Struct google_api_proto::google::cloud::speech::v1::RecognitionConfig

pub struct RecognitionConfig {

    pub encoding: i32,
    pub sample_rate_hertz: i32,
    pub audio_channel_count: i32,
    pub enable_separate_recognition_per_channel: bool,
    pub language_code: String,
    pub alternative_language_codes: Vec<String>,
    pub max_alternatives: i32,
    pub profanity_filter: bool,
    pub adaptation: Option<SpeechAdaptation>,
    pub transcript_normalization: Option<TranscriptNormalization>,
    pub speech_contexts: Vec<SpeechContext>,
    pub enable_word_time_offsets: bool,
    pub enable_word_confidence: bool,
    pub enable_automatic_punctuation: bool,
    pub enable_spoken_punctuation: Option<bool>,
    pub enable_spoken_emojis: Option<bool>,
    pub diarization_config: Option<SpeakerDiarizationConfig>,
    pub metadata: Option<RecognitionMetadata>,
    pub model: String,
    pub use_enhanced: bool,
}

Provides information to the recognizer that specifies how to process the request.

Fields

encoding: i32

Encoding of audio data sent in all RecognitionAudio messages. This field is optional for FLAC and WAV audio files and required for all other audio formats. For details, see [AudioEncoding][google.cloud.speech.v1.RecognitionConfig.AudioEncoding].

sample_rate_hertz: i32

Sample rate in Hertz of the audio data sent in all RecognitionAudio messages. Valid values are: 8000-48000. 16000 is optimal. For best results, set the sampling rate of the audio source to 16000 Hz. If that’s not possible, use the native sample rate of the audio source (instead of re-sampling). This field is optional for FLAC and WAV audio files, but is required for all other audio formats. For details, see [AudioEncoding][google.cloud.speech.v1.RecognitionConfig.AudioEncoding].

audio_channel_count: i32

The number of channels in the input audio data. ONLY set this for MULTI-CHANNEL recognition. Valid values for LINEAR16, OGG_OPUS and FLAC are 1-8. Valid value for MULAW, AMR, AMR_WB and SPEEX_WITH_HEADER_BYTE is only 1. If 0 or omitted, defaults to one channel (mono). Note: We only recognize the first channel by default. To perform independent recognition on each channel set enable_separate_recognition_per_channel to ‘true’.

enable_separate_recognition_per_channel: bool

This needs to be set to true explicitly and audio_channel_count > 1 to get each channel recognized separately. The recognition result will contain a channel_tag field to state which channel that result belongs to. If this is not true, we will only recognize the first channel. The request is billed cumulatively for all channels recognized: audio_channel_count multiplied by the length of the audio.

language_code: String

Required. The language of the supplied audio as a BCP-47 language tag. Example: “en-US”. See Language Support for a list of the currently supported language codes.

alternative_language_codes: Vec<String>

A list of up to 3 additional BCP-47 language tags, listing possible alternative languages of the supplied audio. See Language Support for a list of the currently supported language codes. If alternative languages are listed, recognition result will contain recognition in the most likely language detected including the main language_code. The recognition result will include the language tag of the language detected in the audio. Note: This feature is only supported for Voice Command and Voice Search use cases and performance may vary for other use cases (e.g., phone call transcription).

max_alternatives: i32

Maximum number of recognition hypotheses to be returned. Specifically, the maximum number of SpeechRecognitionAlternative messages within each SpeechRecognitionResult. The server may return fewer than max_alternatives. Valid values are 0-30. A value of 0 or 1 will return a maximum of one. If omitted, will return a maximum of one.

profanity_filter: bool

If set to true, the server will attempt to filter out profanities, replacing all but the initial character in each filtered word with asterisks, e.g. “f***”. If set to false or omitted, profanities won’t be filtered out.

adaptation: Option<SpeechAdaptation>

Speech adaptation configuration improves the accuracy of speech recognition. For more information, see the speech adaptation documentation. When speech adaptation is set it supersedes the speech_contexts field.

transcript_normalization: Option<TranscriptNormalization>

Optional. Use transcription normalization to automatically replace parts of the transcript with phrases of your choosing. For StreamingRecognize, this normalization only applies to stable partial transcripts (stability > 0.8) and final transcripts.

speech_contexts: Vec<SpeechContext>

Array of [SpeechContext][google.cloud.speech.v1.SpeechContext]. A means to provide context to assist the speech recognition. For more information, see speech adaptation.

enable_word_time_offsets: bool

If true, the top result includes a list of words and the start and end time offsets (timestamps) for those words. If false, no word-level time offset information is returned. The default is false.

enable_word_confidence: bool

If true, the top result includes a list of words and the confidence for those words. If false, no word-level confidence information is returned. The default is false.

enable_automatic_punctuation: bool

If ‘true’, adds punctuation to recognition result hypotheses. This feature is only available in select languages. Setting this for requests in other languages has no effect at all. The default ‘false’ value does not add punctuation to result hypotheses.

enable_spoken_punctuation: Option<bool>

The spoken punctuation behavior for the call If not set, uses default behavior based on model of choice e.g. command_and_search will enable spoken punctuation by default If ‘true’, replaces spoken punctuation with the corresponding symbols in the request. For example, “how are you question mark” becomes “how are you?”. See https://cloud.google.com/speech-to-text/docs/spoken-punctuation for support. If ‘false’, spoken punctuation is not replaced.

enable_spoken_emojis: Option<bool>

The spoken emoji behavior for the call If not set, uses default behavior based on model of choice If ‘true’, adds spoken emoji formatting for the request. This will replace spoken emojis with the corresponding Unicode symbols in the final transcript. If ‘false’, spoken emojis are not replaced.

diarization_config: Option<SpeakerDiarizationConfig>

Config to enable speaker diarization and set additional parameters to make diarization better suited for your application. Note: When this is enabled, we send all the words from the beginning of the audio for the top alternative in every consecutive STREAMING responses. This is done in order to improve our speaker tags as our models learn to identify the speakers in the conversation over time. For non-streaming requests, the diarization results will be provided only in the top alternative of the FINAL SpeechRecognitionResult.

metadata: Option<RecognitionMetadata>

Metadata regarding this request.

model: String

Which model to select for the given request. Select the model best suited to your domain to get best results. If a model is not explicitly specified, then we auto-select a model based on the parameters in the RecognitionConfig.

Model	Description
latest_long	Best for long form content like media or conversation.
latest_short	Best for short form content like commands or single shot directed speech.
command_and_search	Best for short queries such as voice commands or voice search.
phone_call	Best for audio that originated from a phone call (typically recorded at an 8khz sampling rate).
video	Best for audio that originated from video or includes multiple speakers. Ideally the audio is recorded at a 16khz or greater sampling rate. This is a premium model that costs more than the standard rate.
default	Best for audio that is not one of the specific audio models. For example, long-form audio. Ideally the audio is high-fidelity, recorded at a 16khz or greater sampling rate.
medical_conversation	Best for audio that originated from a conversation between a medical provider and patient.
medical_dictation	Best for audio that originated from dictation notes by a medical provider.

use_enhanced: bool

Set to true to use an enhanced model for speech recognition. If use_enhanced is set to true and the model field is not set, then an appropriate enhanced model is chosen if an enhanced model exists for the audio.

If use_enhanced is true and an enhanced version of the specified model does not exist, then the speech is recognized using the standard version of the specified model.

Implementations

impl RecognitionConfig

pub fn encoding(&self) -> AudioEncoding

Returns the enum value of encoding, or the default if the field is set to an invalid enum value.

pub fn set_encoding(&mut self, value: AudioEncoding)

Sets encoding to the provided enum value.

Trait Implementations

impl Clone for RecognitionConfig

fn clone(&self) -> RecognitionConfig

Returns a copy of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for RecognitionConfig

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Default for RecognitionConfig

fn default() -> Self

Returns the “default value” for a type.

impl Message for RecognitionConfig

fn encoded_len(&self) -> usize

Returns the encoded length of the message without a length delimiter.

fn clear(&mut self)

Clears the message, resetting all fields to their default.

fn encode(&self, buf: &mut impl BufMut) -> Result<(), EncodeError>

where Self: Sized,

Encodes the message to a buffer.

fn encode_to_vec(&self) -> Vec<u8>

where Self: Sized,

Encodes the message to a newly allocated buffer.

fn encode_length_delimited( &self, buf: &mut impl BufMut, ) -> Result<(), EncodeError>

where Self: Sized,

Encodes the message with a length-delimiter to a buffer.

fn encode_length_delimited_to_vec(&self) -> Vec<u8>

where Self: Sized,

Encodes the message with a length-delimiter to a newly allocated buffer.

fn decode(buf: impl Buf) -> Result<Self, DecodeError>

where Self: Default,

Decodes an instance of the message from a buffer.

fn decode_length_delimited(buf: impl Buf) -> Result<Self, DecodeError>

where Self: Default,

Decodes a length-delimited instance of the message from the buffer.

fn merge(&mut self, buf: impl Buf) -> Result<(), DecodeError>

where Self: Sized,

Decodes an instance of the message from a buffer, and merges it into self.

fn merge_length_delimited(&mut self, buf: impl Buf) -> Result<(), DecodeError>

where Self: Sized,

Decodes a length-delimited instance of the message from buffer, and merges it into self.

impl PartialEq for RecognitionConfig

fn eq(&self, other: &RecognitionConfig) -> bool

This method tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &Rhs) -> bool

This method tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl StructuralPartialEq for RecognitionConfig