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Included models

This distribution includes sample models in ~/Sensory/TrulyNaturalSDK/7.9.0/model/

You can also download models for additional languages in a range of sizes.

Console examples in this section assume $HOME/Sensory/TrulyNaturalSDK/7.9.0 as the SDK install directory; replace that prefix if you installed elsewhere.

Wake words

See the wake word model type for description of model behavior and settings.

spot-voicegenie-enUS-6.6.0-m.snsr

Fixed-phrase "Voice Genie" wake word for US English. Reports a confidence-score with each detection.

spot-hbg-enUS-1.4.0-m.snsr

Fixed-phrase "Hello Blue Genie" wake word for US English.

spot-music-enUS-1.2.0-m.snsr

Music command set for US English. Commands include "play music", "pause music", "stop music", "previous song", and "next song".

Adapting wake word

See the adapting wake word model type for a description of model behavior and settings.

ca-voicegenie-enUS-1.1.0.snsr

This is a fixed-phrase spotter for "Voice Genie" in US English that adapts to users' speech to improve false-accept rates.

Model adaptation and enrollment happens automatically and without any additional code requirements — you can use this model as a drop-in replacement for the fixed-phrase Voice Genie spotter.

Configuration settings of particular interest include cache-file and max-users.

Use user-iterator, delete-user, and rename-user to manage user enrollments.

Note

This model requires support for multi-threading.

Example

The reported text value changes once enrollment has identified and enrolled a new speaker.

% cd $HOME/Sensory/TrulyNaturalSDK/7.9.0

# two different speakers saying "voice genie"
% bin/snsr-eval -t model/ca-voicegenie-enUS-1.1.0.snsr\
    -s cache-file=ca-vg-cache.snsr\
    -s max-users=3
  2235   3045 voice_genie
  6810   7545 voice_genie
 11745  12525 user1/voice_genie
 16845  17595 user1/voice_genie
 29355  30180 voice_genie
 34845  35820 user2/voice_genie
 37815  38520 user1/voice_genie
 40080  40905 user2/voice_genie
^C

# restart, loading enrollments from the cache file
% bin/snsr-eval -t model/ca-voicegenie-enUS-1.1.0.snsr\
    -s cache-file=ca-vg-cache.snsr\
    -s max-users=3
 12045  13035 user2/voice_genie
 15180  15840 user1/voice_genie
 17745  18465 user1/voice_genie
 20175  20820 user2/voice_genie
^C

Wake word enrollment

See the wake word enrollment model type for a description of model behavior and settings.

eft-hbg-enUS-23.0.0.9.snsr

EFT spotter for "Hello Blue Genie", US English. This model produces wake words with a low imposter accept rate.

udt-universal-3.67.1.0.snsr

UDT enrollment. This model creates spotters with nine different operating points and supports multiple languages.

Optimized for German, English (Australian, British, Indian, United States), Spanish (European Union, North American), French (European Union), Italian, Korean, Brazilian Portuguese, and Mandarin Chinese.

udt-enUS-5.1.1.9.snsr

UDT enrollment with backwards compatibility.

Note

This older model produces enrolled wake words with reduced accuracy.

Use this model only when targeting a THF Micro 3.x DSP port, or when the wake word is followed by additional validation.

VAD

See the VAD model type for a description of model behavior and settings.

vad-ml-3.0.0.snsr

Deep-learned stand-alone Voice Activity Detector.

LVCSR tnl

See the LVCSR model type for a description of model behavior and settings.

lvcsr-build-enUS-14.2.0-5MB.snsr tnl

US English recognizer with 4.9 MiB acoustic model and support for grammar-based recognition and in-grammar acoustic confidence scores. Use search.frame-nota to adjust out-of-grammar rejection.

Example

% cd $HOME/Sensory/TrulyNaturalSDK/7.9.0
% snsr-eval -t model/lvcsr-build-enUS-14.2.0-5MB.snsr\
    -s partial-result-interval=0 \
    -f grammar-stream data/grammars/en-US/enrollments-nlu-slot.grm \
    data/enrollments/armadillo-1-2-c.wav

NLU intent: navigate (0.0000) = how far away is winco
NLU entity:   place (0.0000) = winco
   300   1920 armadillo how far away is winco

STT stt

See the STT model type for a description of model behavior and settings.

You can download additional models for other languages in a range of different sizes.

stt-enUS-general-medium-2.4.5-pnc.snsr stt

STT recognizer with broad-domain and grammar-based recognition support. Results include capitalization and punctuation.

This model requires STT support, which currently depends on third-party Open Source modules that are optionally included in the TrulyNatural SDK See Open Source Licenses for details.

Templates

Templates add functionality to recognizer models. This includes running models simultaneously or sequentially, and adding VAD audio gating.

See template types for an overview.

tpl-spot-concurrent-1.6.0.snsr

Runs two wake word models at the same time.

tpl-spot-concurrent

tpl-spot-debug-1.6.0.snsr

Adds runtime data collection to a wake word model.

tpl-spot-debug

tpl-spot-select-1.6.0.snsr

Dynamically selects which of the two embedded wake word models to run.

tpl-spot-select

tpl-spot-sequential-1.6.0.snsr

Runs two wake word models one after the other, with optional looping on the second. Includes push-to-talk as an alternative to the wake word.

tpl-spot-sequential

tpl-spot-vad-3.14.0.snsr

Runs a wake word until it spots, then does start- and endpoint detection on the subsequent audio stream using a VAD.

tpl-spot-vad

tpl-opt-spot-vad-lvcsr-1.29.0.snsr tnl

Optionally runs a wake word until it spots, segments the subsequent audio stream with a VAD, then sends the segmented audio to an LVCSR or STT recognizer. You can select at runtime whether recognition waits on the wake word or starts immediately.

tpl-opt-spot-vad-lvcsr

tpl-spot-vad-lvcsr-3.24.0.snsr tnl

Runs a wake word until it spots, segments the subsequent audio stream with a VAD, then sends the segmented audio to an LVCSR or STT recognizer.

tpl-spot-vad-lvcsr

tpl-vad-lvcsr-3.18.0.snsr

Detects speech with a VAD and sends the segmented audio to an LVCSR or STT recognizer.

tpl-vad-lvcsr