AnyLingual: Low-Latency Speech Translation
Direct speech-to-speech translation that keeps conversations natural
When your sales rep is on a call with a prospect and they don't share a common language, deals stall.
BLEU Score
38.58
CoVoST2 es→en
Languages
All Major
Production ready
Executive Summary
What we built
AnyLingual — a direct speech-to-speech translation system that lets two people speak naturally in their own languages, with a virtual translator handling everything with minimal delay.
Why it matters
When your sales rep is on a call with a prospect and they don't share a common language, deals stall. Human interpreters are expensive and not on-demand. Existing speech translation systems introduce 2+ seconds of delay and produce robotic output. Language barriers shouldn't be a hard stop.
Results
- AnyLingual Small: 0.76s latency — 2.5x faster than GPT-4o cascaded
- AnyLingual Large: 38.58 BLEU on CoVoST2 — best-in-class quality
- Supports all major spoken languages with bidirectional translation
- Deploys on telephony, WebRTC, and chat interfaces
Best for
- →Customer support in native languages without language-specific agents
- →Sales calls with international prospects
- →Healthcare telemedicine across language barriers
- →Global team collaboration without forcing English as default
Limitations
- Currently in pilot deployments with live users
- Quality-latency tradeoff: choose Small for speed, Large for quality
The Problem
Current solutions fall short. Each approach has different causes and different costs.
Symptom
Deals stall waiting for interpreters
Cause
Human interpreters are excellent but expensive, and not available on-demand for every call, language pair, and time zone
Business Cost
Symptom
Reading captions during calls is impractical
Cause
Text-based translation forces split attention: listening, reading, and speaking simultaneously. Exhausting on long calls.
Business Cost
Symptom
2+ second delays break conversation flow
Cause
Cascaded ASR→MT→TTS pipelines accumulate latency. Errors compound through each step. Prosody gets lost.
Business Cost
How It Works
Different approaches offer different tradeoffs. Here's how they compare.
Traditional Cascaded Pipeline
ASR → Machine Translation → TTS
- Modular and debuggable
- Higher latency (1.5-2s+) due to multiple steps
- Errors compound through pipeline
- Prosody lost when converting to text
AnyLingual Small
Encoder-decoder architecture, end-to-end S2S
- Sub-second latency (0.76s)
- 2.5x faster than GPT-4o cascaded
- Optimized for speed
- Quality comparable to cascaded systems
AnyLingual Large
Multimodal LLM + TTS synthesis
- Best-in-class translation quality
- 40% faster than cascaded pipelines
- Optimized for quality
- Generates text then synthesizes speech
Benchmark Results
Interactive explorer comparing Anyreach to baseline methods across datasets and metrics.
Baseline Comparison: BLEU
Word-level accuracy against reference translations. Higher = more accurate word choices.
| Model | BLEU | chrF++ | COMET | Latency |
|---|---|---|---|---|
AnyLingual Large | 38.58 | 62.40 | 0.86 | 1.154s |
gpt-4o-transcribe + gpt-4o | 37.61 | 61.38 | 0.85 | 1.895s |
whisper-large-v3 + gpt-4o | 37.38 | 61.93 | 0.86 | 1.483s |
AnyLingual Small | 37.23 | 61.21 | 0.85 | 0.763s |
canary-1b-v2 | 37.20 | 61.37 | 0.85 | 0.961s |
deepgram + gpt-4o | 35.33 | 60.09 | 0.84 | 1.179s |
whisper-large-v3 | 33.78 | 58.01 | 0.82 | 0.764s |
gpt-4o-audio | 26.86 | 56.12 | 0.82 | 1.228s |
Product Features
Ready for production with enterprise-grade reliability.
Two Model Options
AnyLingual Small (0.76s latency) for speed-critical applications. AnyLingual Large (38.58 BLEU) for quality-critical applications. Choose based on your use case.
Sub-Second Latency
2.5x faster than GPT-4o cascaded pipelines. Natural conversation flow without awkward pauses or interruptions.
All Major Languages
Supports all major spoken languages including Spanish, Mandarin, French, Russian, Arabic, Hindi, and many more. Bidirectional translation for all supported pairs.
Telephony Integration
Native PSTN support for voice calls. Drop into existing call center infrastructure without special hardware.
WebRTC & Chat Voice
Works with video conferencing and chat-based voice interfaces. Consistent experience across all channels.
Direct Speech-to-Speech
Translates audio directly without intermediate text conversion. Preserves tone, emphasis, and natural speech patterns.
Integration Details
Runs On
Anyreach Cloud Infrastructure
Latency Budget
0.76s (Small) to 1.15s (Large)
Providers
Telephony (PSTN), WebRTC, Chat Voice
Implementation
Pilot deployment in 1-2 weeks
Frequently Asked Questions
Common questions about our voicemail detection system.
Ready to see this in action?
Book a technical walkthrough with our team to see how this research applies to your use case.