2024
Prime Minister's Award, Korea Invention Patent Exhibition
Awarded for multi-microphone speech processing technology related to mpBeamforming.
About mpWAV
We build AI voice interfaces you can trust in the real world
mpWAV is an AI voice interface technology company that helps products listen to, understand, and respond to users in real environments where ambient noise and device echo exist.
We develop the full voice stack — single- and multi-microphone enhancement, wake-word detection, sound source localization, multi-party voice processing, speaker diarization, on-device speech recognition, and a conversational language model.
Beyond algorithms, we provide what real implementation requires: microphone arrays, multi-channel audio I/O, DSP·FPGA·AP porting, and product integration.
Real-World Noise-Robust AI Voice Interface Solution
Image [C1]
Robot · Kiosk · Vehicle · Smart Device · Meeting · Factory
↓ Real-World Noise · Echo · Multiple Speakers
↓ mpWAV AI Voice Interface
↓ Listen · Understand · Respond
Who We Are
What kind of company is mpWAV?
mpWAV is an AI voice technology company that improves speech recognition and voice interface performance in real-world noise.
We connect preprocessing that refines the audio arriving at the microphone with wake-word, localization, and speaker analysis, on-device speech recognition, and conversational AI — and implement it all in the customer's software and hardware environment.
We don't stop at cleaning the audio — we connect it so the product understands the user and responds.
Official material describes mpWAV as a developer of AI voice interface software and hardware, noise-robust speech recognition, and noise-reducing speech enhancement.
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Real-World Audio → Voice Enhancement → Interaction Intelligence
→ Speech Recognition → Dialogue Understanding → Product Action
Foundation: Multi-Channel HW · DSP · FPGA · AP · Edge · SoC
Company at a Glance
From research to product — applying voice technology to reality
Founded
2020
mpWAV was founded to solve the speech recognition problems that occur in real product environments.
Business
AI voice interface SW·HW
We develop voice enhancement, voice interaction analysis, speech recognition, conversational AI, and multi-channel hardware.
Technology portfolio
10 voice technology families
mpAEC · mpBeamforming · mpAB · mpNC · mpWWD · mpS · mpLocalization · mpDiarization · mpASR · mpLLM
Product implementation
Software + HW + Embedded
From software validation to microphone arrays, DSP·FPGA·AP porting, and SoC expansion.
Key applications
Robots · Kiosks · Vehicles · Smart Devices · Meetings · Industrial Acoustics
We compose the required technology stack per product and site.
Team
11 people
Specialists in speech signal processing, AI, software, embedded systems, and hardware. (Per official company material, June 2026)
CEO
Hyung-Min Park
Leads mpWAV with research and technology commercialization experience in speech, language, and signal processing.
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2020 Founded | 10 Technologies | SW+HW | DSP·FPGA·AP Porting | 11 People (June 2026)
The Problem We Solve
Voice AI advances — but real products face different problems
Speech recognition models are advancing fast, but a real product's microphone never receives only the user's voice.
Conversation, music, road noise, motor noise, the product's own speaker echo, and overlapping speech all arrive together.
Some products cannot fit multiple microphones — and after recognition, the product still needs the user's position, the speaker's identity, intent, and dialogue context.
mpWAV technically connects the entire flow from input audio to the product's final action.
Ambient noise & far-field speech
The user's voice can be buried under conversation and household or machine noise.
Product speaker echo
Prompts and responses played by the product loop back into the microphone.
Single-microphone constraints
Earbuds and small devices often cannot fit a multi-microphone array.
Wake-up and user position
Robots and vehicles must know when — and from which direction — the user spoke.
Multiple speakers
Meetings and voice chat require separating overlapping voices and speakers.
Context and intent
Kiosks and robots must connect recognized sentences to product functions and actions.
Voice interface performance is decided not by the ASR model alone, but by input, analysis, recognition, dialogue, and product integration together.
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Robot: motor·fan | Kiosk: store chatter·prompts | Vehicle: driving·audio
Earbuds: single mic | Meeting: multi-party | Smart device: wake word·dialogue
AI Voice Technology Stack
From voice input to recognition and dialogue
Voice Enhancement
Improving voice input
- mpNC
Reduces ambient noise from a single microphone.
- mpAEC
Reduces acoustic echo from the product's speaker.
- mpBeamforming
Reduces ambient noise and strengthens the target voice with multiple mics.
- mpAB
Integrates mpAEC and mpBeamforming to handle echo and noise together.
Voice Interaction Intelligence
Wake-up, localization, and speaker analysis
- mpWWD
Detects the wake word and activates the voice interface.
- mpS
Prepares multi-party or overlapping voice input for downstream processing.
- mpLocalization
Estimates the speaker's direction or sound source position.
- mpDiarization
Separates who spoke when in multi-party audio.
Speech Recognition & Dialogue
Recognition and dialogue understanding
- mpASR
On-device end-to-end speech recognition converting voice into text or product commands.
- mpLLM
Analyzes intent and context of recognized sentences, connecting them to product functions and dialogue flow.
Product Implementation
Implementation foundation
- Multi-channel microphone arrays
- Speaker output & AEC reference
- DSP·FPGA·AP
- Edge AI
- Semiconductor IP·SoC
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Voice Enhancement: mpNC · mpAEC · mpBeamforming · mpAB
↓ Interaction: mpWWD · mpS · mpLocalization · mpDiarization
↓ Recognition & Dialogue: mpASR · mpLLM
↓ Implementation: HW · DSP · FPGA · AP · Edge · SoC
Why mpWAV
Integrated voice interface technology built for real products
Noise control that preserves the target voice
If noise reduction damages the user's voice along with the noise, recognition performance can drop.
mpWAV designs its technology to reduce ambient noise while minimizing target-voice distortion and recognition loss.
Less repeated per-product tuning
We optimize from the actual input signals rather than fixed microphone position data, reducing the repeated tuning burden when microphone configurations change.
Single- and multi-microphone coverage
Products with an array use mpBeamforming and mpAB; small products that cannot add microphones use mpNC.
From input to recognition and dialogue
Beyond preprocessing, we connect wake word, localization, speakers, ASR, and LLM as one voice interface architecture.
Works with your existing ASR
You don't have to replace your recognition engine — mpWAV preprocessing applies in front of it.
Software and hardware together
Beyond algorithms we cover microphone arrays, audio I/O, and FPGA·DSP·AP porting.
Official material presents minimal target-voice distortion, input-signal-based auto-optimization, reduced tuning when microphone configurations change, and software-hardware integration as key characteristics.
| Product development challenge | mpWAV approach |
|---|---|
| Voice damaged during noise removal | Preserve target voice, consider ASR results |
| Re-tuning when microphones change | Auto-optimization from input signals |
| Single-microphone product constraints | mpNC single-mic coverage |
| Preprocessing only | Wake·location·speaker·ASR·LLM connected |
| Full ASR replacement burden | Applies in front of existing ASR |
| SW and HW developed separately | Arrays and porting integrated |
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Six challenge ↔ approach pairs
From Research to Product
Connecting research results to real product voice experiences
mpWAV's technology is grounded in long-term research in speech and audio signal processing and speech recognition.
Technology validated in papers and patents expands into software, AI models, FPGA·DSP implementations, microphone array modules, and industrial PoCs.
- 1
Research
Speech/audio signal processing and noise-robust speech recognition.
- 2
Patent
Core algorithms and implementation technology protected as domestic and international IP.
- 3
Software·AI
Implemented as voice enhancement, interaction, recognition, and conversational AI.
- 4
Embedded·Hardware
Transferred to real products via FPGA·DSP·AP and microphone arrays.
- 5
Industrial PoC
Validated with real product data and usage environments.
- 6
Product·Scale-up
Expanded as software, modules, licenses, and semiconductor IP.
Research → Patent → Algorithm → Embedded System → Product
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Academic Research → Patent → Software·AI Model → FPGA·DSP·AP → Industrial PoC → Product·SoC
Applications
The right voice technology for each product and site
Robots
Wake-word detection, user direction estimation, motor/fan noise and robot speaker echo processing, connected to commands and dialogue.
mpWWD · mpLocalization · mpAB · mpASR · mpLLM
Kiosks
Captures far-field voice in store noise, recognizes menus and options, and connects to conversational ordering.
mpAB · mpASR · mpLLM · Mic-Array HW
Vehicles & mobility
Handles wake word, seat/speech direction, driving noise, and car audio echo.
mpWWD · mpLocalization · mpAEC · mpBeamforming · mpASR
Smart devices & earbuds
Single-microphone enhancement and on-device commands for products that cannot add microphones.
mpNC · mpWWD · mpASR · mpLLM
Meetings & voice chat
Processes multi-party or overlapping voices and structures per-speaker utterances and meeting content.
mpS · mpDiarization · mpAEC · mpASR · mpLLM
Factory acoustic inspection
Analyzes normal and abnormal acoustic patterns of motors and equipment amid complex production noise.
Noise-Robust Acoustic Processing · Anomaly Detection
Hearing assistance
Applies voice enhancement to everyday conversation and public hearing welfare through ClearSense Audio.
mpNC · Speech Enhancement
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Robot | Kiosk | Vehicle | Earbuds·Smart | Meeting | Factory | ClearSense
Implementation Experience
Validated in real products and real sites
Robot ASR preprocessing
Official material presents validation experience in home robot, showroom robot, and care robot environments.
Kiosk module
Multi-channel microphone array I/O and ASR preprocessing module deployments are presented.
Mobility PoC
Reviewed voice interface applicability and global expandability in real noise environments.
Factory anomaly detection
Validated detecting abnormal motor sounds amid complex production noise without a separate test chamber.
Hearing assistance
Reviewed smartphone- and earphone-based voice enhancement in welfare center environments through ClearSense Audio.
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Robot voice test | Kiosk linear array | In-vehicle data
Factory motor measurement | ClearSense in use | FPGA·DSP boards
Engineering Capabilities
We run the algorithms inside real products
Software·SDK
Integrates mpWAV technology into existing systems or in front of ASR.
AI Model
Fits mpWWD, mpASR, and mpLLM to the target product and domain.
Mic-Array HW
Designs multi-channel microphones, speaker output, and AEC reference structures.
DSP·FPGA·AP Porting
Optimizes for real-time execution on the product's compute platform.
License·Co-development
Designs collaboration structures around per-product data and requirements.
Semiconductor IP·SoC
Expands into dedicated structures for volume production and miniaturization.
Official material presents real-time FPGA implementation, MCU+DSP, AP·DSP porting, microphone array design, and dedicated SoC expansion.
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Technology → Software/AI Model → Mic Array/Audio HW → DSP·FPGA·AP → Product Integration → License·SoC
Research-Driven Team
A team with 25+ years of research and product implementation capability
mpWAV is a specialist team connecting speech and language research, AI models, software, embedded systems, and hardware development.
CEO Hyung-Min Park earned his B.S., M.S., and Ph.D. in Electrical Engineering at KAIST, with research and teaching experience at Carnegie Mellon University's Language Technologies Institute and Sogang University.
- 25+ yrs
- Speech, language & signal processing research
- 70+
- International journal papers in speech and signal processing
- 40+
- International conference papers
- 50
- Cumulative patents of the core researchers
- 16
- Technology transfers to industry
- 60
- Academic, industrial & government research projects
These figures are the cumulative record of the founding researchers as presented in official material — separate from mpWAV's corporate patents listed below.
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Speech Processing | AI Model | Embedded System | Hardware Design | Product Engineering
Intellectual Property
Core technology protected by domestic and international IP
mpWAV's corporate intellectual property holdings:
Korean patents
7 registered · 3 pending
International patents
7 registered · 10 pending
Trademarks
2 Korean · 2 international
Design rights
4
These figures are for the mpWAV corporation — separate from the 50 cumulative patents of the founding researchers, which include prior institutional work.
Per official company material (June 2026)
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Korea·US·China·Europe | Registered & pending | mpAEC·mpBeamforming patent fields
Awards and Certifications
Research results and competitiveness, confirmed by awards and certifications
2025
NET New Technology Certification
Certified by the Ministry of Trade, Industry and Energy for real-environment voice interface preprocessing.
2026
Innovative Product for Public Procurement
ClearSense Audio was designated an innovative procurement product, establishing a base for public sector deployment.
2024
CES 2024 Innovation Awards, two categories
Recognition for ClearSense Audio, which applies mpWAV voice enhancement to everyday listening.
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PM Award trophy | NET certificate | Procurement designation | CES Innovation badge
Milestones
Expanding from research to products and markets
2020
mpWAV founded
Began commercializing noise-robust AI voice interface technology for real environments.
Product & technology
From preprocessing to the full interface stack
Expanded from mpAEC, mpBeamforming, and mpAB into single-mic noise control, wake word, localization and speaker analysis, speech recognition, and conversational AI.
2024
Prime Minister's Award
Recognized for the inventiveness of multi-microphone speech processing technology.
2025
NET New Technology Certification
Certified for real-environment voice interface preprocessing.
2026
Public market and hearing welfare expansion
Expanded the business base around ClearSense Audio and public procurement.
Next
Global products and semiconductor IP
Broadening into robots, kiosks, mobility, smart devices, and meetings, while pursuing a dedicated SoC.
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2020 Founded → Core Voice Processing → 2024 PM Award
→ 2025 NET → 2026 Public Market → Global · Semiconductor IP · SoC
Business Model
Collaboration models for every product and development stage
Software·SDK
Individual technologies or the full voice interface stack applied to your product.
AI Model
mpWWD, mpASR, and mpLLM fitted to your product and domain.
Microphone array module
Multi-channel voice input hardware designed for robots and kiosks.
DSP·FPGA·AP porting
Implemented to run on your product's compute platform.
Technology licensing
Voice enhancement, interaction, recognition, and industrial acoustic analysis.
Joint development
Microphones, preprocessing, ASR, LLM, and product APIs connected in one project.
Semiconductor IP·SoC
Dedicated voice interface structures for volume production and miniaturization.
Official material presents software and microphone array modules for robots and kiosks, chips for vehicles, consumer devices, and defense, and factory anomaly detection licensing as its business models.
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SW·AI Model | Mic-Array Module | Porting | License | Co-Dev | Semiconductor IP·SoC
→ Robot · Kiosk · Vehicle · Smart Device · Meeting · Factory
Global and Technology Roadmap
Real-environment voice technology, to more products and global markets
Building on voice interfaces for robots, kiosks, and mobility, mpWAV is expanding into smart devices, meetings and voice chat, and hearing assistance.
The following is a roadmap the company is pursuing — not completed results.
1
Core Applications
Robots · Kiosks · Mobility
Strengthening preprocessing and product integration for real noise environments.
2
Expanded Applications
Smart Home · Hearing Assistance · Meetings · Voice Chat
Applying single-mic technology, speaker analysis, recognition, and conversational AI to new product lines.
3
Global Products
International business and language expansion
Scaling language-independent preprocessing and on-device models into global products.
4
Semiconductor Platform
Semiconductor IP · dedicated SoC
Pursuing semiconductor collaboration for volume production and miniaturization, built on FPGA·DSP implementations.
Real-World Voice Technology for Global Products
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Core: Robot·Kiosk·Mobility → Expanded: Smart Device·Meeting·Hearing
→ Global Voice Platform: Software·Edge AI·Semiconductor IP·SoC
Our Vision
So people and products can converse naturally — even in the real world
The voice interface mpWAV pursues is not technology that only works in a quiet lab.
Amid conversation, music, vehicles, and machine noise, products must hear the user's call, know their position and identity, and understand intent and dialogue context.
mpWAV connects input enhancement, interaction analysis, on-device recognition, and conversational AI to deliver voice experiences you can trust in real environments.
Reliable voice interfaces for every product, in the real world
Reliable AI Voice Interfaces for the Real World
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Person ↔ Robot · Kiosk · Vehicle · Smart Device · Meeting (connected by one waveform)
Company Information
mpWAV company information
| Company | mpwav Inc. |
|---|---|
| Korean name | (주)엠피웨이브 |
| CEO | Hyung-Min Park |
| Founded | 2020 |
| Business | AI voice interface software & hardware |
| Technology | Voice enhancement · Interaction · ASR · LLM · Multi-channel HW |
| info@mpwav.com | |
| Phone | +82-2-705-8916 |
| Headquarters | Teilhard Hall 405, 35 Baekbeom-ro, Mapo-gu, Seoul, Korea |
| Business registration | 859-81-01905 |
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Office | R&D space | Acoustic testing | Board development | Building·map
FAQ
Frequently asked questions about mpWAV
mpWAV is an AI voice technology company that improves product voice interfaces in real-world noise.
We develop voice enhancement, wake-word detection, localization and speaker analysis, on-device speech recognition, a conversational LLM, and multi-channel hardware.
Noise and echo reduction are part of our core technology.
The full portfolio spans mpNC, mpAEC, mpBeamforming, mpAB, mpWWD, mpS, mpLocalization, mpDiarization, mpASR, and mpLLM.
mpNC handles single-microphone noise control for earbuds and small smart devices that cannot fit an array.
Quantitative performance and supported platforms should be validated under real product conditions.
We develop mpASR, an on-device end-to-end speech recognition technology, and mpLLM, a 1B-class on-device dialogue model direction.
Actual runtime performance depends on model version and target platform.
mpS and mpDiarization can process multi-party audio and separate per-speaker segments.
Both.
mpWAV connects voice algorithms and AI models with microphone arrays, multi-channel audio I/O, and FPGA·DSP·AP porting.
Per official company material (June 2026): 7 Korean patents registered and 3 pending, 7 international patents registered and 10 pending.
No.
The 50 patents are the cumulative record of the core researchers, listed separately from mpWAV's corporate patents.
We have deployment or validation experience in robots, kiosks, mobility, factory acoustic inspection, and hearing assistance.
Smart devices, meetings and voice chat, and defense are expansion areas built on our existing technology.
Depending on the product and project, we can consider software, AI models, microphone arrays, porting, technology licensing, joint development, and semiconductor IP collaboration.
Work with mpWAV
Build AI voice interfaces that work in the real world — with us
Tell us your product type, microphone and speaker structure, dominant noise, required voice features, and target platform — we will review the right mpWAV technology and collaboration model.
From single-mic noise control to multi-channel echo and noise processing, wake·location·speaker analysis, on-device ASR and conversational LLM, microphone arrays and DSP·FPGA·AP porting — start at whatever stage your product is in.
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Research·Technology → AI Voice Stack → Engineering·Integration → Customer Product → Real-World Voice Experience