--- title: Speech-to-Text description: Datadog, the leading service for cloud-scale monitoring. breadcrumbs: Docs > DDSQL Reference > Data Directory > Speech-to-Text --- # Speech-to-Text Speech-to-Text is a Google Cloud service that converts spoken language into written text using machine learning models. It supports real-time and batch audio transcription, multiple languages, and domain-specific tuning. The service can process audio from various sources such as files or streaming input, making it useful for voice commands, call analytics, and caption generation. ``` gcp.speech_recognizer ``` ## Fields | Title | ID | Type | Data Type | Description | | -------------------------- | ---- | ------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ----------- | | _key | core | string | | ancestors | core | array | | annotations | core | hstore | Allows users to store small amounts of arbitrary data. Both the key and the value must be 63 characters or less each. At most 100 annotations. | | create_time | core | timestamp | Output only. Creation time. | | datadog_display_name | core | string | | default_recognition_config | core | json | Default configuration to use for requests with this Recognizer. This can be overwritten by inline configuration in the RecognizeRequest.config field. | | delete_time | core | timestamp | Output only. The time at which this Recognizer was requested for deletion. | | etag | core | string | Output only. This checksum is computed by the server based on the value of other fields. This may be sent on update, undelete, and delete requests to ensure the client has an up-to-date value before proceeding. | | expire_time | core | timestamp | Output only. The time at which this Recognizer will be purged. | | gcp_display_name | core | string | User-settable, human-readable name for the Recognizer. Must be 63 characters or less. | | kms_key_name | core | string | Output only. The [KMS key name](https://cloud.google.com/kms/docs/resource-hierarchy#keys) with which the Recognizer is encrypted. The expected format is `projects/{project}/locations/{location}/keyRings/{key_ring}/cryptoKeys/{crypto_key}`. | | kms_key_version_name | core | string | Output only. The [KMS key version name](https://cloud.google.com/kms/docs/resource-hierarchy#key_versions) with which the Recognizer is encrypted. The expected format is `projects/{project}/locations/{location}/keyRings/{key_ring}/cryptoKeys/{crypto_key}/cryptoKeyVersions/{crypto_key_version}`. | | labels | core | array | | language_codes | core | array | Optional. This field is now deprecated. Prefer the `language_codes` field in the `RecognitionConfig` message. The language of the supplied audio as a [BCP-47](https://www.rfc-editor.org/rfc/bcp/bcp47.txt) language tag. Supported languages for each model are listed in the [Table of Supported Models](https://cloud.google.com/speech-to-text/v2/docs/speech-to-text-supported-languages). If additional languages are provided, recognition result will contain recognition in the most likely language detected. The recognition result will include the language tag of the language detected in the audio. When you create or update a Recognizer, these values are stored in normalized BCP-47 form. For example, "en-us" is stored as "en-US". | | model | core | string | Optional. This field is now deprecated. Prefer the `model` field in the `RecognitionConfig` message. Which model to use for recognition requests. Select the model best suited to your domain to get best results. Guidance for choosing which model to use can be found in the [Transcription Models Documentation](https://cloud.google.com/speech-to-text/v2/docs/transcription-model) and the models supported in each region can be found in the [Table Of Supported Models](https://cloud.google.com/speech-to-text/v2/docs/speech-to-text-supported-languages). | | name | core | string | Output only. Identifier. The resource name of the Recognizer. Format: `projects/{project}/locations/{location}/recognizers/{recognizer}`. | | organization_id | core | string | | parent | core | string | | project_id | core | string | | project_number | core | string | | reconciling | core | bool | Output only. Whether or not this Recognizer is in the process of being updated. | | region_id | core | string | | resource_name | core | string | | state | core | string | Output only. The Recognizer lifecycle state. | | tags | core | hstore_csv | | uid | core | string | Output only. System-assigned unique identifier for the Recognizer. | | update_time | core | timestamp | Output only. The most recent time this Recognizer was modified. | | zone_id | core | string |