How to Build An Audio Machine Learning Dataset

Published by Phonic on
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

Oral vs Written Responses: What Are The Differences?

Published by Phonic on
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

Product Update: Video & Screen Recording

Published by Phonic on
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

Product Update: Understand, Visualize & Share Voice Data

Published by Phonic on
Audio is a great way to collect high quality, authentic feedback. Voice data possesses the same virtues as unstructured text, however it yields longer responses, more descriptive language and unlocks an entire world of tonal analysis for researchers. These benefits are enough to make many add aud... Read More

Product Update: Transcription in 31 Languages

Published by Phonic on
Accessibility is not a feature - it is essential to creating inclusive products. This is particularly true for survey platforms where accessibility is key to representative samples and maximal response rates.One of the benefits of collecting voice responses is improved accessibility... Read More