How to Fine-Tune Nemotron 3.5 ASR for Your Language, Domain, or Accent

NVIDIA's Nemotron 3.5 ASR is a cutting-edge, multilingual speech-to-text model that transcribes audio in real-time across 40 language-locales using a single 600 million-parameter checkpoint, with built-in punctuation and capitalization. It overcomes traditional challenges in multilingual speech recognition, such as the need for multiple models or APIs, high latency, and lack of language flexibility, by employing a Cache-Aware FastConformer-RNNT architecture that reduces redundant computations. This model is available as open weights on Hugging Face, allowing users to inspect, fine-tune, and deploy it without additional API dependencies. Fine-tuning the model can significantly improve its accuracy for specific languages, domains, or accents, particularly benefiting languages with less pretraining data. The model's flexibility extends to various applications, including sub-second voice agents, live multilingual meeting captions, and on-device transcription, making it a versatile tool for building multilingual speech applications.

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