Is it possible to bring back old Kaldi's chain-model style training back to Icefall

[David Lin]

(PS: It is hybrid problem between Kaldi and K2/Icefall)

Recently I need to port Kaldi's chain model training to Icefall.

Alhough Icefall's method is with better result, but we are having very not-normal setup, such that Icefall's training method (based on CTC) does not work for us. However, Icefall have lots of new algorithm, which is very hard to port one-by-one to Kaldi.

Therefore, I am trying to use alignment file from Kaldi, to feed those alignment-data into Icefall training flow, and use chain-style training method; which is, to convert alignment (originally it is lattice in Kaldi) to training-FST-graph, and use it inside Icefall training.

However, converting alignment from Kaldi to Icefall, while putting alignment into Icefall-training-FST-graph, is very confusing. For example, I am not sure how I can turn Kaldi alignment into Icefall-training-FST graph.

Is there any documentation, or any example to port Kaldi's chain model training method back to Icefall?

PS: Chain model here is the non-E2E version of chain model in old Kaldi, not the E2E one.

[ita...@gmail.com]

follow up question   -   is there a similar forum for icefall/k2 ?  

ב-יום רביעי, 12 באפריל 2023 בשעה 13:42:48 UTC+3, David Lin כתב/ה:

[Daniel Povey]

you can ask questions for k2/icefall via issues on the github.

I'm afraid we don't have a plan to port chain-type training.

Yes, for ~100 hours of data it does work better.

Possibly a different network topology would work better for that amount of data but we haven't really spent time tuning for that scenario, I'm afraid.

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[David Lin]

Got it. Thank you Daniel.

Daniel Povey 在 2023年5月15日 星期一晚上11:22:58 [UTC+8] 的信中寫道：