What is acceptable between adults might not be the same with children. Look out for your underage community and track any suspicious or unsafe situations around them.
Quickly detect situations of cross-gender harassment in your community based on your member’s voice gender.
Map the patterns and behaviours of your community with their negative and positive expressions.
Use acoustic intelligence to set, improve, or calibrate your Safety & Trust policies.
Happy voices shape community engagement. Promote systemic change by rewarding good behaviour in the community with the appreciation they deserve.
SafeVox uses unique voice intelligence to capture tone and other markers such as laughter, screaming, and high emotions, among many other acoustic biomarkers. Make better predictions and spot problematic behaviour faster with a simple solution that scales with and adapts to the diversity of your community.
AI extracts information from voice in any language and labels acoustic events in the most relevant way.
AI determines conversational risk based on key behaviours between speakers, and highlights when vulnerable speakers are present.
For richer analytics, keyword spotting or transcription is applied to targeted segments.
Content moderators can get to an accurate decision faster when presented with summaries of acoustic intelligence and most important highlights on speaker activity.
The market’s most powerful audio moderation tool that uniquely combines the acoustic (tone) and semantic (words) modalities for superior accuracy and automation capabilities.
“The problem was HOW you said it!”
Context is everything, more so with cross-culture communities. Human vocal expressions are universal enough to give you an understanding of how people “feel” during social interactions.
Get a better sense on the impact of someone's behavior, regardless of their intent.
“Well... That escalated quickly!”
Get an immediate sense of the speakers' emotional journey before even clicking "play". From hot to cold zones, you can detect hotspots in the conversation to guide your analysis.
“Why do you speak to her like that bro? She's alright!”
Narrowing down intent and meaning behind words becomes exceptionally hard and nuanced in cross-gender interactions, more so when one is a relative minority in a community.
“Dude, you’re talking to a kid, chill!”
Don’t rely on online social justice warriors to protect the vulnerable members of your community.
“What is this horrible noise? Mute!”
Get real-time information when audio disruption impacts the quality of the conversation. Intentional or not, the presence of disruptive noise negatively affects the user experience.
Near real-time analysis on recorded audio streams to support human moderation.
Review difficult cases and fine-tune the system for continuous improvements.
Real-time analysis on live audio streams to support automated moderation.