Merge branch 'master' into patch-1

Author: danpovey

cmake/gen_cmake_skeleton.py

@@ -269,7 +269,7 @@ def gen_code(self):
 
         if len(self.depends) > 0:
             ret.append("target_link_libraries(" + self.target_name + " PUBLIC")
-            for d in self.depends:
+            for d in self.depends + ['-lcblas', '-llapack']:
                 ret.append("    " + d)
             ret.append(")\n")
 

docker/ubuntu22.04-cuda12.2.0/Dockerfile

@@ -0,0 +1,46 @@
+FROM nvidia/cuda:12.2.0-devel-ubuntu22.04
+LABEL maintainer="[email protected]"
+
+RUN apt-get update && \
+    apt-get install -y --no-install-recommends \
+        build-essential \
+        g++ \
+        make \
+        automake \
+        bzip2 \
+        unzip \
+        wget \
+        sox \
+        libtool \
+        git \
+        subversion \
+        python2.7 \
+        python3 \
+        zlib1g-dev \
+        ca-certificates \
+        gfortran \
+        patch \
+        ffmpeg \
+        vim && \
+    apt-get update && \
+    apt-get install -y --no-install-recommends\
+        software-properties-common && \
+    apt-add-repository multiverse && \
+    apt-get update && \
+    yes | DEBIAN_FRONTEND=noninteractive apt-get install -yqq --no-install-recommends\
+        intel-mkl && \
+    rm -rf /var/lib/apt/lists/*
+
+RUN ln -s /usr/bin/python2.7 /usr/bin/python
+
+RUN git clone --depth 1 https://github.com/kaldi-asr/kaldi.git /opt/kaldi && \
+    cd /opt/kaldi/tools && \
+    make -j $(nproc) && \
+    cd /opt/kaldi/src && \
+    ./configure --shared --use-cuda && \
+    make depend -j $(nproc) && \
+    make -j $(nproc) && \
+    find /opt/kaldi  -type f \( -name "*.o" -o -name "*.la" -o -name "*.a" \) -exec rm {} \; && \
+    rm -rf /opt/kaldi/.git
+
+WORKDIR /opt/kaldi/

egs/ami/s5/run_ihm.sh

@@ -17,7 +17,7 @@ set -euxo pipefail
 # Path where AMI gets downloaded (or where locally available):
 AMI_DIR=$PWD/wav_db # Default,
 case $(hostname -d) in
-  fit.vutbr.cz) AMI_DIR=/mnt/matylda5/iveselyk/KALDI_AMI_WAV ;; # BUT,
+  fit.vutbr.cz) AMI_DIR=/mnt/matylda2/data/AMI_KALDI_DOWNLOAD ;; # BUT,
   clsp.jhu.edu) AMI_DIR=/export/corpora4/ami/amicorpus ;; # JHU,
   cstr.ed.ac.uk) AMI_DIR= ;; # Edinburgh,
 esac

egs/ami/s5/run_mdm.sh

@@ -10,7 +10,7 @@ mic=mdm$nmics
 # Path where AMI gets downloaded (or where locally available):
 AMI_DIR=$PWD/wav_db # Default,
 case $(hostname -d) in
-  fit.vutbr.cz) AMI_DIR=/mnt/matylda5/iveselyk/KALDI_AMI_WAV ;; # BUT,
+  fit.vutbr.cz) AMI_DIR=/mnt/matylda2/data/AMI_KALDI_DOWNLOAD ;; # BUT,
   clsp.jhu.edu) AMI_DIR=/export/corpora4/ami/amicorpus ;; # JHU,
   cstr.ed.ac.uk) AMI_DIR= ;; # Edinburgh,
 esac

egs/ami/s5/run_sdm.sh

@@ -17,7 +17,7 @@ set -euxo pipefail
 # Path where AMI gets downloaded (or where locally available):
 AMI_DIR=$PWD/wav_db # Default,
 case $(hostname -d) in
-  fit.vutbr.cz) AMI_DIR=/mnt/matylda5/iveselyk/KALDI_AMI_WAV ;; # BUT,
+  fit.vutbr.cz) AMI_DIR=/mnt/matylda2/data/AMI_KALDI_DOWNLOAD ;; # BUT,
   clsp.jhu.edu) AMI_DIR=/export/corpora4/ami/amicorpus ;; # JHU,
   cstr.ed.ac.uk) AMI_DIR= ;; # Edinburgh,
 esac

egs/ami/s5b/cmd.sh

@@ -15,7 +15,7 @@ export decode_cmd="queue.pl --mem 2G"
 # the use of cuda_cmd is deprecated, used only in 'nnet1',
 export cuda_cmd="queue.pl --gpu 1 --mem 20G"
 
-if [[ "$(hostname -f)" == "*.fit.vutbr.cz" ]]; then
+if [[ "$(hostname -d)" == "fit.vutbr.cz" ]]; then
   queue_conf=$HOME/queue_conf/default.conf # see example /homes/kazi/iveselyk/queue_conf/default.conf,
   export train_cmd="queue.pl --config $queue_conf --mem 2G --matylda 0.2"
   export decode_cmd="queue.pl --config $queue_conf --mem 3G --matylda 0.1"

egs/ami/s5b/conf/ami_beamformit.cfg

@@ -0,0 +1,50 @@
+#BeamformIt sample configuration file for AMI data (http://groups.inf.ed.ac.uk/ami/download/)
+
+# scrolling size to compute the delays
+scroll_size = 250
+
+# cross correlation computation window size
+window_size = 500
+
+#amount of maximum points for the xcorrelation taken into account
+nbest_amount = 4
+
+#flag wether to apply an automatic noise thresholding 
+do_noise_threshold = 1
+
+#Percentage of frames with lower xcorr taken as noisy
+noise_percent = 10
+
+######## acoustic modelling parameters
+
+#transition probabilities weight for multichannel decoding
+trans_weight_multi = 25
+trans_weight_nbest = 25
+
+###
+
+#flag wether to print the feaures after setting them, or not
+print_features = 1
+
+#flag wether to use the bad frames in the sum process
+do_avoid_bad_frames = 1
+
+#flag to use the best channel (SNR) as a reference
+#defined from command line
+do_compute_reference = 1
+
+#flag wether to use a uem file or not(process all the file)
+do_use_uem_file = 0
+
+#flag wether to use an adaptative weights scheme or fixed weights
+do_adapt_weights = 1
+
+#flag wether to output the sph files or just run the system to create the auxiliary files
+do_write_sph_files = 1
+
+####directories where to store/retrieve info####
+#channels_file = ./cfg-files/channels
+
+#show needs to be passed as argument normally, here a default one is given just in case
+#show_id = Ttmp
+

egs/ami/s5b/run.sh

@@ -28,7 +28,7 @@ set -euo pipefail
 # Path where AMI gets downloaded (or where locally available):
 AMI_DIR=$PWD/wav_db # Default,
 case $(hostname -d) in
-  fit.vutbr.cz) AMI_DIR=/mnt/matylda5/iveselyk/KALDI_AMI_WAV ;; # BUT,
+  fit.vutbr.cz) AMI_DIR=/mnt/matylda2/data/AMI_KALDI_DOWNLOAD ;; # BUT,
   clsp.jhu.edu) AMI_DIR=/export/corpora4/ami/amicorpus ;; # JHU,
   cstr.ed.ac.uk) AMI_DIR= ;; # Edinburgh,
 esac

egs/ami/s5c/run.sh

@@ -3,7 +3,7 @@
 # Apache 2.0.
 #
 # This recipe performs diarization for the mix-headset data in the
-# AMI dataset. The x-vector extractor we use is trained on VoxCeleb v2 
+# AMI dataset. The x-vector extractor we use is trained on VoxCeleb v2
 # corpus with simulated RIRs. We use oracle SAD in this recipe.
 # This recipe demonstrates the following:
 # 1. Diarization using x-vector and clustering (AHC, VBx, spectral)
@@ -38,7 +38,7 @@ diarizer_type=spectral  # must be one of (ahc, spectral, vbx)
 # Path where AMI gets downloaded (or where locally available):
 AMI_DIR=$PWD/wav_db # Default,
 case $(hostname -d) in
-  fit.vutbr.cz) AMI_DIR=/mnt/matylda5/iveselyk/KALDI_AMI_WAV ;; # BUT,
+  fit.vutbr.cz) AMI_DIR=/mnt/matylda2/data/AMI_KALDI_DOWNLOAD ;; # BUT,
   clsp.jhu.edu) AMI_DIR=/export/corpora5/amicorpus ;; # JHU,
   cstr.ed.ac.uk) AMI_DIR= ;; # Edinburgh,
 esac
@@ -57,7 +57,7 @@ if [ $stage -le 1 ]; then
   local/ami_download.sh $mic $AMI_DIR
 fi
 
-# Prepare data directories. 
+# Prepare data directories.
 if [ $stage -le 2 ]; then
   # Download the data split and references from BUT's AMI setup
   if ! [ -d AMI-diarization-setup ]; then
@@ -120,7 +120,7 @@ if [ $stage -le 6 ]; then
      transform-vec $model_dir/xvectors_plda_train/transform.mat ark:- ark:- |\
       ivector-normalize-length ark:-  ark:- |" \
     $model_dir/xvectors_plda_train/plda || exit 1;
-  
+
   cp $model_dir/xvectors_plda_train/plda $model_dir/
   cp $model_dir/xvectors_plda_train/transform.mat $model_dir/
   cp $model_dir/xvectors_plda_train/mean.vec $model_dir/

egs/gop_speechocean762/s5/local/visualize_feats.py

@@ -8,6 +8,7 @@
 import random
 import kaldi_io
 import seaborn as sns
+import numpy as np
 from collections import Counter
 from sklearn.manifold import TSNE
 from utils import load_human_scores, load_phone_symbol_table
@@ -62,6 +63,9 @@ def main():
                                   min(args.samples, len(lables)))
     features, lables = list(zip(*sampled_paris))
 
+    # Convert the tuple of arrays to a single 2D array
+    features = np.vstack(features)
+
     # Draw scatters
     label_counter = Counter(lables)
     colors = sns.color_palette("colorblind", len(label_counter))