AI Voice Engineering Services
mpWAV applies single- and multi-microphone enhancement, wake-word detection, sound source localization, speech separation, speaker diarization, on-device speech recognition, and a conversational LLM to your product.
From PoC on your real audio data through software integration, DSP·FPGA·AP porting, microphone array and multi-channel hardware design, model optimization, licensing, and dedicated SoC collaboration — engineering services matched to your development stage.
From Technology to Your Product
Our engineering services validate and integrate our voice algorithms and AI models so they run on your real product data, your microphone and speaker structure, and your compute platform.
Rather than handing over algorithm or model files, we review the entire data flow — input capture, preprocessing, wake·location·speaker analysis, recognition, dialogue understanding, and product API execution.
We turn an algorithm's potential into your product's real performance.
Service Portfolio
Confirm the effect on your real product data
We analyze single/multi-channel audio collected from your product and your current recognition results, comparing before and after mpWAV technology.
Covers
Connect the voice technology you need to your product
Apply a single module, or integrate the full software stack from preprocessing to recognition and dialogue.
Typical structures
Wake word, recognition, and dialogue inside the product
We review the feasibility of running mpWWD, mpASR, and mpLLM under your product's CPU·GPU·NPU and memory conditions.
Scope
Move validated technology to your target platform
We optimize technology proven on PC or reference environments to run in real time on your DSP, FPGA, or AP.
Scope
From voice input to the processing board
We connect the microphone array, speaker output, AEC reference, multi-channel audio I/O, and compute platform into one product structure.
Scope
Technology designed jointly around your product and data
When per-product optimization matters more than a standard module, we collaborate through algorithm licensing, AI model application, or co-development.
Scope
Dedicated voice interface structures for volume production
Building on FPGA·DSP validation, we review semiconductor IP or dedicated SoC collaboration for products that need power, size, and cost optimization.
Collaboration type
Proof of Concept
Voice technology performance depends on microphone count and layout, user distance, noise, speaker output, number of talkers, your existing ASR, and the execution platform.
mpWAV evaluates before-and-after results against data collected from your actual product rather than generic demo audio.
Software Integration
Depending on your product's current structure and required features, apply a single module or integrate several technologies into one continuous pipeline.
Microphone → mpNC / mpAEC / mpBeamforming / mpAB → Existing ASR
Improves input quality without replacing your recognition engine.
mpWWD → mpLocalization → mpAB → mpASR → mpLLM → Robot Command
Connects wake-up, speech direction, noise/echo preprocessing, recognition, and dialogue.
Mic Array → mpAB → mpASR → mpLLM → Ordering API
Voice ordering and conversational option confirmation in store noise.
Single Mic → mpNC → mpWWD → mpASR → mpLLM → Device Function
For earbuds and small devices that can't add microphones.
mpAB → mpSeparation → mpDiarization → mpASR → mpLLM → Transcript / Summary
Connects multi-party processing, speaker separation, records, and summaries.
On-Device/On-Premise/Cloud AI Optimization
An on-device voice interface is not decided by model accuracy alone.
Wake-word detection, recognition, and the dialogue model must be reviewed as one execution structure against your product's memory, CPU·GPU·NPU, power, response time, and update method.
Wake-word detection
On-device speech recognition
Dialogue and intent understanding
Input preprocessing
Depending on your microphone conditions, the following applies as the front end:
Key review metrics
Microphone array
takes your product’s existing mic configuration
Preprocessing
mpNC and mpAB remove noise and echo
Recognition and dialogue
mpWWD, mpASR, and mpLLM follow on
Product action
hands the result to your product API
Embedded Porting
Applying technology proven in a reference environment to a real product requires porting matched to the target processor's compute, memory, audio interfaces, and latency.
On-device multi-channel real-time processing
OS and product service integration
AI models and preprocessing together
Multi-Channel Hardware Integration
Applying multi-microphone technology to a real product means designing mic count and layout, channel synchronization, speaker output, the AEC reference, and the compute board together.
mpWAV brings experience with linear and circular arrays, USB multi-channel audio I/O, FPGA·DSP·AP connections, and integrated noise-refinement speech preprocessing.
Representative design cases
Licensing and Co-Development
Every product differs in microphones, users, noise, compute platform, and service goals — a standard package cannot solve everything.
mpWAV negotiates licensing, model optimization, or co-development scope based on your real data and product requirements.
Applied to your product's single- or multi-microphone input.
Connects wake word, user direction, multi-party voice, and speaker information to product functions.
Reviewed for your domain vocabulary, menus, command sets, and product APIs.
Co-develops analysis models using per-product acoustic data — such as factory equipment anomaly detection.
Microphone arrays, audio I/O, preprocessing, recognition, dialogue, and product APIs in one project.
Technology proven in the first product extended to other mic configurations, platforms, product lines, and languages.
Semiconductor IP and SoC Partnership
Vehicles, smart devices, and volume products must weigh size, power, and cost alongside algorithm performance.
Building on software algorithms, real-time FPGA processing, and multi-channel hardware implementation, mpWAV reviews IP·SoC collaboration with semiconductor companies and volume customers.
Technology blocks under review
Fields under review
Service Packages by Application
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Find the Right Service
| Current situation | Recommended service |
|---|---|
| We want to confirm the effect of mpWAV technology first | PoC & validation |
| We want to connect a technology module to an existing product | Software integration |
| We want wake word, ASR, and LLM running inside the product | On-device AI optimization |
| Our target DSP·FPGA·AP is already fixed | Embedded porting |
| We need a microphone array and audio board | HW integration |
| We need per-product data and long-term collaboration | Licensing·co-development |
| We need a dedicated chip for volume production | SoC·IP partnership |
From Requirement to Deployment
The following is a typical example — the actual sequence and scope are adjusted per project.
Wake word, commands, dialogue, meeting records, listening improvement, or anomaly detection — we scope what you need.
Microphone count, speakers, user distance, number of talkers, the noise environment, and the target platform.
Single/multi-channel raw audio, the AEC reference, ground-truth text, and existing results.
Select the required technologies and processing order from the full mpWAV portfolio.
Confirm before/after performance and product features on PC or an evaluation environment.
SDK, model optimization, mic array, DSP·FPGA·AP porting, or licensing.
Connect audio input, mpWAV technology, your existing ASR, mpASR·mpLLM, and product APIs.
Tune latency, memory, compute, power, and model size.
Confirm results and user experience on the real product, where it's used.
Licensing, updates, follow-on products, international deployment, and SoC expansion.
Project Deliverables
The following are typical examples — actual scope is agreed per project under the development and licensing terms.
Implementation Experience
ASR preprocessing validated for home, showroom, and care robots
Multi-channel array I/O and ASR preprocessing structures deployed
Vehicle and mobility voice interfaces reviewed in real noise
Motor anomaly detection validated amid complex line noise
ClearSense Audio applied in welfare center environments
Real-time FPGA, MCU+DSP structures, and AP·DSP porting
Project Information
You don't need every item confirmed to start — share the voice problems your product hits most often and the features you're aiming for.
You don't need every item confirmed to start — share the voice problems your product hits most often and the features you're aiming for.
FAQ
All ten.
mpNC, mpAEC, mpBeamforming, mpAB, mpWWD, mpSeparation, mpLocalization, mpDiarization, mpASR, and mpLLM.
Delivery form — licence, porting, or joint development — and contract terms differ per technology and are agreed per project.
Yes.
Starting from your product structure and typical usage scenarios, we can design the required data channels, recording conditions, and ground-truth format first.
Yes — the PoC is designed around that.
We leave the engine you run today untouched, put mpWAV preprocessing in front of it, and compare before and after on the same data to show the gain.
Because nothing is changed on the engine, your original system is still intact if the result falls short.
Yes. mpNC is our noise removal technology built for single-microphone products.
It exists for earbuds and wearables, where a microphone array will not fit.
How far it goes depends on your compute budget and target platform, so we confirm against real product conditions.
Yes — a microphone array, mpAB, mpASR, and mpLLM connected together.
Store noise and prompt echo are removed first, then menu, options, and quantity are interpreted and handed to your ordering API.
To start we need menu data, a dialogue policy, and the target hardware.
Yes.
mpSeparation splits overlapping speech by speaker, mpDiarization works out who spoke when, and mpASR turns each speaker's audio into text.
Yes — porting and real-time optimization together.
Whether a specific chipset is supported comes down to compute resources, the toolchain, and audio interfaces.
Yes.
We design USB audio interface boards with multi-channel microphone array input, multi-channel AEC reference input, and a digital amplifier for speaker output.
Whether you get a standard module or a custom design depends on the project.
There is no fixed standard duration or price.
They are agreed per project based on the technologies applied, data readiness, target platform, hardware scope, optimization level, and field validation scope.
Start Your AI Voice Project
Tell us your product type, mic·speaker structure, noise environment, required features, and target platform — we will scope the right mpWAV technology and services.
From single-mic and multi-channel noise-removal preprocessing to per-speaker separation and diarization, speaker direction estimation, on-device wake-word detection and recognition, a conversational LLM, FPGA·DSP·AP porting, and SoC expansion — start at whatever stage your product is in.
