Control any device to respond to your and only your voice
Personalize your experience with our AI based speaker ID. With an identification accuracy of more than 95% with very low CPU and memory requirement, its ideal for all personal devices such as phones, smart speakers, smart radios and laptops.
Speaker ID block diagram
TPR: 95% on android mobile phone for single user enrolment use cases.
FPR: 5% on android mobile phone for single user enrolment.
CPU: 370MHZ on Android Mobile Phone.
Latency: less than 350 ms delay.
Competitive Benchmarking for Home use case
True positive rate
False positive rate
Meeami Speaker ID (XMOS+P64)
Amazon Echo DOT
Text Dependent Speaker ID
Uses proprietary feature vector (40-D) and pre-trained background model @2.5 MB
Operates on frame by frame basis
Tunes the background model during enrollment
Provision for updating the background model
Identification and imposter rejection is 95% and above
supports specific tuning for max identification or imposter rejection
CPU : 360MHz (unoptimized), additional 1MHz per new speaker
Text Independent Speaker ID
Operates once in 200 frames of speech
Identification Accuracy (IA) - 90%
Imposter Rejection Rate - 83%
CPU: Base: 320 MHz (unoptimized)
Model size : 38 MB
Every increment in enrolled speaker consumes negligible MHz (around 0.5MHz)