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@vimalmanohar vimalmanohar commented Dec 3, 2016

This pull request is a place holder for all the modifications required for training nnet3 models for speech activity detection, music detection and similar tasks and using those models on test data. This includes recipes for

  1. Training SAD and music detection model on Fisher and Babel corpus corrupted with MUSAN music and noise.
  2. Creating segments for Babel dev data (evalutated on WER), AMI dev data (evalutated on DER), RT04 (evaluated on DER)
  3. Music detection task on Broadcast news

This PR request also contains generic tools for segmentation, nnet3 modifications for training with multi-task objectives and other generic utility scripts and binaries.

@vimalmanohar vimalmanohar changed the title Asr diarization clean WIP: Segmentation using nnet3 for diarization and ASR Dec 3, 2016
@vimalmanohar vimalmanohar force-pushed the asr_diarization_clean branch 3 times, most recently from 0917238 to 83cbdd6 Compare December 9, 2016 19:15
…softmax per row, copy-matrix apply-log, matrix-add-offset, matrix-dot-product
…gments_for_data, get_utt2num_frames, get_reco2num_frames, get_reco2dur, convert_ali_to_vec, quantize_vector, convert_rttm_to_utt2spk_and_segments, get_frame_shift_from_config
…reco2file_and_channel and modify subset_data_dir.sh to add more options
@vimalmanohar vimalmanohar force-pushed the master branch 2 times, most recently from db310c4 to b4ef16d Compare January 6, 2017 19:22
@vimalmanohar vimalmanohar force-pushed the master branch 2 times, most recently from eff681c to 1dabfa5 Compare January 16, 2017 19:06
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@danpovey This is the pull request. But I have made many script changes in a different branch after this e.g. in #5 and #9.

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danpovey commented Feb 16, 2017 via email

vimalmanohar pushed a commit that referenced this pull request Jan 13, 2019
Added dereverberation measures, cln evaluation and updated RESULTS
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3 participants