online feature

examples/libritts/cosyvoice/cosyvoice

@@ -1 +0,0 @@
-../../../cosyvoice

examples/libritts/cosyvoice/local/prepare_data.py

@@ -54,6 +54,7 @@ if __name__ == "__main__":
     parser.add_argument('--des_dir',
                         type=str)
     parser.add_argument('--instruct',
-                        type=str)
+                        type=str,
+                        default='')
     args = parser.parse_args()
     main()

examples/libritts/cosyvoice/run.sh

@@ -27,7 +27,7 @@ fi
 if [ ${stage} -le 1 ] && [ ${stop_stage} -ge 1 ]; then
   echo "Extract campplus speaker embedding, you will get spk2embedding.pt and utt2embedding.pt in data/$x dir"
   for x in train-clean-100 train-clean-360 train-other-500 dev-clean dev-other test-clean test-other; do
-    tools/extract_embedding.py --dir data/$x \
+    ../../../tools/extract_embedding.py --dir data/$x \
       --onnx_path $pretrained_model_dir/campplus.onnx
   done
 fi
@@ -35,7 +35,7 @@ fi
 if [ ${stage} -le 2 ] && [ ${stop_stage} -ge 2 ]; then
   echo "Extract discrete speech token, you will get utt2speech_token.pt in data/$x dir"
   for x in train-clean-100 train-clean-360 train-other-500 dev-clean dev-other test-clean test-other; do
-    tools/extract_speech_token.py --dir data/$x \
+    ../../../tools/extract_speech_token.py --dir data/$x \
       --onnx_path $pretrained_model_dir/speech_tokenizer_v1.onnx
   done
 fi
@@ -44,7 +44,7 @@ if [ ${stage} -le 3 ] && [ ${stop_stage} -ge 3 ]; then
   echo "Prepare required parquet format data, you should have prepared wav.scp/text/utt2spk/spk2utt/utt2embedding.pt/spk2embedding.pt/utt2speech_token.pt"
   for x in train-clean-100 train-clean-360 train-other-500 dev-clean dev-other test-clean test-other; do
     mkdir -p data/$x/parquet
-    tools/make_parquet_list.py --num_utts_per_parquet 1000 \
+    ../../../tools/make_parquet_list.py --num_utts_per_parquet 1000 \
       --num_processes 10 \
       --src_dir data/$x \
       --des_dir data/$x/parquet
@@ -69,7 +69,7 @@ if [ ${stage} -le 5 ] && [ ${stop_stage} -ge 5 ]; then
   for model in llm flow hifigan; do
     torchrun --nnodes=1 --nproc_per_node=$num_gpus \
         --rdzv_id=$job_id --rdzv_backend="c10d" --rdzv_endpoint="localhost:1234" \
-      cosyvoice/bin/train.py \
+      ../../../cosyvoice/bin/train.py \
       --train_engine $train_engine \
       --config conf/cosyvoice.yaml \
       --train_data data/train.data.list \

examples/libritts/cosyvoice/tools

@@ -1 +0,0 @@
-../../../tools

examples/libritts/cosyvoice2/conf/cosyvoice2.yaml

@@ -139,7 +139,7 @@ tokenize: !name:cosyvoice.dataset.processor.tokenize
     get_tokenizer: !ref <get_tokenizer>
     allowed_special: !ref <allowed_special>
 filter: !name:cosyvoice.dataset.processor.filter
-    max_length: 40960
+    max_length: 6000
     min_length: 100
     token_max_length: 200
     token_min_length: 1
@@ -158,7 +158,7 @@ feat_extractor: !name:matcha.utils.audio.mel_spectrogram
     center: False
 compute_fbank: !name:cosyvoice.dataset.processor.compute_fbank
     feat_extractor: !ref <feat_extractor>
-    token_mel_ratio: 2
+    num_frames: 960
 compute_f0: !name:cosyvoice.dataset.processor.compute_f0
     sample_rate: !ref <sample_rate>
     hop_size: 480

examples/libritts/cosyvoice2/cosyvoice

@@ -1 +0,0 @@
-../../../cosyvoice

examples/libritts/cosyvoice2/run.sh

@@ -24,27 +24,12 @@ if [ ${stage} -le 0 ] && [ ${stop_stage} -ge 0 ]; then
   done
 fi
 
-if [ ${stage} -le 1 ] && [ ${stop_stage} -ge 1 ]; then
-  echo "Extract campplus speaker embedding, you will get spk2embedding.pt and utt2embedding.pt in data/$x dir"
-  for x in train-clean-100 train-clean-360 train-other-500 dev-clean dev-other test-clean test-other; do
-    tools/extract_embedding.py --dir data/$x \
-      --onnx_path $pretrained_model_dir/campplus.onnx
-  done
-fi
-
-if [ ${stage} -le 2 ] && [ ${stop_stage} -ge 2 ]; then
-  echo "Extract discrete speech token, you will get utt2speech_token.pt in data/$x dir"
-  for x in train-clean-100 train-clean-360 train-other-500 dev-clean dev-other test-clean test-other; do
-    tools/extract_speech_token.py --dir data/$x \
-      --onnx_path $pretrained_model_dir/speech_tokenizer_v2.onnx
-  done
-fi
-
+# NOTE embedding/token extraction is not necessary now as we support online feature extraction
 if [ ${stage} -le 3 ] && [ ${stop_stage} -ge 3 ]; then
   echo "Prepare required parquet format data, you should have prepared wav.scp/text/utt2spk/spk2utt/utt2embedding.pt/spk2embedding.pt/utt2speech_token.pt"
   for x in train-clean-100 train-clean-360 train-other-500 dev-clean dev-other test-clean test-other; do
     mkdir -p data/$x/parquet
-    tools/make_parquet_list.py --num_utts_per_parquet 1000 \
+    ../../../tools/make_parquet_list.py --num_utts_per_parquet 1000 \
       --num_processes 10 \
       --src_dir data/$x \
       --des_dir data/$x/parquet
@@ -69,12 +54,13 @@ if [ ${stage} -le 5 ] && [ ${stop_stage} -ge 5 ]; then
   for model in llm flow hifigan; do
     torchrun --nnodes=1 --nproc_per_node=$num_gpus \
         --rdzv_id=$job_id --rdzv_backend="c10d" --rdzv_endpoint="localhost:1234" \
-      cosyvoice/bin/train.py \
+      ../../../cosyvoice/bin/train.py \
       --train_engine $train_engine \
       --config conf/cosyvoice2.yaml \
       --train_data data/train.data.list \
       --cv_data data/dev.data.list \
       --qwen_pretrain_path $pretrained_model_dir/CosyVoice-BlankEN \
+      --onnx_path $pretrained_model_dir \
       --model $model \
       --checkpoint $pretrained_model_dir/$model.pt \
       --model_dir `pwd`/exp/cosyvoice2/$model/$train_engine \

examples/libritts/cosyvoice2/run_dpo.sh

@@ -36,7 +36,7 @@ fi
 if [ ${stage} -le 1 ] && [ ${stop_stage} -ge 1 ]; then
   echo "Extract campplus speaker embedding, you will get spk2embedding.pt and utt2embedding.pt in data/$x dir"
   for x in train-clean-100 train-clean-360 train-other-500 dev-clean dev-other test-clean test-other; do
-    tools/extract_embedding.py --dir data/$x \
+    ../../../tools/extract_embedding.py --dir data/$x \
       --onnx_path $pretrained_model_dir/campplus.onnx
   done
 fi
@@ -44,7 +44,7 @@ fi
 if [ ${stage} -le 2 ] && [ ${stop_stage} -ge 2 ]; then
   echo "Extract discrete speech token, you will get utt2speech_token.pt in data/$x dir"
   for x in train-clean-100 train-clean-360 train-other-500 train-clean-100_reject train-clean-360_reject dev-clean dev-other test-clean test-other; do
-    tools/extract_speech_token.py --dir data/$x \
+    ../../../tools/extract_speech_token.py --dir data/$x \
       --onnx_path $pretrained_model_dir/speech_tokenizer_v2.onnx
   done
 fi
@@ -53,7 +53,7 @@ if [ ${stage} -le 3 ] && [ ${stop_stage} -ge 3 ]; then
   echo "Prepare required parquet format data, you should have prepared wav.scp/text/utt2spk/spk2utt/utt2embedding.pt/spk2embedding.pt/utt2speech_token.pt"
   for x in train-clean-100 train-clean-360 train-other-500 dev-clean dev-other test-clean test-other; do
     mkdir -p data/$x/parquet
-    tools/make_parquet_list.py --num_utts_per_parquet 1000 \
+    ../../../tools/make_parquet_list.py --num_utts_per_parquet 1000 \
       --num_processes 10 \
       --dpo \
       --src_dir data/$x \
@@ -80,11 +80,12 @@ if [ ${stage} -le 5 ] && [ ${stop_stage} -ge 5 ]; then
   for model in llm; do
     torchrun --nnodes=1 --nproc_per_node=$num_gpus \
         --rdzv_id=$job_id --rdzv_backend="c10d" --rdzv_endpoint="localhost:1234" \
-      cosyvoice/bin/train.py \
+      ../../../cosyvoice/bin/train.py \
       --train_engine $train_engine \
       --config conf/cosyvoice2.yaml \
       --train_data data/train.data.list \
       --cv_data data/dev.data.list \
+      --onnx_path $pretrained_model_dir \
       --qwen_pretrain_path $pretrained_model_dir/CosyVoice-BlankEN \
       --model $model \
       --checkpoint $pretrained_model_dir/$model.pt \

examples/libritts/cosyvoice2/tools

@@ -1 +0,0 @@
-../../../tools

examples/libritts/cosyvoice3/conf/cosyvoice3.yaml

@@ -129,7 +129,7 @@ tokenize: !name:cosyvoice.dataset.processor.tokenize
     get_tokenizer: !ref <get_tokenizer>
     allowed_special: !ref <allowed_special>
 filter: !name:cosyvoice.dataset.processor.filter
-    max_length: 40960
+    max_length: 6000
     min_length: 100
     token_max_length: 200
     token_min_length: 1
@@ -148,7 +148,7 @@ feat_extractor: !name:matcha.utils.audio.mel_spectrogram
     center: False
 compute_fbank: !name:cosyvoice.dataset.processor.compute_fbank
     feat_extractor: !ref <feat_extractor>
-    token_mel_ratio: 2
+    num_frames: 960
 compute_f0: !name:cosyvoice.dataset.processor.compute_f0
     sample_rate: !ref <sample_rate>
     hop_size: 480

examples/libritts/cosyvoice3/cosyvoice

@@ -1 +0,0 @@
-../../../cosyvoice

examples/libritts/cosyvoice3/run.sh

@@ -25,36 +25,20 @@ if [ ${stage} -le 0 ] && [ ${stop_stage} -ge 0 ]; then
   done
 fi
 
-if [ ${stage} -le 1 ] && [ ${stop_stage} -ge 1 ]; then
-  echo "Extract campplus speaker embedding, you will get spk2embedding.pt and utt2embedding.pt in data/$x dir"
-  for x in train-clean-100 train-clean-360 train-other-500 dev-clean dev-other test-clean test-other; do
-    tools/extract_embedding.py --dir data/$x \
-      --onnx_path $pretrained_model_dir/campplus.onnx
-  done
-fi
-
-if [ ${stage} -le 2 ] && [ ${stop_stage} -ge 2 ]; then
-  echo "Extract discrete speech token, you will get utt2speech_token.pt in data/$x dir"
-  for x in train-clean-100 train-clean-360 train-other-500 dev-clean dev-other test-clean test-other; do
-    tools/extract_speech_token.py --dir data/$x \
-      --onnx_path $pretrained_model_dir/speech_tokenizer_v3.onnx
-  done
-fi
-
+# NOTE embedding/token extraction is not necessary now as we support online feature extraction
 if [ ${stage} -le 3 ] && [ ${stop_stage} -ge 3 ]; then
   echo "Prepare required parquet format data, you should have prepared wav.scp/text/utt2spk/spk2utt/utt2embedding.pt/spk2embedding.pt/utt2speech_token.pt"
   for x in train-clean-100 train-clean-360 train-other-500 dev-clean dev-other test-clean test-other; do
     mkdir -p data/$x/parquet
-    tools/make_parquet_list.py --num_utts_per_parquet 1000 \
+    ../../../tools/make_parquet_list.py --num_utts_per_parquet 1000 \
       --num_processes 10 \
-      --instruct \
       --src_dir data/$x \
       --des_dir data/$x/parquet
   done
 fi
 
 # train llm
-export CUDA_VISIBLE_DEVICES="0,1,2,3"
+export CUDA_VISIBLE_DEVICES="0"
 num_gpus=$(echo $CUDA_VISIBLE_DEVICES | awk -F "," '{print NF}')
 job_id=1986
 dist_backend="nccl"
@@ -71,12 +55,13 @@ if [ ${stage} -le 5 ] && [ ${stop_stage} -ge 5 ]; then
   for model in llm flow hifigan; do
     torchrun --nnodes=1 --nproc_per_node=$num_gpus \
         --rdzv_id=$job_id --rdzv_backend="c10d" --rdzv_endpoint="localhost:1234" \
-      cosyvoice/bin/train.py \
+      ../../../cosyvoice/bin/train.py \
       --train_engine $train_engine \
       --config conf/cosyvoice3.yaml \
       --train_data data/train.data.list \
       --cv_data data/dev.data.list \
       --qwen_pretrain_path $pretrained_model_dir/CosyVoice-BlankEN \
+      --onnx_path $pretrained_model_dir \
       --model $model \
       --checkpoint $pretrained_model_dir/$model.pt \
       --model_dir `pwd`/exp/cosyvoice3/$model/$train_engine \

examples/libritts/cosyvoice3/tools

@@ -1 +0,0 @@
-../../../tools

examples/magicdata-read/cosyvoice/cosyvoice

@@ -1 +0,0 @@
-../../../cosyvoice

examples/magicdata-read/cosyvoice/run.sh

@@ -27,7 +27,7 @@ fi
 if [ ${stage} -le 1 ] && [ ${stop_stage} -ge 1 ]; then
   echo "Extract campplus speaker embedding, you will get spk2embedding.pt and utt2embedding.pt in data/$x dir"
   for x in dev test train; do
-    tools/extract_embedding.py --dir data/$x \
+    ../../../tools/extract_embedding.py --dir data/$x \
       --onnx_path $pretrained_model_dir/campplus.onnx
   done
 fi
@@ -35,7 +35,7 @@ fi
 if [ ${stage} -le 2 ] && [ ${stop_stage} -ge 2 ]; then
   echo "Extract discrete speech token, you will get utt2speech_token.pt in data/$x dir"
   for x in dev test train; do
-    tools/extract_speech_token.py --dir data/$x \
+    ../../../tools/extract_speech_token.py --dir data/$x \
       --onnx_path $pretrained_model_dir/speech_tokenizer_v1.onnx
   done
 fi
@@ -44,7 +44,7 @@ if [ ${stage} -le 3 ] && [ ${stop_stage} -ge 3 ]; then
   echo "Prepare required parquet format data, you should have prepared wav.scp/text/utt2spk/spk2utt/utt2embedding.pt/spk2embedding.pt/utt2speech_token.pt"
   for x in dev test train; do
     mkdir -p data/$x/parquet
-    tools/make_parquet_list.py --num_utts_per_parquet 1000 \
+    ../../../tools/make_parquet_list.py --num_utts_per_parquet 1000 \
       --num_processes 10 \
       --src_dir data/$x \
       --des_dir data/$x/parquet
@@ -69,7 +69,7 @@ if [ ${stage} -le 5 ] && [ ${stop_stage} -ge 5 ]; then
   for model in llm flow hifigan; do
     torchrun --nnodes=1 --nproc_per_node=$num_gpus \
         --rdzv_id=$job_id --rdzv_backend="c10d" --rdzv_endpoint="localhost:0" \
-      cosyvoice/bin/train.py \
+      ../../../cosyvoice/bin/train.py \
       --train_engine $train_engine \
       --config conf/cosyvoice.yaml \
       --train_data data/train.data.list \

examples/magicdata-read/cosyvoice/tools

@@ -1 +0,0 @@
-../../../tools