Canary-1b on long audio file.
any leads?
 Hi, thanks for the question and interest. We are working on improving the performance of canary on long form audio. We do also plan to release the model with timestamp generation soon.  This issue is stale because it has been open for 30 days with no activity. Remove stale label or comment or this will be closed in 7 days. This issue was closed because it has been inactive for 7 days since being marked as stale.
Hi,
I am trying to make working canary-1b on long audio file. Inspiring my self from [https://github.com/NVIDIA/NeMo/blob/b5798ded9f27168db9d7d77cbe4f9da80bf49268/examples/asr/asr_chunked_inference/aed/speech_to_text_aed_chunked_infer.py#L19](url) this notebook.
But the results are not convincing in regards of what whisper can do. Seems that script just chunk the audio file but do not share context to help th model to transcribe.. More over it does not include a VAD model, and it seems difficult to timestamp the segments.
Does anyone have succed to have something close to the whisper output, with better quality?
Thanks