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  • John Snow Labs
  • Sep 26, 2022

Lithuanian asr_wav2vec2_large_xlsr_53_lithuanian_by_DeividasM TFWav2Vec2ForCTC from DeividasM

  • wav2vec2
  • lt
  • audio
  • open_source
  • asr

Description

Pretrained Wav2vec2 model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.asr_wav2vec2_large_xlsr_53_lithuanian_by_DeividasM is a Lithuanian model originally trained by DeividasM.

NOTE: This model only works on a CPU, if you need to use this model on a GPU device please use asr_wav2vec2_large_xlsr_53_lithuanian_by_DeividasM_gpu

Download Copy S3 URI

How to use


audio_assembler = AudioAssembler() \
    .setInputCol("audio_content") \
    .setOutputCol("audio_assembler")

speech_to_text = Wav2Vec2ForCTC \
    .pretrained("asr_wav2vec2_large_xlsr_53_lithuanian_by_DeividasM", "lt")\
    .setInputCols("audio_assembler") \
    .setOutputCol("text")

pipeline = Pipeline(stages=[
  audio_assembler,
  speech_to_text,
])

pipelineModel = pipeline.fit(audioDf)

pipelineDF = pipelineModel.transform(audioDf)


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

val speechToText = Wav2Vec2ForCTC
    .pretrained("asr_wav2vec2_large_xlsr_53_lithuanian_by_DeividasM", "lt")
    .setInputCols("audio_assembler") 
    .setOutputCol("text") 

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

val pipelineModel = pipeline.fit(audioDf)

val pipelineDF = pipelineModel.transform(audioDf)

Model Information

Model Name: asr_wav2vec2_large_xlsr_53_lithuanian_by_DeividasM
Compatibility: Spark NLP 4.2.0+
License: Open Source
Edition: Official
Input Labels: [audio_assembler]
Output Labels: [text]
Language: lt
Size: 1.2 GB