↑30% Turn Detection Accuracy
More precise end-of-speech detection for better response timing.
SEE ORPHEUS SDK IN ACTION
Experience how raw audio is transformed into structured, machine-ready input in real time.
Main speaker
.......HiIlike...thoseschedulestomorrowmorning.........................MyconfirmationnumberisAX402..and......canyoualsoswitchmetoanhonesty..andCindyupdatedeachothertomymeal.Thankyou.
Background:
.......shhh,don'tcryLili,don'tcry,.......mommy'sgonefor5min........She'llbebacksoon........shhh,don'tcry............................
Works across all languages
MEASURED IMPACT ON MACHINE PERFORMANCE
↓40% Fewer Interruptions
Prevents systems from speaking over users.
More Accurate Response Timing
Systems respond at the right moment, not too early or late.
↓WER in Overlapping Speech Scenarios
Better turn boundaries reduce transcription errors in real-time audio.
FROM UNSTRUCTURED SPEECH TO CONTROLLED CONVERSATION FLOW
Real-time conversations break when systems don't know when to listen or respond.
Conversation Timing Breaks in Real Time
Systems struggle to detect when users finish speaking, leading to interruptions, delays, and unnatural interaction.
- Systems interrupt users or respond too early
- Delayed responses create unnatural pauses
- Overlapping speech confuses ASR and agents
- No clear end-of-speech signals in real time
Your models are only as good as your timing.
Detect Turns. Control the Flow. Respond at the Right Time.
Hecttor detects end-of-speech in real time, enabling systems to respond precisely without overlap or delay.
- Identifies end-of-turn with high precision
- Enables natural, interruption-free responses
- Reduces latency in response triggering
- Works in real time across live conversations
Clean timing. Natural flow. Reliable interaction.
How turn-taking model works
From raw, overlapping audio to clean, structured input ready for transcription, analytics, and voice AI.
Real-time by design
Analyzes conversation flow instantly, enabling natural interaction without delay or post-processing.
Detects speaker turns and boundaries
Identifies when speakers start, stop, and overlap, even in fast or unstructured conversations.
Handles overlap and interruptions
Resolves competing speech so systems can follow the conversation reliably.
Optimizes response timing for AI
Enables voice agents to respond at the right moment, avoiding delays, cut-offs, or double-talk.
A REAL-TIME SYSTEM FOR MACHINE-READY AUDIO
Three layers working together before ASR to produce clean, structured input.
WHERE TURN-TAKING MATTERS MOST
Designed for environments where overlapping speech, noise, and unclear audio break transcription, analytics, and voice AI systems.
Voice AI and conversational agents
Ensure natural interaction with clear turn boundaries and accurate response timing.
Analytics and transcription systems
Precise speaker timing and interaction flow for better context and insights.
Customer support and call centers
Fewer interruptions, smoother conversations, and more efficient communication.
Voice platforms and telecom systems
Consistent conversational structure across large-scale, real-time communication systems.
Built for Machine Pipelines, Not Listening
Hecttor Orpheus SDK sits between raw audio and ASR, structuring speech before it reaches downstream systems.
- Processes audio before transcription
- Delivers structured input for AI systems
- Requires no changes to your architecture
- Runs in real-time streams
FREQUENTLY ASKED QUESTIONS
What is turn-taking in voice AI?
Turn-taking is the ability to detect when a speaker has finished so the system knows when to respond. It ensures conversations flow naturally without interruptions or delays.
Does turn-taking affect ASR accuracy?
Yes. Accurate turn detection reduces overlapping speech and misaligned segments, which improves transcription quality in real-time systems.
Is turn-taking different from VAD?
Yes. VAD detects whether speech exists. Turn-taking determines when speech ends so the system can respond at the correct moment.
How does Hecttor turn-taking work?
Hecttor detects end-of-speech in real time and triggers responses at the right moment, preventing overlap and reducing latency in live conversations.