Open uni-manjunath-ke opened 1 year ago
fast_beam_search
depends on k2. If you want to use fast_beam_search, please use k2-fsa/sherap.
We are going to support HLG decoding in sherpa-onnx. If you want to use a lexicon or/and an n-gram LM in decoding, then you may find HLG decoding interesting.
Please also have a look at https://github.com/k2-fsa/icefall/pull/1275
Sure, Thanks. Ya, we are interested in HLG. Hoping to see this HLG code at https://github.com/k2-fsa/icefall/pull/1275 merged soon and available for usage.
Hi @csukuangfj , Just wanted to confirm, if the HLG code at https://github.com/k2-fsa/icefall/pull/1275 is only for CTC, or it can be used with zipformers as well. Could you please confirm. Because, we are interested in Zipformer models for now.
Currently, I see in https://github.com/k2-fsa/icefall/pull/1275 that HLG support is added for ICefall, When can we expect this support to be ported for sherpa-onnx? or Is that already ported to Sherpa-onnx? Thanks
Currently, I see in k2-fsa/icefall#1275 that HLG support is added for ICefall, When can we expect this support to be ported for sherpa-onnx? or Is that already ported to Sherpa-onnx? Thanks
please see https://github.com/k2-fsa/sherpa-onnx/pull/349
We will finish it in two weeks.
if the HLG code at https://github.com/k2-fsa/icefall/pull/1275 is only for CTC
Yes, you are right. It is only for CTC.
it can be used with zipformers as well
Zipformer is a kind of neural network, while ctc is a kind of loss function. They are two different things. If you train a zipformer using CTC loss, then you can use HLG decoding with zipformer. If you train a zipformer using transducer loss, then you cannot use HLG decoding with zipformer.
Currently, I see in k2-fsa/icefall#1275 that HLG support is added for ICefall, When can we expect this support to be ported for sherpa-onnx? or Is that already ported to Sherpa-onnx? Thanks
@uni-manjunath-ke
https://github.com/k2-fsa/sherpa-onnx/pull/349
The C++ part is usable now.
Thank you.
I found that the fast-beam-search decoding is currently not supported in sherpa-onnx. Is this activity is planned for future? If yes, when can this be expected (timeline)?
In specific, do you plan to support fast-beam-search-with-lg. Because, currently, the fast-beam-search-with-lg is not supported by zipformer/streaming-decode.py. Thanks