Director of Business Development, SoundHound, Andrew Richards, shares how Houndify handles speech recognition in noisy environments.
Voice AI in noisy environments
Voice AI can provide immense value outside of the home. Problem is, outside is noisy! So how to you create voice AI solutions and speech recognition systems that work well in cars, in traffic, outside or with screaming kids in the background!?
We’re joined by SoundHound’s Director of Business Development, Andrew Richards, to shed some light on how one of the top voice AI companies tackles this challenge.
We dive into:
- What are the common challenges when implementing voice solutions in noisy environments?
- Any examples of areas where the environment proves trickier than others?
- Microphone technology, placement and arrays
- What’s beam forming and why is it important?
- How do you (or what do you do to…) mitigate the noise to get a clean signal?
- About additive noise, convolutional noise, distortion and noise reduction
- What do you need to consider when implementing a voice assistant in a noisy environment?
- How to train speech recognition systems for use in noisy places?
Links
Read the Houndify Speech to Meaning blog (recommended)
All about speech recognition with Catherine Breslin
How voice AI is disrupting industries with SoundHound’s Mike Zagorsek
How to train speech recognition systems with Atexto
