice computing?
We recently wrote a textbook to help train more developers in this field. Check it out at [this link.](https://www.neurolex.ai/voicebook/)
Can you provide custom services?
Yes! We can customize service contracts to meet your needs. Here are some services that we can provide beyond our core product offerings: 1. Manual data annotation - $1/minute of audio per label 2. Automated data anotation - $0.12/minute of audio 3. Data cleaning - $100/hour 4. Data modeling - $150/hour 5. Research assistants (collect data) - $15/hour 6. Speaker diarization (up to 3 speakers) - $0.024/minute of audio processed 7. Hardware design - Varies based on scope 8. Manual transcription (100% accuracy) - $1-2/minute 10. Custom software development - Varies based on scope If you want something done that does not fit the above list, reach out to us. We most likely are able to help you with the >30 voice engineers in our lab.
When can you start a project?
We can start projects immediately and scale-up very quickly. Just book a meeting on our calendar [here](http://calendly.com/jimschwoebel) and we'll handle the rest.
What features can you extract?
We commonly get asked how many and what types of features we extract to build machine learning models. Simply, there are 4 main types of features that we can extract: 1. Audio features - acoustic features extracted from an audio file (e.g. fundamental frequency) 2. Text features - language features extracted from a transcript (e.g. noun frequency) 3. Mixed features - Mixing up audio features and text features - often as a ratio (e.g. speaking rate). 4. Meta features - features derived from machine learning models on any of the embeddings described above (e.g. age - 20s). You can read more about each of these types of features @ this[ GitHub link](https://github.com/jim-schwoebel/voicebook/wiki/0.3.-Featurization).
Can I join your research lab?
Absolutely! If you are interested to join our lab, please [fill out this application](http://innovate.neurolex.co) to join our innovation fellows program. After applying, we will be in touch within 1-3 months. If you'd like to speak sooner,[ schedule a demo meeting](https://calendly.com/jimschwoebel). We are always willing to speak about how you can contribute to our company.
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