icefall/egs/alimeeting/ASR_v2/README.md

Introduction

This recipe trains multi-domain ASR models for AliMeeting. By multi-domain, we mean that we train a single model on close-talk and far-field conditions. This recipe optionally uses [GSS]-based enhancement for far-field array microphone. We pool data in the following 4 ways and train a single model on the pooled data:

(i) individual headset microphone (IHM) (ii) IHM with simulated reverb (iii) Single distant microphone (SDM) (iv) GSS-enhanced array microphones

This is different from alimeeting/ASR since that recipe trains a model only on the far-field audio. Additionally, we use text normalization here similar to the original M2MeT challenge, so the results should be more comparable to those from Table 4 of the paper.

The following additional packages need to be installed to run this recipe:

• pip install jieba
• pip install paddlepaddle
• pip install git+https://github.com/desh2608/gss.git

./RESULTS.md contains the latest results.

Performance Record

pruned_transducer_stateless7

The following are decoded using modified_beam_search:

Evaluation set	eval WER	test WER
IHM	9.58	11.53
SDM	23.37	25.85
MDM (GSS-enhanced)	11.82	14.22

See RESULTS for details.