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author | Isabella Gottardi <isabella.gottardi@arm.com> | 2021-04-20 11:50:37 +0100 |
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committer | Isabella Gottardi <isabella.gottardi@arm.com> | 2021-04-22 11:08:54 +0100 |
commit | e03f1af5dcbe7f448cc63456ece6302590c38387 (patch) | |
tree | c691ab615f98144506dfad82e6917bc2b1ea2e11 /docs/use_cases/kws_asr.md | |
parent | 5cafe0a147c7360fe19542a1cf14c91ab787a304 (diff) | |
download | ml-embedded-evaluation-kit-e03f1af5dcbe7f448cc63456ece6302590c38387.tar.gz |
MLECO-1871: Rename samples with clearer names
Signed-off-by: Isabella Gottardi <isabella.gottardi@arm.com>
Change-Id: I926c6c138b32dc658cd195737a63eac327964284
Diffstat (limited to 'docs/use_cases/kws_asr.md')
-rw-r--r-- | docs/use_cases/kws_asr.md | 8 |
1 files changed, 4 insertions, 4 deletions
diff --git a/docs/use_cases/kws_asr.md b/docs/use_cases/kws_asr.md index 55989c7..950d576 100644 --- a/docs/use_cases/kws_asr.md +++ b/docs/use_cases/kws_asr.md @@ -519,8 +519,8 @@ Choice: 5. “List” menu option prints a list of pair ... indexes - the original filenames embedded in the application: ```log - INFO - List of Files: - INFO - 0 => yesnogostop.wav + [INFO] List of Files: + [INFO] 0 => yes_no_go_stop.wav ``` ### Running Keyword Spotting and Automatic Speech Recognition @@ -531,7 +531,7 @@ The following example illustrates application output: ```log INFO - KWS audio data window size 16000 -INFO - Running KWS inference on audio clip 0 => yesnogostop.wav +INFO - Running KWS inference on audio clip 0 => yes_no_go_stop.wav INFO - Inference 1/7 INFO - For timestamp: 0.000000 (inference #: 0); threshold: 0.900000 INFO - label @ 0: yes, score: 0.996094 @@ -559,7 +559,7 @@ INFO - NPU total cycles: 28910172 It could take several minutes to complete one inference run (average time is 2-3 minutes). -Using the input “yesnogostop.wav”, the log shows inference results for the KWS operation first, detecting the +Using the input “yes_no_go_stop.wav”, the log shows inference results for the KWS operation first, detecting the trigger word “yes“ with the stated probability score (in this case 0.99). After this, the ASR inference is run, printing the words recognized from the input sample. |