Convert speech to text for instant transcriptions of audio/video recordings. Identify, measure and quantify emotions in human voice. A proprietary speech emotion recognition technology powered by Emotion AI, ML, and NLP.
Our automatic speech recognition technology is easy and scalable to generate accurate transcriptions in real-time. Without any additional hardware, you can also identify the emotions hidden in voice tonalities.
Our speech-to-text conversion happens in real-time and is more than 95% accurate, to be reliably used in scale, especially in Qualitative Research.
Leverage the science of AI, Machine Learning and NLP to measure and quantify the emotions hidden in voice tonalities and speech acoustics.
Either use live audio from phone/video calls or upload calls recorded from normal laptop/mobile microphones. You don't need any additional hardware.
enterprise customers across the globe
global patents on Emotion AI
repository of emotion benchmark data
You get real-time transcriptions of audio recordings with our technology with more than 95% accuracy. These transcripts are also assigned a timestamp and marked against the different people in the audio. However, no PII is captured.
Along with speech to text, our Voice AI technology goes one step further to analyze subtle emotions hidden in speech acoustics and voice tonality. And measures, quantifies as well as classifies voice variations into 7 universal emotions.
In order to access Entropik Tech's Voice AI technology, you don't need any additional hardware. All you have to do is turn on your microphone and record your voice. Or just upload an mp3 of your old audio recordings.
Here's how simple and easy it is to leverage our Voice AI technology to get instant transcriptions and speech emotion analytics.
Turn on necessary microphone recordings to capture your voice or uploaded mp3 files of pre-recorded audio recordings.
Get accurate transcriptions populated instantly with timestamps against the different voices heard in the audio.
Get emotion insights of voice recordings for each individual and summarize these emotions as positive, negative and neutral.
To extract deeper human insights, combine Voice AI with Facial Coding and Eye Tracking technologies.
