How to Use NVIDIA Canary-1B-v2 for ASR, Translation, and Automatic SRT Subtitle Export in Python
In this tutorial, we build a speech recognition and translation workflow using NVIDIA Canary-1B-v2. We begin by setting up the required audio, NeMo, NumPy, and SciPy dependencies, then load the Canary model on a GPU-enabled runtime for efficient inference. From there, we prepare audio into a clean 16 kHz mono format, perform English ASR, translate speech into multiple languages, generate word and segment timestamps, export translated subtitles as an SRT file, test long-form transcription, run b
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NVIDIA Canary-1B-v2 is a speech recognition model that can transcribe audio, translate speech into multiple languages, and generate timestamped subtitles. The tutorial demonstrates how to set up the necessary software dependencies, load the model on a GPU for efficient processing, prepare audio files in the required format, and run various tasks including English speech recognition, translation into supported languages, and automatic subtitle file generation. This workflow enables building a multilingual speech recognition and translation pipeline for applications like subtitle generation and large-scale transcription of audio files.
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