Speech, music, silence or other
Use case examples:
Contact Centers: speaker share, cross-talk, talk-to-listen share, hold music detection.
Conference tools: Speech, silence and noise detection.
Robotics and Voicebots: Detect speech in challenging environments.
Telemedicine: Patient-doctor talk time.
Male, female, unknown
Use case examples:
Gaming community: identify female from male gamers to prioritize toxicity detection.
Conference tools: promote inclusivity by mapping gender-wise speaker share.
Robotics and Voicebots: further personalize interactions and vocabulary used by detecting the speaker's gender.
high, medium, low
Use case examples:
Contact Centers: track agent engagement levels, enable real-time coaching to promote agent engagement.
Gaming community: map out gamers energy level to find patterns in toxicity behavior.
Conference tools: detect energy levels in a conversation to infer which topics lead to high engagement, and gauge the motivation level of team members.
Robotics and Voicebots: further personalize interactions and vocabulary used by detecting the speaker's energy levels.
With the arousal model you are able to get a highly reliable classification of someone's voice energy. Low energy can be related to negative emotions: sadness, lack of interest, boredom. High energy can be related to both positive (happiness) or negative (irritation) emotions.
Read our docs
happy, irritated, netural, tired
Use case examples:
Gaming community: detect negative interactions between community members (angry, hateful and aggressive) to prioritize toxicity detection.
Conference tools: detect negativity interactions between team members, prioritize mental well-being, and promote work-life balance.
Robotics and Voicebots: detect moods and adapt responses to adjust empathy.
EU Languages: EN, ES, FR, DE, IT, and unknown
Use case examples:
Contact Centers: detect multilingual conversations between customers and agents.
Robotics and Voicebots: detect language and adapt responses to the language when applicable.
Speaker 1, Speaker 2... etc.
Use case examples:
Conference tools: speaker separation in mono files, cross-talk.
Robotics and Voicebots: speaker recognition based on speaker's voice print recording.