CrystalSound

Crystal-clear voice. AI-enhanced, enterprise ready.

The audio intelligence layer behind every NamiTech solution.

Before

Input

Original Audio

AI Enhancement

After

Enhanced

AI-Enhanced Audio

Overview

Every NamiTech product, from voice biometric authentication with VoiceDNA to compliance recording with VoiceGate, depends on one foundation: audio clean enough for AI to act on.

CrystalSound is the speech enhancement engine that makes that possible. Built on a unified neural model trained on real enterprise acoustic environments in Vietnam and Japan, it processes six enhancement tasks simultaneously on a single audio stream, removing noise, echo, reverb, and degradation at the source before any downstream AI process begins.

What it does

Poor audio quality is a silent multiplier of every contact centre problem. Transcription errors, failed biometric verifications, and missed compliance keywords mostly trace back to an audio signal that was never clean to begin with.

CrystalSound eliminates this root cause, delivering full-band, AI-ready audio in real time, at low speech distortion, on device, across every channel and every deployment environment.

Key Features

Noise Suppression
Real-time reduction of background noise, crowd sound, and environmental interference, while preserving the natural characteristics of the speaker's voice that can improve recognition accuracy. Trained on the acoustic conditions of Vietnamese and Japanese enterprise telephony and retail environments.
Echo Cancellation
Acoustic echo and double-talk eliminated during live calls and meetings, without degrading voice clarity. Designed for contact centre headsets, remote work setups, and noisy branch counters.
Dereverberation
Room reverberation cleared to make speech easier to hear and process. Critical for branch counter microphones and in-store deployments where room acoustics are variable.
Packet-Loss Concealment
Continuous speech maintained when network conditions are weak or unstable, reconstructing signal interruptions in real time without perceptible artefacts.
Bandwidth Extension
High-frequency detail restored to support fuller, clearer voice quality, particularly in telephony environments where bandwidth compression degrades audio.
Personalised Voice Extraction
Voice-ID embedding used to isolate and enhance a single registered speaker's voice while suppressing other voices in the stream. Speaker-targeted enhancement, not a fixed filter.

Six Tasks. One Model.

A unified neural model performs all six enhancement tasks on a single audio stream simultaneously, instead of chaining six single-purpose filters. This reduces processing complexity while keeping the audio stream clear, low-latency, and responsive during live interactions.

Technology Edge

Built for real-world enterprise conditions — not laboratory audio.

CrystalSound is designed to operate reliably in real deployment environments, where audio is noisy, inconsistent, and resource-constrained. Its unified model architecture processes multiple enhancement tasks in a single pass, eliminating the compounding latency and quality loss of traditional filter chains.
On-device processing ensures audio is enhanced locally without leaving your secure perimeter, supporting both low-latency performance and privacy-sensitive deployments. Optimised model variants enable flexible deployment across cloud, on-premises systems, and resource-constrained devices.

Why It Matters Across The Platform

CrystalSound is the prerequisite layer for the entire NamiTech stack:

VoiceDNA voice biometric enrolment and verification require clean audio to reach target accuracy levels.
NamiGen AI Agent conversation quality and intent detection improve directly with audio clarity.
NamiSense Agent Scoring and QA results are more accurate when transcription quality is higher.
VoiceGate compliance recordings are legally stronger when the audio is clear and artefact-free.
NamiSense Anywhere branch and retail deployments depend on microphone audio quality at the point of contact.

Technical Specifications

Architecture
Unified neural model, six tasks, single audio stream, real-time inference
Enhancement tasks
Noise suppression / Echo cancellation / Dereverberation / Packet-loss concealment / Bandwidth extension / Personalised voice extraction
Processing
Real-time on-device streaming and batch
Deployment
On-device (desktop, mobile, edge) / Cloud (GCP, Azure, AWS) / Embedded SDK
Hardware
Device-agnostic; optimised variants support resource-constrained devices