SWIrcnd—recognition end

This event is logged at the end of recognition.

Note: The entries in the log are not guaranteed to be sorted by the nbest result at the time when SWIrcnd is printed.

In addition to the Tokens used for every event, this event has the following tokens:

Token

Meaning

BORT

Beginning of recognition time (when the recognizer first processed the signal).

CONF

Confidence value for n-best item. Values can range from 0 to 999.

DPNM

Root name of the diphone acoustic models used to recognize the top choice on the n-best list. (If there is no applicable value to report, a value of NA is used.)

DURS

Amount of speech processed by the recognizer in milliseconds. The value can sometimes exceed EOSS by small amounts. See Measuring latency with EORT and EOSS.

ENDR

See Reasons for end of speech.

EORT

End-of-recognition time in milliseconds. Clock time when the results are ready. Measured in real time from the arrival of the first packet of the input stream. See Measuring latency with EORT and EOSS.

EOSD

How much speech data was passed to the endpointer before EOS was determined. This token helps determine latency due to endpointer decision-making (mostly end of speech timeout).

If EOSD equals EOSS then something unusual caused the end-of-speech; for example, the maximum speech duration timer expired. See Measuring latency with EORT and EOSS.

EOSS

End-of-speech signal: where in the input stream the endpointer wanted the recognizer to stop. See Measuring latency with EORT and EOSS.

EOST

End-of-speech time in milliseconds. Clock time when the endpointer determined the end of caller speech; measured in real time from the arrival of the first packet; delays in the audio path are not counted. See Measuring latency with EORT and EOSS.

GRMR

Grammar for n-best item.

KEYS

List of key/value pairs for the top result.

LA

Value of the swirec_load_adjusted_speedvsaccuracy parameter used for the recognition. Values include:

idle
normal
busy
Xidle
Xnormal
Xbusy

"X" values indicate that the parameter specified that value. Values without "X" were determined at runtime with the parameter setting "on."

MACC

Filename of the statistics file (the monophone accumulator) that tuned the acoustic model used for the recognition event. (Also, see the DACC token).

MDVR

Model version—version stamp of models. Format is L.M.m.s, where L is language number, M is major version, m is minor version, and s is the set number.

MEDIA

An audio media type. For example, "MEDIA=audio/basic;rate:8000"

MPNM

Indicates the acoustic models used for generating the recognition result.

Contains a comma separated list showing the language and acoustic model filenames used for first-pass recognition processing to get the top choice on the n-best list.

Each list element has the format LangCode/Version/Path/Filename.
(If there is no applicable value to report, a value of NA is used.) For example:

MPNM=en.us/10.0.0/models/FirstPass/models.hmm,de.de/10.0.0/models/FirstPass/models.hmm

NBST

Number of n-best items. Used only if RSTT is "ok" or "lowconf."

OFFS

For internal use only. Shows an offset value for acoustic models. For example, "OFFS=1.3".

RAWS

Raw score for n-best item.

RAWT

Raw text for n-best item; set to the value of the SWI_literal key. See Measuring latency with EORT and EOSS.

RCPU

Recognizer CPU time in milliseconds. Measures how much CPU was used for the recognition.

RENR

See Reasons for end of recognition.

RSLT

Parsed text for n-best item.

RSTT

See Return codes.

SAFEK

Parsed text for n-best item. Used only if the grammar sets SWI_safeKey. Typically, the key passes a partial recognition result when passing the whole result might be a security risk.

SCAL

For internal use only. Shows a multiplier for acoustic scale. For example, "SCAL=5.5".

SECURE

Indicates that sensitive information is suppressed for this event. The token only appears when true.

SPAG

The second pass has not modified the result of the first pass.

When the recognizer is "unsure" about the accuracy of the nbest list, it invokes a second pass through the data to help improve the accuracy. A second pass uses more CPU and may also presage a low-confidence recognition.

SPIV

The second pass has been invoked.

When the recognizer is "unsure" about the accuracy of the nbest list, it invokes a second pass through the data to help improve the accuracy. A second pass uses more CPU and may also presage a low-confidence recognition.

SPMS

Second-pass models. Contains a comma separated list showing the language and acoustic model used to recognize the top choice on the n-best list.

When this token appears in the log, it confirms the recognizer performed second-pass processing. It does not appear when recognition completes after the first-pass (see MPNM). (Because the n-best can change during the second pass, MPNM and SPMS might not be consistent. For example, they might refer to different languages.)

Each list element has the format LangCode/Version/Path/Filename.
(If there is no applicable value to report, a value of NA is used.) For example:

SPMS=en.us/10.0.0/models/SecondPass1/models1.hmm,de.de/10.0.0/models/SecondPass1/models1.hmm

SPOK

Normalized raw text for n-best item; set to the value of the SWI_spoken key. See Measuring latency with EORT and EOSS.

WVNM

Waveform name.