Phrase(mapping=None, *, ignore_unknown_fields=False, **kwargs)A phrases containing words and phrase "hints" so that the speech
recognition is more likely to recognize them. This can be used to
improve the accuracy for specific words and phrases, for example, if
specific commands are typically spoken by the user. This can also be
used to add additional words to the vocabulary of the recognizer.
See usage
limits <https://cloud.google.com/speech-to-text/quotas#content>__.
List items can also include pre-built or custom classes containing
groups of words that represent common concepts that occur in natural
language. For example, rather than providing a phrase hint for every
month of the year (e.g. "i was born in january", "i was born in
febuary", ...), use the pre-built $MONTH class improves the
likelihood of correctly transcribing audio that includes months
(e.g. "i was born in $month"). To refer to pre-built classes, use
the class' symbol prepended with $ e.g. $MONTH. To refer to
custom classes that were defined inline in the request, set the
class's custom_class_id to a string unique to all class
resources and inline classes. Then use the class' id wrapped in
$\ {...} e.g. "${my-months}". To refer to custom classes
resources, use the class' id wrapped in ${} (e.g.
${my-months}).
Speech-to-Text supports three locations: global, us (US
North America), and eu (Europe). If you are calling the
speech.googleapis.com endpoint, use the global location. To
specify a region, use a regional
endpoint </speech-to-text/docs/endpoints>__ with matching us or
eu location value.
Attributes
| Name | Description |
| value |
str
The phrase itself. |
| boost |
float
Hint Boost. Overrides the boost set at the phrase set level. Positive value will increase the probability that a specific phrase will be recognized over other similar sounding phrases. The higher the boost, the higher the chance of false positive recognition as well. Negative boost will simply be ignored. Though ``boost`` can accept a wide range of positive values, most use cases are best served with values between 0 and 20. We recommend using a binary search approach to finding the optimal value for your use case. Speech recognition will skip PhraseSets with a boost value of 0. |