Voice Based Autonomous Access Control Terminals HEXIUM Technical Development Co., Ltd. 2003
Table of Contents Introducing Hexium Ltd. The problem Access control Biometrics Voice-print properties Innovation Preliminary market analysis Summary
HEXIUM Technical Development Co., Ltd. Research, development, production (hardware, software) Security control, image processing, industrial measurement, signal processing and automation
The problem Communication network TriMedia Terminal Server RS485 1.Physical access/time control 2.Inexpensive, reliable, fast, user-friendly
Issues with ownership based access control What to identify? a card? a keyword? a PIN code? … and NOT the PERSON! Gives rise to abuse..
Biometrics Identification of human subjects based on Physical parameters Behavioral parameters Examples: Fingerprint, iris, face, ear, hand Signature, voice
Comparision of biometrics MethodRecognitionUser acceptance User friendliness Difficulty/ method of abuse Fingerprint*********Sensor dependent Signature******* Learning Face*****^Masks Retina/iris**** Hand*********Sensor dependent Voice***^**** Sensor and system dependent
But.. Issues with biometrics Expensive sensors Poor acceptance by users due to.. Uncomfortable use Mistrust Precision, reliability Recall Slow processing
Properties of voice Identitity verification: Speaker dependent features (speaker verificaton) Message verification: Message dependent features (speech recognition) Properties Speaker independent but content dependent Speaker dependent, independent of the message
Voice-print properties The figures show the spectogram of a sentence spoken twice by the same person Both the rhythm (a behavioral property) and the spectral distribution of identical sounds (physical parameters) stay remarkably constant. People are generally good at copying behavioral patterns (a behavioral property), but is is impossible for them to copy the physical “layout” of sounds. Speech of different people show vastly different rythmic and spectral patterns.
Issues with speaker verification Noisy environment People staying close Takes time (dialogue) Goal: scaleable, multi-layer system FAR 0.01% % FRR small (below 1%) FAR: false acceptance rate FRR: false reject rate
Innovation Advanced noise filtering “Liveness” verification using array microphones Optimized implementations Robust dialogue design minimizing the error rate Multi-model user interface Open system architecture
Preliminary market analysis IDC Access control, 2002: USD 4.2M Biometrics, only banks, 2004: USD 1,800M We are here..
Summary Advanced, autonomous voice based access control terminals Competitive technology Better acceptance than that of competing biometrics technologies Growing market demand
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