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openai/whisper-large-v3-turbo - AI Audio Models Tool

Overview

A finetuned, pruned variant of Whisper large-v3 for automatic speech recognition and speech translation. It reduces decoding layers from 32 to 4 to enable much faster inference with only a minor quality trade-off. Supports transcription and translation across 99 languages and integrates with Hugging Face Transformers for easy deployment in ML workflows.

Key Features

  • Pruned architecture: decoding layers reduced from 32 to 4 for faster inference.
  • Designed for automatic speech recognition and speech-to-text translation.
  • Supports transcription and translation across 99 languages.
  • Integrates with Hugging Face Transformers for end-to-end workflows.
  • Optimized for lower-latency inference with minimal quality impact.

Ideal Use Cases

  • Low-latency transcription pipelines where speed matters.
  • Multilingual transcription and speech translation across 99 languages.
  • Batch processing of large audio datasets with faster throughput.
  • Embedding ASR into Hugging Face–based applications and demos.

Getting Started

  • Open the model page on Hugging Face to view usage notes.
  • Install Hugging Face Transformers and any required audio libraries.
  • Load openai/whisper-large-v3-turbo via the Transformers API.
  • Run the model on sample audio to verify transcription and translation.

Pricing

Pricing not disclosed in the provided model information. Check the Hugging Face model page or provider for current pricing and licensing.

Limitations

  • Slight reduction in transcription quality compared with the full 32-layer model due to pruning.
  • Trade-off favors inference speed over absolute maximum accuracy in some audio conditions.

Key Information

  • Category: Audio Models
  • Type: AI Audio Models Tool
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