Speaker Recognition in Deeply Audio AI solution identifies who is speaking within a second, even in noisy environments.
Speaker Verification separates the voice of a person from other voices. For instance, if you register the voice of the call center staff, you can distinguish it from the voice of other customers.
Speaker Identification distinguishes voices from people.
Emotion Analysis accurately classifies the positive and negative sentiment from a speaker's voice in real-time. This SDK & API work greatly even in low-quality audio environments such as call centers and conference calls. By using the Emotion Analysis, customer service teams can make an AI-based customer satisfaction assessment system for inbound and outbound calls in call centers, and conference call service providers can add emotion recognition feature.
Audio Event Detection
Non-verbal Sound Recognition detects non-verbal sound of people such as laugh, sigh, tut tuts, sobbing, etc. If a customer has a dataset for sound of interest, it is also possible to build a custom model that detects the sound.
We support high accuracy even in real-world environments through the process of tuning and optimizing our AI models for real-world data, and also provide the ability for customers to customize various AI inference parameters as needed.
Deeply Audio AI technology is already trusted by customers for its high accuracy and robustness even in real-world environments.
We have a lot of experience to detect special sounds in house, cars, factories, and other various environments.
Do you want to find out if audio AI technology can be applied to your project? contact us right now!