class WhisperForCTC extends AnnotatorModel[WhisperForCTC] with HasBatchedAnnotateAudio[WhisperForCTC] with HasAudioFeatureProperties with WriteTensorflowModel with WriteOnnxModel with HasEngine with HasGeneratorProperties with HasProtectedParams

Whisper Model with a language modeling head on top for Connectionist Temporal Classification (CTC).

Whisper is an automatic speech recognition (ASR) system trained on 680,000 hours of multilingual and multitask supervised data collected from the web. It transcribe in multiple languages, as well as translate from those languages into English.

The audio needs to be provided pre-processed an array of floats.

For multilingual models, the language and the task (transcribe or translate) can be set with setLanguage and setTask.

Note that at the moment, this annotator only supports greedy search and only Spark Versions 3.4 and up are supported.

Pretrained models can be loaded with pretrained of the companion object:

val speechToText = WhisperForCTC.pretrained()
  .setInputCols("audio_assembler")
  .setOutputCol("text")

The default model is "asr_whisper_tiny_opt", if no name is provided.

For available pretrained models please see the Models Hub.

To see which models are compatible and how to import them see https://github.com/JohnSnowLabs/spark-nlp/discussions/5669 and to see more extended examples, see WhisperForCTCTestSpec.

References:

Robust Speech Recognition via Large-Scale Weak Supervision

Paper Abstract:

We study the capabilities of speech processing systems trained simply to predict large amounts of transcripts of audio on the internet. When scaled to 680,000 hours of multilingual and multitask supervision, the resulting models generalize well to standard benchmarks and are often competitive with prior fully supervised results but in a zero- shot transfer setting without the need for any fine- tuning. When compared to humans, the models approach their accuracy and robustness. We are releasing models and inference code to serve as a foundation for further work on robust speech processing.

Example

import spark.implicits._
import com.johnsnowlabs.nlp.base._
import com.johnsnowlabs.nlp.annotators._
import com.johnsnowlabs.nlp.annotators.audio.WhisperForCTC
import org.apache.spark.ml.Pipeline

val audioAssembler: AudioAssembler = new AudioAssembler()
  .setInputCol("audio_content")
  .setOutputCol("audio_assembler")

val speechToText: WhisperForCTC = WhisperForCTC
  .pretrained()
  .setInputCols("audio_assembler")
  .setOutputCol("text")

val pipeline: Pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText))

val bufferedSource =
  scala.io.Source.fromFile("src/test/resources/audio/txt/librispeech_asr_0.txt")

val rawFloats = bufferedSource
  .getLines()
  .map(_.split(",").head.trim.toFloat)
  .toArray
bufferedSource.close

val processedAudioFloats = Seq(rawFloats).toDF("audio_content")

val result = pipeline.fit(processedAudioFloats).transform(processedAudioFloats)
result.select("text.result").show(truncate = false)
+------------------------------------------------------------------------------------------+
|result                                                                                    |
+------------------------------------------------------------------------------------------+
|[ Mr. Quilter is the apostle of the middle classes and we are glad to welcome his gospel.]|
+------------------------------------------------------------------------------------------+
Linear Supertypes
HasProtectedParams, HasGeneratorProperties, HasEngine, WriteOnnxModel, WriteTensorflowModel, HasAudioFeatureProperties, HasBatchedAnnotateAudio[WhisperForCTC], AnnotatorModel[WhisperForCTC], CanBeLazy, RawAnnotator[WhisperForCTC], HasOutputAnnotationCol, HasInputAnnotationCols, HasOutputAnnotatorType, ParamsAndFeaturesWritable, HasFeatures, DefaultParamsWritable, MLWritable, Model[WhisperForCTC], Transformer, PipelineStage, Logging, Params, Serializable, Serializable, Identifiable, AnyRef, Any
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Inherited
  1. WhisperForCTC
  2. HasProtectedParams
  3. HasGeneratorProperties
  4. HasEngine
  5. WriteOnnxModel
  6. WriteTensorflowModel
  7. HasAudioFeatureProperties
  8. HasBatchedAnnotateAudio
  9. AnnotatorModel
  10. CanBeLazy
  11. RawAnnotator
  12. HasOutputAnnotationCol
  13. HasInputAnnotationCols
  14. HasOutputAnnotatorType
  15. ParamsAndFeaturesWritable
  16. HasFeatures
  17. DefaultParamsWritable
  18. MLWritable
  19. Model
  20. Transformer
  21. PipelineStage
  22. Logging
  23. Params
  24. Serializable
  25. Serializable
  26. Identifiable
  27. AnyRef
  28. Any
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Visibility
  1. Public
  2. All

Instance Constructors

  1. new WhisperForCTC()

    Annotator reference id.

    Annotator reference id. Used to identify elements in metadata or to refer to this annotator type

  2. new WhisperForCTC(uid: String)

    uid

    required uid for storing annotator to disk

Type Members

  1. implicit class ProtectedParam[T] extends Param[T]
    Definition Classes
    HasProtectedParams
  2. type AnnotationContent = Seq[Row]

    internal types to show Rows as a relevant StructType Should be deleted once Spark releases UserDefinedTypes to @developerAPI

    internal types to show Rows as a relevant StructType Should be deleted once Spark releases UserDefinedTypes to @developerAPI

    Attributes
    protected
    Definition Classes
    AnnotatorModel
  3. type AnnotatorType = String
    Definition Classes
    HasOutputAnnotatorType

Value Members

  1. final def !=(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  2. final def ##(): Int
    Definition Classes
    AnyRef → Any
  3. final def $[T](param: Param[T]): T
    Attributes
    protected
    Definition Classes
    Params
  4. def $$[T](feature: StructFeature[T]): T
    Attributes
    protected
    Definition Classes
    HasFeatures
  5. def $$[K, V](feature: MapFeature[K, V]): Map[K, V]
    Attributes
    protected
    Definition Classes
    HasFeatures
  6. def $$[T](feature: SetFeature[T]): Set[T]
    Attributes
    protected
    Definition Classes
    HasFeatures
  7. def $$[T](feature: ArrayFeature[T]): Array[T]
    Attributes
    protected
    Definition Classes
    HasFeatures
  8. final def ==(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  9. def _transform(dataset: Dataset[_], recursivePipeline: Option[PipelineModel]): DataFrame
    Attributes
    protected
    Definition Classes
    AnnotatorModel
  10. val addedSpecialTokens: MapFeature[String, Int]
    Attributes
    protected[nlp]
  11. def afterAnnotate(dataset: DataFrame): DataFrame
    Attributes
    protected
    Definition Classes
    AnnotatorModel
  12. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  13. def batchAnnotate(batchedAnnotations: Seq[Array[AnnotationAudio]]): Seq[Seq[Annotation]]

    Takes audio annotations and produces transcribed document annotations.

    Takes audio annotations and produces transcribed document annotations.

    batchedAnnotations

    Audio annotations in batches

    returns

    Transcribed audio as DOCUMENT type annotation

    Definition Classes
    WhisperForCTC → HasBatchedAnnotateAudio
  14. def batchProcess(rows: Iterator[_]): Iterator[Row]
    Definition Classes
    HasBatchedAnnotateAudio
  15. val batchSize: IntParam

    Size of every batch (Default depends on model).

    Size of every batch (Default depends on model).

    Definition Classes
    HasBatchedAnnotateAudio
  16. val beamSize: IntParam

    Beam size for the beam search algorithm (Default: 4)

    Beam size for the beam search algorithm (Default: 4)

    Definition Classes
    HasGeneratorProperties
  17. def beforeAnnotate(dataset: Dataset[_]): Dataset[_]
    Attributes
    protected
    Definition Classes
    AnnotatorModel
  18. final def checkSchema(schema: StructType, inputAnnotatorType: String): Boolean
    Attributes
    protected
    Definition Classes
    HasInputAnnotationCols
  19. final def clear(param: Param[_]): WhisperForCTC.this.type
    Definition Classes
    Params
  20. def clone(): AnyRef
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  21. val configProtoBytes: IntArrayParam

    ConfigProto from tensorflow, serialized into byte array.

    ConfigProto from tensorflow, serialized into byte array. Get with config_proto.SerializeToString()

  22. def copy(extra: ParamMap): WhisperForCTC

    requirement for annotators copies

    requirement for annotators copies

    Definition Classes
    RawAnnotator → Model → Transformer → PipelineStage → Params
  23. def copyValues[T <: Params](to: T, extra: ParamMap): T
    Attributes
    protected
    Definition Classes
    Params
  24. final def defaultCopy[T <: Params](extra: ParamMap): T
    Attributes
    protected
    Definition Classes
    Params
  25. val doNormalize: BooleanParam

    Whether or not to normalize the input with mean and standard deviation

    Whether or not to normalize the input with mean and standard deviation

    Definition Classes
    HasAudioFeatureProperties
  26. val doSample: BooleanParam

    Whether or not to use sampling, use greedy decoding otherwise (Default: false)

    Whether or not to use sampling, use greedy decoding otherwise (Default: false)

    Definition Classes
    HasGeneratorProperties
  27. val engine: Param[String]

    This param is set internally once via loadSavedModel.

    This param is set internally once via loadSavedModel. That's why there is no setter

    Definition Classes
    HasEngine
  28. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  29. def equals(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  30. def explainParam(param: Param[_]): String
    Definition Classes
    Params
  31. def explainParams(): String
    Definition Classes
    Params
  32. def extraValidate(structType: StructType): Boolean
    Attributes
    protected
    Definition Classes
    RawAnnotator
  33. def extraValidateMsg: String

    Override for additional custom schema checks

    Override for additional custom schema checks

    Attributes
    protected
    Definition Classes
    RawAnnotator
  34. final def extractParamMap(): ParamMap
    Definition Classes
    Params
  35. final def extractParamMap(extra: ParamMap): ParamMap
    Definition Classes
    Params
  36. val featureSize: IntParam

    Definition Classes
    HasAudioFeatureProperties
  37. val features: ArrayBuffer[Feature[_, _, _]]
    Definition Classes
    HasFeatures
  38. def finalize(): Unit
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  39. val generationConfig: StructFeature[GenerationConfig]
    Attributes
    protected[nlp]
  40. def get[T](feature: StructFeature[T]): Option[T]
    Attributes
    protected
    Definition Classes
    HasFeatures
  41. def get[K, V](feature: MapFeature[K, V]): Option[Map[K, V]]
    Attributes
    protected
    Definition Classes
    HasFeatures
  42. def get[T](feature: SetFeature[T]): Option[Set[T]]
    Attributes
    protected
    Definition Classes
    HasFeatures
  43. def get[T](feature: ArrayFeature[T]): Option[Array[T]]
    Attributes
    protected
    Definition Classes
    HasFeatures
  44. final def get[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  45. def getAddedSpecialTokens: Map[String, Int]
    Attributes
    protected[nlp]
  46. def getBatchSize: Int

    Size of every batch.

    Size of every batch.

    Definition Classes
    HasBatchedAnnotateAudio
  47. def getBeamSize: Int

    Definition Classes
    HasGeneratorProperties
  48. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  49. def getConfigProtoBytes: Option[Array[Byte]]

    ConfigProto from tensorflow, serialized into byte array.

    ConfigProto from tensorflow, serialized into byte array. Get with config_proto.SerializeToString()

  50. final def getDefault[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  51. def getDoNormalize: Boolean

    Definition Classes
    HasAudioFeatureProperties
  52. def getDoSample: Boolean

    Definition Classes
    HasGeneratorProperties
  53. def getEngine: String

    Definition Classes
    HasEngine
  54. def getFeatureSize: Int

    Definition Classes
    HasAudioFeatureProperties
  55. def getGenerationConfig: GenerationConfig
    Attributes
    protected[nlp]
  56. def getInputCols: Array[String]

    returns

    input annotations columns currently used

    Definition Classes
    HasInputAnnotationCols
  57. def getIsMultilingual: Boolean

  58. def getLanguage: Option[String]

  59. def getLazyAnnotator: Boolean
    Definition Classes
    CanBeLazy
  60. def getMaxOutputLength: Int

    Definition Classes
    HasGeneratorProperties
  61. def getMinOutputLength: Int

    Definition Classes
    HasGeneratorProperties
  62. def getModelIfNotSet: Whisper

  63. def getNReturnSequences: Int

    Definition Classes
    HasGeneratorProperties
  64. def getNoRepeatNgramSize: Int

    Definition Classes
    HasGeneratorProperties
  65. final def getOrDefault[T](param: Param[T]): T
    Definition Classes
    Params
  66. final def getOutputCol: String

    Gets annotation column name going to generate

    Gets annotation column name going to generate

    Definition Classes
    HasOutputAnnotationCol
  67. def getPaddingSide: String

    Definition Classes
    HasAudioFeatureProperties
  68. def getPaddingValue: Float

    Definition Classes
    HasAudioFeatureProperties
  69. def getParam(paramName: String): Param[Any]
    Definition Classes
    Params
  70. def getPreprocessor: WhisperPreprocessor
    Attributes
    protected[nlp]
  71. def getRandomSeed: Option[Long]

    Definition Classes
    HasGeneratorProperties
  72. def getRepetitionPenalty: Double

    Definition Classes
    HasGeneratorProperties
  73. def getReturnAttentionMask: Boolean

    Definition Classes
    HasAudioFeatureProperties
  74. def getSamplingRate: Int

    Definition Classes
    HasAudioFeatureProperties
  75. def getSignatures: Option[Map[String, String]]

  76. def getTask: Option[String]

    Definition Classes
    HasGeneratorProperties
  77. def getTemperature: Double

    Definition Classes
    HasGeneratorProperties
  78. def getTopK: Int

    Definition Classes
    HasGeneratorProperties
  79. def getTopP: Double

    Definition Classes
    HasGeneratorProperties
  80. def getVocabulary: Map[String, Int]
  81. final def hasDefault[T](param: Param[T]): Boolean
    Definition Classes
    Params
  82. def hasParam(paramName: String): Boolean
    Definition Classes
    Params
  83. def hasParent: Boolean
    Definition Classes
    Model
  84. def hashCode(): Int
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  85. def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  86. def initializeLogIfNecessary(isInterpreter: Boolean): Unit
    Attributes
    protected
    Definition Classes
    Logging
  87. val inputAnnotatorTypes: Array[AnnotatorType]

    Annotator reference id.

    Annotator reference id. Used to identify elements in metadata or to refer to this annotator type

    Definition Classes
    WhisperForCTC → HasInputAnnotationCols
  88. final val inputCols: StringArrayParam

    columns that contain annotations necessary to run this annotator AnnotatorType is used both as input and output columns if not specified

    columns that contain annotations necessary to run this annotator AnnotatorType is used both as input and output columns if not specified

    Attributes
    protected
    Definition Classes
    HasInputAnnotationCols
  89. final def isDefined(param: Param[_]): Boolean
    Definition Classes
    Params
  90. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  91. val isMultilingual: ProtectedParam[Boolean]

    Whether or not the model is multilingual.

  92. final def isSet(param: Param[_]): Boolean
    Definition Classes
    Params
  93. def isTraceEnabled(): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  94. val language: Param[String]

    Optional language to set for the transcription.

    Optional language to set for the transcription. The imported model needs to support multiple languages.

  95. val lazyAnnotator: BooleanParam
    Definition Classes
    CanBeLazy
  96. def log: Logger
    Attributes
    protected
    Definition Classes
    Logging
  97. def logDebug(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  98. def logDebug(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  99. def logError(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  100. def logError(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  101. def logInfo(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  102. def logInfo(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  103. def logName: String
    Attributes
    protected
    Definition Classes
    Logging
  104. def logTrace(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  105. def logTrace(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  106. def logWarning(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  107. def logWarning(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  108. val maxInputLength: IntParam

    max length of the input sequence (Default: 0)

    max length of the input sequence (Default: 0)

    Definition Classes
    HasGeneratorProperties
  109. val maxOutputLength: IntParam

    Maximum length of the sequence to be generated (Default: 20)

    Maximum length of the sequence to be generated (Default: 20)

    Definition Classes
    HasGeneratorProperties
  110. val minOutputLength: IntParam

    Minimum length of the sequence to be generated (Default: 0)

    Minimum length of the sequence to be generated (Default: 0)

    Definition Classes
    HasGeneratorProperties
  111. def msgHelper(schema: StructType): String
    Attributes
    protected
    Definition Classes
    HasInputAnnotationCols
  112. val nReturnSequences: IntParam

    The number of sequences to return from the beam search.

    The number of sequences to return from the beam search.

    Definition Classes
    HasGeneratorProperties
  113. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  114. val noRepeatNgramSize: IntParam

    If set to int > 0, all ngrams of that size can only occur once (Default: 0)

    If set to int > 0, all ngrams of that size can only occur once (Default: 0)

    Definition Classes
    HasGeneratorProperties
  115. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  116. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  117. def onWrite(path: String, spark: SparkSession): Unit
    Definition Classes
    WhisperForCTC → ParamsAndFeaturesWritable
  118. val optionalInputAnnotatorTypes: Array[String]
    Definition Classes
    HasInputAnnotationCols
  119. val outputAnnotatorType: AnnotatorType
    Definition Classes
    WhisperForCTC → HasOutputAnnotatorType
  120. final val outputCol: Param[String]
    Attributes
    protected
    Definition Classes
    HasOutputAnnotationCol
  121. val paddingSide: Param[String]

    Definition Classes
    HasAudioFeatureProperties
  122. val paddingValue: FloatParam

    Definition Classes
    HasAudioFeatureProperties
  123. lazy val params: Array[Param[_]]
    Definition Classes
    Params
  124. var parent: Estimator[WhisperForCTC]
    Definition Classes
    Model
  125. val preprocessor: StructFeature[WhisperPreprocessor]
    Attributes
    protected[nlp]
  126. val randomSeed: Option[Long]

    Optional Random seed for the model.

    Optional Random seed for the model. Needs to be of type Int.

    Definition Classes
    HasGeneratorProperties
  127. val repetitionPenalty: DoubleParam

    The parameter for repetition penalty (Default: 1.0).

    The parameter for repetition penalty (Default: 1.0). 1.0 means no penalty. See this paper for more details.

    Definition Classes
    HasGeneratorProperties
  128. val returnAttentionMask: BooleanParam

    Definition Classes
    HasAudioFeatureProperties
  129. val samplingRate: IntParam

    Definition Classes
    HasAudioFeatureProperties
  130. def save(path: String): Unit
    Definition Classes
    MLWritable
    Annotations
    @Since( "1.6.0" ) @throws( ... )
  131. def set[T](param: ProtectedParam[T], value: T): WhisperForCTC.this.type

    Sets the value for a protected Param.

    Sets the value for a protected Param.

    If the parameter was already set, it will not be set again. Default values do not count as a set value and can be overridden.

    T

    Type of the parameter

    param

    Protected parameter to set

    value

    Value for the parameter

    returns

    This object

    Definition Classes
    HasProtectedParams
  132. def set[T](feature: StructFeature[T], value: T): WhisperForCTC.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  133. def set[K, V](feature: MapFeature[K, V], value: Map[K, V]): WhisperForCTC.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  134. def set[T](feature: SetFeature[T], value: Set[T]): WhisperForCTC.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  135. def set[T](feature: ArrayFeature[T], value: Array[T]): WhisperForCTC.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  136. final def set(paramPair: ParamPair[_]): WhisperForCTC.this.type
    Attributes
    protected
    Definition Classes
    Params
  137. final def set(param: String, value: Any): WhisperForCTC.this.type
    Attributes
    protected
    Definition Classes
    Params
  138. final def set[T](param: Param[T], value: T): WhisperForCTC.this.type
    Definition Classes
    Params
  139. def setAddedSpecialTokens(value: Map[String, Int]): WhisperForCTC.this.type
    Attributes
    protected[nlp]
  140. def setBatchSize(size: Int): WhisperForCTC.this.type

    Size of every batch.

    Size of every batch.

    Definition Classes
    HasBatchedAnnotateAudio
  141. def setBeamSize(beamNum: Int): WhisperForCTC.this.type

    Definition Classes
    HasGeneratorProperties
  142. def setConfigProtoBytes(bytes: Array[Int]): WhisperForCTC.this.type

    ConfigProto from tensorflow, serialized into byte array.

    ConfigProto from tensorflow, serialized into byte array. Get with config_proto.SerializeToString()

  143. def setDefault[T](feature: StructFeature[T], value: () ⇒ T): WhisperForCTC.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  144. def setDefault[K, V](feature: MapFeature[K, V], value: () ⇒ Map[K, V]): WhisperForCTC.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  145. def setDefault[T](feature: SetFeature[T], value: () ⇒ Set[T]): WhisperForCTC.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  146. def setDefault[T](feature: ArrayFeature[T], value: () ⇒ Array[T]): WhisperForCTC.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  147. final def setDefault(paramPairs: ParamPair[_]*): WhisperForCTC.this.type
    Attributes
    protected
    Definition Classes
    Params
  148. final def setDefault[T](param: Param[T], value: T): WhisperForCTC.this.type
    Attributes
    protected[org.apache.spark.ml]
    Definition Classes
    Params
  149. def setDoNormalize(value: Boolean): WhisperForCTC.this.type

    Definition Classes
    HasAudioFeatureProperties
  150. def setDoSample(value: Boolean): WhisperForCTC.this.type

    Definition Classes
    HasGeneratorProperties
  151. def setFeatureSize(value: Int): WhisperForCTC.this.type

    Definition Classes
    HasAudioFeatureProperties
  152. def setGenerationConfig(value: GenerationConfig): WhisperForCTC.this.type
    Attributes
    protected[nlp]
  153. final def setInputCols(value: String*): WhisperForCTC.this.type
    Definition Classes
    HasInputAnnotationCols
  154. def setInputCols(value: Array[String]): WhisperForCTC.this.type

    Overrides required annotators column if different than default

    Overrides required annotators column if different than default

    Definition Classes
    HasInputAnnotationCols
  155. def setIsMultilingual(value: Boolean): WhisperForCTC.this.type

  156. def setLanguage(value: String): WhisperForCTC.this.type

    Sets the language for the audio, formatted to e.g.

    Sets the language for the audio, formatted to e.g. <|en|>. Check the model description for supported languages.

  157. def setLazyAnnotator(value: Boolean): WhisperForCTC.this.type
    Definition Classes
    CanBeLazy
  158. def setMaxInputLength(value: Int): WhisperForCTC.this.type
    Definition Classes
    HasGeneratorProperties
  159. def setMaxOutputLength(value: Int): WhisperForCTC.this.type

    Definition Classes
    HasGeneratorProperties
  160. def setMinOutputLength(value: Int): WhisperForCTC.this.type

    Definition Classes
    HasGeneratorProperties
  161. def setModelIfNotSet(spark: SparkSession, tensorflowWrapper: Option[TensorflowWrapper], onnxWrappers: Option[EncoderDecoderWrappers]): WhisperForCTC.this.type

  162. def setNReturnSequences(beamNum: Int): WhisperForCTC.this.type

    Definition Classes
    HasGeneratorProperties
  163. def setNoRepeatNgramSize(value: Int): WhisperForCTC.this.type

    Definition Classes
    HasGeneratorProperties
  164. final def setOutputCol(value: String): WhisperForCTC.this.type

    Overrides annotation column name when transforming

    Overrides annotation column name when transforming

    Definition Classes
    HasOutputAnnotationCol
  165. def setPaddingSide(value: String): WhisperForCTC.this.type

    Definition Classes
    HasAudioFeatureProperties
  166. def setPaddingValue(value: Float): WhisperForCTC.this.type

    Definition Classes
    HasAudioFeatureProperties
  167. def setParent(parent: Estimator[WhisperForCTC]): WhisperForCTC
    Definition Classes
    Model
  168. def setPreprocessor(value: WhisperPreprocessor): WhisperForCTC.this.type
    Attributes
    protected[nlp]
  169. def setRandomSeed(value: Long): WhisperForCTC.this.type

    Definition Classes
    HasGeneratorProperties
  170. def setRepetitionPenalty(value: Double): WhisperForCTC.this.type

    Definition Classes
    HasGeneratorProperties
  171. def setReturnAttentionMask(value: Boolean): WhisperForCTC.this.type

    Definition Classes
    HasAudioFeatureProperties
  172. def setSamplingRate(value: Int): WhisperForCTC.this.type

    Definition Classes
    HasAudioFeatureProperties
  173. def setSignatures(value: Map[String, String]): WhisperForCTC.this.type

  174. def setTask(value: String): WhisperForCTC.this.type

    Sets the formatted task for the audio.

    Sets the formatted task for the audio. Either <|translate|> or <|transcribe|>.

    Only multilingual models can do translation.

    Definition Classes
    WhisperForCTC → HasGeneratorProperties
  175. def setTemperature(value: Double): WhisperForCTC.this.type

    Definition Classes
    HasGeneratorProperties
  176. def setTopK(value: Int): WhisperForCTC.this.type

    Definition Classes
    HasGeneratorProperties
  177. def setTopP(value: Double): WhisperForCTC.this.type

    Definition Classes
    HasGeneratorProperties
  178. def setVocabulary(value: Map[String, Int]): WhisperForCTC.this.type
  179. val signatures: MapFeature[AnnotatorType, AnnotatorType]

    It contains TF model signatures for the loaded saved model

  180. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  181. val task: Param[String]

    Set transformer task, e.g.

    Set transformer task, e.g. "summarize:" (Default: "").

    Definition Classes
    HasGeneratorProperties
  182. val temperature: DoubleParam

    The value used to module the next token probabilities (Default: 1.0)

    The value used to module the next token probabilities (Default: 1.0)

    Definition Classes
    HasGeneratorProperties
  183. def toString(): String
    Definition Classes
    Identifiable → AnyRef → Any
  184. val topK: IntParam

    The number of highest probability vocabulary tokens to keep for top-k-filtering (Default: 50)

    The number of highest probability vocabulary tokens to keep for top-k-filtering (Default: 50)

    Definition Classes
    HasGeneratorProperties
  185. val topP: DoubleParam

    If set to float < 1.0, only the most probable tokens with probabilities that add up to topP or higher are kept for generation (Default: 1.0)

    If set to float < 1.0, only the most probable tokens with probabilities that add up to topP or higher are kept for generation (Default: 1.0)

    Definition Classes
    HasGeneratorProperties
  186. final def transform(dataset: Dataset[_]): DataFrame

    Given requirements are met, this applies ML transformation within a Pipeline or stand-alone Output annotation will be generated as a new column, previous annotations are still available separately metadata is built at schema level to record annotations structural information outside its content

    Given requirements are met, this applies ML transformation within a Pipeline or stand-alone Output annotation will be generated as a new column, previous annotations are still available separately metadata is built at schema level to record annotations structural information outside its content

    dataset

    Dataset[Row]

    Definition Classes
    AnnotatorModel → Transformer
  187. def transform(dataset: Dataset[_], paramMap: ParamMap): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" )
  188. def transform(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" ) @varargs()
  189. final def transformSchema(schema: StructType): StructType

    requirement for pipeline transformation validation.

    requirement for pipeline transformation validation. It is called on fit()

    Definition Classes
    RawAnnotator → PipelineStage
  190. def transformSchema(schema: StructType, logging: Boolean): StructType
    Attributes
    protected
    Definition Classes
    PipelineStage
    Annotations
    @DeveloperApi()
  191. val uid: String
    Definition Classes
    WhisperForCTC → Identifiable
  192. def validate(schema: StructType): Boolean

    takes a Dataset and checks to see if all the required annotation types are present.

    takes a Dataset and checks to see if all the required annotation types are present.

    schema

    to be validated

    returns

    True if all the required types are present, else false

    Attributes
    protected
    Definition Classes
    RawAnnotator
  193. val vocabulary: MapFeature[String, Int]

    Vocabulary used to encode the words to ids

    Vocabulary used to encode the words to ids

    Attributes
    protected[nlp]
  194. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  195. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  196. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  197. def wrapColumnMetadata(col: Column): Column
    Attributes
    protected
    Definition Classes
    RawAnnotator
  198. def write: MLWriter
    Definition Classes
    ParamsAndFeaturesWritable → DefaultParamsWritable → MLWritable
  199. def writeOnnxModel(path: String, spark: SparkSession, onnxWrapper: OnnxWrapper, suffix: String, fileName: String): Unit
    Definition Classes
    WriteOnnxModel
  200. def writeOnnxModels(path: String, spark: SparkSession, onnxWrappersWithNames: Seq[(OnnxWrapper, String)], suffix: String, dataFileSuffix: String = "_data"): Unit
    Definition Classes
    WriteOnnxModel
  201. def writeTensorflowHub(path: String, tfPath: String, spark: SparkSession, suffix: String = "_use"): Unit
    Definition Classes
    WriteTensorflowModel
  202. def writeTensorflowModel(path: String, spark: SparkSession, tensorflow: TensorflowWrapper, suffix: String, filename: String, configProtoBytes: Option[Array[Byte]] = None): Unit
    Definition Classes
    WriteTensorflowModel
  203. def writeTensorflowModelV2(path: String, spark: SparkSession, tensorflow: TensorflowWrapper, suffix: String, filename: String, configProtoBytes: Option[Array[Byte]] = None, savedSignatures: Option[Map[String, String]] = None): Unit
    Definition Classes
    WriteTensorflowModel

Inherited from HasProtectedParams

Inherited from HasGeneratorProperties

Inherited from HasEngine

Inherited from WriteOnnxModel

Inherited from WriteTensorflowModel

Inherited from HasAudioFeatureProperties

Inherited from HasBatchedAnnotateAudio[WhisperForCTC]

Inherited from AnnotatorModel[WhisperForCTC]

Inherited from CanBeLazy

Inherited from RawAnnotator[WhisperForCTC]

Inherited from HasOutputAnnotationCol

Inherited from HasInputAnnotationCols

Inherited from HasOutputAnnotatorType

Inherited from ParamsAndFeaturesWritable

Inherited from HasFeatures

Inherited from DefaultParamsWritable

Inherited from MLWritable

Inherited from Model[WhisperForCTC]

Inherited from Transformer

Inherited from PipelineStage

Inherited from Logging

Inherited from Params

Inherited from Serializable

Inherited from Serializable

Inherited from Identifiable

Inherited from AnyRef

Inherited from Any

Parameters

A list of (hyper-)parameter keys this annotator can take. Users can set and get the parameter values through setters and getters, respectively.

Members

Parameter setters

Parameter getters