We use machine learning for lots of things at Phonic. Speech recognition, sentiment analysis and emotional classification are all problems that are best solved by supervised ML systems. Generally speaking, theses systems require training on large datasets - the bigger the better. While there are... Read More
At Phonic we advocate for the efficiency of human speech. Communicating with voice is fast (150 words per minute compared to 50 for typing), rich in emotion and accessible to nearly everyone on the planet. We've always known that these differences enable longer, more detailed survey responses... Read More
Phonic started out with a simple idea: make it easy to collect authentic, qualitative feedback from anywhere. Until now this has meant embedding a microphone in online experiences and collecting voice at scale. Today, we expand our vision with general purpose video and screen recording capabiliti... Read More