Description
Pretrained Wav2Vec2ForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.future_swahili_asr_24_02_2025 is a Swahili (macrolanguage) model originally trained by Futuresony.
How to use
audioAssembler = AudioAssembler() \
.setInputCol("audio_content") \
.setOutputCol("audio_assembler")
speechToText = Wav2Vec2ForCTC.pretrained("future_swahili_asr_24_02_2025","sw") \
.setInputCols(["audio_assembler"]) \
.setOutputCol("text")
pipeline = Pipeline().setStages([audioAssembler, speechToText])
pipelineModel = pipeline.fit(data)
pipelineDF = pipelineModel.transform(data)
val audioAssembler = new DocumentAssembler()
.setInputCols("audio_content")
.setOutputCols("audio_assembler")
val speechToText = Wav2Vec2ForCTC.pretrained("future_swahili_asr_24_02_2025", "sw")
.setInputCols(Array("audio_assembler"))
.setOutputCol("text")
val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
val pipelineModel = pipeline.fit(data)
val pipelineDF = pipelineModel.transform(data)
Model Information
| Model Name: | future_swahili_asr_24_02_2025 |
| Compatibility: | Spark NLP 5.5.1+ |
| License: | Open Source |
| Edition: | Official |
| Input Labels: | [audio_assembler] |
| Output Labels: | [text] |
| Language: | sw |
| Size: | 1.2 GB |
References
https://huggingface.co/Futuresony/Future-sw_ASR-24-02-2025