Fix wewetspeech prepare.sh

egs/gigaspeech/KWS/prepare.sh

@@ -49,6 +49,7 @@ if [ $stage -le 0 ] && [ $stop_stage -ge 0 ]; then
     pushd data
     ln -svf $(realpath ../ASR/data/lang_bpe_500) .
     popd
+    touch data/fbank/.gigaspeech.done
   else
     log "Gigaspeech dataset already exists, skipping."
   fi
@@ -63,7 +64,7 @@ if [ $stage -le 1 ] && [ $stop_stage -ge 1 ]; then
     ln -svf $(realpath ./open-commands/EN/small/commands.txt) commands_small.txt
     ln -svf $(realpath ./open-commands/EN/large/commands.txt) commands_large.txt
     pushd open-commands
-    ./script/prepare.sh --stage 3 --stop-stage 3 
+    ./script/prepare.sh --stage 2 --stop-stage 2
     ./script/prepare.sh --stage 6 --stop-stage 6
     popd
     popd

egs/gigaspeech/KWS/zipformer/decode.py

@@ -186,13 +186,6 @@ def get_parser():
         help="The default threshold (probability) to trigger the keyword.",
     )
 
-    parser.add_argument(
-        "--keywords-version",
-        type=str,
-        default="",
-        help="The keywords configuration version, just to save results to different files.",
-    )
-
     parser.add_argument(
         "--num-tailing-blanks",
         type=int,
@@ -222,7 +215,7 @@ def decode_one_batch(
     model: nn.Module,
     sp: spm.SentencePieceProcessor,
     batch: dict,
-    kws_graph: Optional[ContextGraph] = None,
+    keywords_graph: Optional[ContextGraph] = None,
 ) -> List[List[Tuple[str, Tuple[int, int]]]]:
     """Decode one batch and return the result in a list.
 
@@ -242,7 +235,7 @@ def decode_one_batch(
         It is the return value from iterating
         `lhotse.dataset.K2SpeechRecognitionDataset`. See its documentation
         for the format of the `batch`.
-      kws_graph:
+      keywords_graph:
         The graph containing keywords.
     Returns:
       Return the decoding result. See above description for the format of
@@ -274,7 +267,7 @@ def decode_one_batch(
         model=model,
         encoder_out=encoder_out,
         encoder_out_lens=encoder_out_lens,
-        keywords_graph=kws_graph,
+        keywords_graph=keywords_graph,
         beam=params.beam,
         num_tailing_blanks=params.num_tailing_blanks,
         blank_penalty=params.blank_penalty,
@@ -295,7 +288,7 @@ def decode_dataset(
     params: AttributeDict,
     model: nn.Module,
     sp: spm.SentencePieceProcessor,
-    kws_graph: ContextGraph,
+    keywords_graph: ContextGraph,
     keywords: Set[str],
     test_only_keywords: bool,
 ) -> Tuple[List[Tuple[str, List[str], List[str]]], KwMetric]:
@@ -310,7 +303,7 @@ def decode_dataset(
         The neural model.
       sp:
         The BPE model.
-      kws_graph:
+      keywords_graph:
         The graph containing keywords.
     Returns:
       Return a dict, whose key may be "greedy_search" if greedy search
@@ -341,7 +334,7 @@ def decode_dataset(
             params=params,
             model=model,
             sp=sp,
-            kws_graph=kws_graph,
+            keywords_graph=keywords_graph,
             batch=batch,
         )
 
@@ -459,7 +452,7 @@ def save_results(
             s += f"\tPrecision: {precision:.3f}\n"
             s += f"\tRecall(PPR): {recall:.3f}\n"
             s += f"\tFPR: {fpr:.3f}\n"
-            s += f"\tF1: {2 * precision * recall / (precision + recall):.3f}\n"
+            s += f"\tF1: {0.0 if precision * recall == 0 else 2 * precision * recall / (precision + recall):.3f}\n"
             if key != "all":
                 s += f"\tTP list: {' # '.join(item.TP_list)}\n"
                 s += f"\tFP list: {' # '.join(item.FP_list)}\n"
@@ -505,7 +498,7 @@ def main():
     params.suffix += f"-tailing-blanks-{params.num_tailing_blanks}"
     if params.blank_penalty != 0:
         params.suffix += f"-blank-penalty-{params.blank_penalty}"
-    params.suffix += f"-version-{params.keywords_version}"
+    params.suffix += f"-keywords-{params.keywords_file.split('/')[-1]}"
 
     setup_logger(f"{params.res_dir}/log-decode-{params.suffix}")
     logging.info("Decoding started")
@@ -555,10 +548,10 @@ def main():
 
     params.keywords_config = "".join(keywords_config)
 
-    kws_graph = ContextGraph(
+    keywords_graph = ContextGraph(
         context_score=params.keywords_score, ac_threshold=params.keywords_threshold
     )
-    kws_graph.build(
+    keywords_graph.build(
         token_ids=token_ids,
         phrases=phrases,
         scores=keywords_scores,
@@ -677,7 +670,7 @@ def main():
             params=params,
             model=model,
             sp=sp,
-            kws_graph=kws_graph,
+            keywords_graph=keywords_graph,
             keywords=keywords,
             test_only_keywords="fsc" in test_set,
         )

egs/gigaspeech/KWS/zipformer/train.py

@@ -276,7 +276,7 @@ def get_parser():
     return parser
 
 
-def add_model_arguments(parser: argparse.ArgumentParser):
+def add_training_arguments(parser: argparse.ArgumentParser):
     parser.add_argument(
         "--world-size",
         type=int,

egs/librispeech/ASR/pruned_transducer_stateless2/beam_search.py

@@ -993,7 +993,7 @@ def keywords_search(
     """
     assert encoder_out.ndim == 3, encoder_out.shape
     assert encoder_out.size(0) >= 1, encoder_out.size(0)
-    assert context_graph is not None
+    assert keywords_graph is not None
 
     packed_encoder_out = torch.nn.utils.rnn.pack_padded_sequence(
         input=encoder_out,
@@ -1018,7 +1018,7 @@ def keywords_search(
             Hypothesis(
                 ys=[-1] * (context_size - 1) + [blank_id],
                 log_prob=torch.zeros(1, dtype=torch.float32, device=device),
-                context_state=context_graph.root,
+                context_state=keywords_graph.root,
                 timestamp=[],
                 ac_probs=[],
             )
@@ -1125,7 +1125,7 @@ def keywords_search(
                         context_score,
                         new_context_state,
                         _,
-                    ) = context_graph.forward_one_step(hyp.context_state, new_token)
+                    ) = keywords_graph.forward_one_step(hyp.context_state, new_token)
                     new_num_tailing_blanks = 0
                     if new_context_state.token == -1:  # root
                         new_ys[-context_size:] = [-1] * (context_size - 1) + [blank_id]
@@ -1143,7 +1143,7 @@ def keywords_search(
                 B[i].add(new_hyp)
 
             top_hyp = B[i].get_most_probable(length_norm=True)
-            matched, matched_state = context_graph.is_matched(top_hyp.context_state)
+            matched, matched_state = keywords_graph.is_matched(top_hyp.context_state)
             if matched:
                 ac_prob = (
                     sum(top_hyp.ac_probs[-matched_state.level :]) / matched_state.level
@@ -1164,7 +1164,7 @@ def keywords_search(
                     Hypothesis(
                         ys=[-1] * (context_size - 1) + [blank_id],
                         log_prob=torch.zeros(1, dtype=torch.float32, device=device),
-                        context_state=context_graph.root,
+                        context_state=keywords_graph.root,
                         timestamp=[],
                         ac_probs=[],
                     )
@@ -1174,7 +1174,7 @@ def keywords_search(
 
     for i, hyps in enumerate(B):
         top_hyp = hyps.get_most_probable(length_norm=True)
-        matched, matched_state = context_graph.is_matched(top_hyp.context_state)
+        matched, matched_state = keywords_graph.is_matched(top_hyp.context_state)
         if matched:
             ac_prob = (
                 sum(top_hyp.ac_probs[-matched_state.level :]) / matched_state.level

egs/wenetspeech/ASR/prepare.sh

@@ -376,5 +376,6 @@ if [ $stage -le 22 ] && [ $stop_stage -ge 22 ]; then
         --token-type $token \
         --lang-dir $lang_dir
     fi
+    python ./local/compile_lg.py --lang-dir $lang_dir
   done
 fi

egs/wenetspeech/KWS/prepare.sh

@@ -22,63 +22,69 @@ log() {
 }
 
 if [ $stage -le 0 ] && [ $stop_stage -ge 0 ]; then
-  log "Stage 0: Prepare gigaspeech dataset."
+  log "Stage 0: Prepare wewetspeech dataset."
   mkdir -p data/fbank
-  if [ ! -e data/fbank/.gigaspeech.done ]; then
+  if [ ! -e data/fbank/.wewetspeech.done ]; then
     pushd ../ASR
-    ./prepare.sh --stage 0 --stop-stage 9
-    ./prepare.sh --stage 11 --stop-stage 11
+    ./prepare.sh --stage 0 --stop-stage 17
+    ./prepare.sh --stage 22 --stop-stage 22
     popd
     pushd data/fbank
-    ln -svf $(realpath ../ASR/data/fbank/gigaspeech_cuts_DEV.jsonl.gz) .
-    ln -svf $(realpath ../ASR/data/fbank/gigaspeech_feats_DEV.lca) .
-    ln -svf $(realpath ../ASR/data/fbank/gigaspeech_cuts_TEST.jsonl.gz) .
-    ln -svf $(realpath ../ASR/data/fbank/gigaspeech_feats_TEST.lca) .
-    ln -svf $(realpath ../ASR/data/fbank/gigaspeech_cuts_L.jsonl.gz) .
-    ln -svf $(realpath ../ASR/data/fbank/gigaspeech_feats_L.lca) .
-    ln -svf $(realpath ../ASR/data/fbank/gigaspeech_cuts_M.jsonl.gz) .
-    ln -svf $(realpath ../ASR/data/fbank/gigaspeech_feats_M.lca) .
-    ln -svf $(realpath ../ASR/data/fbank/gigaspeech_cuts_S.jsonl.gz) .
-    ln -svf $(realpath ../ASR/data/fbank/gigaspeech_feats_S.lca) .
-    ln -svf $(realpath ../ASR/data/fbank/gigaspeech_cuts_XS.jsonl.gz) .
-    ln -svf $(realpath ../ASR/data/fbank/gigaspeech_feats_XS.lca) .
-    ln -svf $(realpath ../ASR/data/fbank/XL_split) .
+    ln -svf $(realpath ../ASR/data/fbank/cuts_DEV.jsonl.gz) .
+    ln -svf $(realpath ../ASR/data/fbank/feats_DEV.lca) .
+    ln -svf $(realpath ../ASR/data/fbank/cuts_TEST_NET.jsonl.gz) .
+    ln -svf $(realpath ../ASR/data/fbank/feats_TEST_NET.lca) .
+    ln -svf $(realpath ../ASR/data/fbank/cuts_TEST_MEETING.jsonl.gz) .
+    ln -svf $(realpath ../ASR/data/fbank/feats_TEST_MEETING.lca) .
+    ln -svf $(realpath ../ASR/data/fbank/cuts_L.jsonl.gz) .
+    ln -svf $(realpath ../ASR/data/fbank/L_split_1000) .
+    ln -svf $(realpath ../ASR/data/fbank/cuts_M.jsonl.gz) .
+    ln -svf $(realpath ../ASR/data/fbank/M_split_1000) .
+    ln -svf $(realpath ../ASR/data/fbank/cuts_S.jsonl.gz) .
+    ln -svf $(realpath ../ASR/data/fbank/S_split_1000) .
     ln -svf $(realpath ../ASR/data/fbank/musan_cuts.jsonl.gz) .
     ln -svf $(realpath ../ASR/data/fbank/musan_feats) .
     popd
     pushd data
-    ln -svf $(realpath ../ASR/data/lang_bpe_500) .
+    ln -svf $(realpath ../ASR/data/lang_partial_tone) .
     popd
+    touch data/fbank/.wewetspeech.done
   else
-    log "Gigaspeech dataset already exists, skipping."
+    log "WenetSpeech dataset already exists, skipping."
   fi
 fi
 
 if [ $stage -le 1 ] && [ $stop_stage -ge 1 ]; then
   log "Stage 1: Prepare open commands dataset."
   mkdir -p data/fbank
-  if [ ! -e data/fbank/.fluent_speech_commands.done ]; then
+  if [ ! -e data/fbank/.cn_speech_commands.done ]; then
     pushd data
     git clone https://github.com/pkufool/open-commands.git
-    ln -svf $(realpath ./open-commands/EN/small/commands.txt) commands_small.txt
-    ln -svf $(realpath ./open-commands/EN/large/commands.txt) commands_large.txt
+    ln -svf $(realpath ./open-commands/CN/small/commands.txt) commands_small.txt
+    ln -svf $(realpath ./open-commands/CN/large/commands.txt) commands_large.txt
     pushd open-commands
-    ./script/prepare.sh --stage 3 --stop-stage 3 
-    ./script/prepare.sh --stage 6 --stop-stage 6
+    ./script/prepare.sh --stage 1 --stop-stage 1
+    ./script/prepare.sh --stage 3 --stop-stage 5
     popd
     popd
     pushd data/fbank
-    ln -svf $(realpath ../open-commands/data/fbank/fluent_speech_commands_cuts_large.jsonl.gz) .
-    ln -svf $(realpath ../open-commands/data/fbank/fluent_speech_commands_feats_large) .
-    ln -svf $(realpath ../open-commands/data/fbank/fluent_speech_commands_cuts_small.jsonl.gz) .
-    ln -svf $(realpath ../open-commands/data/fbank/fluent_speech_commands_feats_small) .
-    ln -svf $(realpath ../open-commands/data/fbank/fluent_speech_commands_cuts_valid.jsonl.gz) .
-    ln -svf $(realpath ../open-commands/data/fbank/fluent_speech_commands_feats_valid) .
-    ln -svf $(realpath ../open-commands/data/fbank/fluent_speech_commands_cuts_train.jsonl.gz) .
-    ln -svf $(realpath ../open-commands/data/fbank/fluent_speech_commands_feats_train) .
+    ln -svf $(realpath ../open-commands/data/fbank/cn_speech_commands_cuts_large.jsonl.gz) .
+    ln -svf $(realpath ../open-commands/data/fbank/cn_speech_commands_feats_large) .
+    ln -svf $(realpath ../open-commands/data/fbank/cn_speech_commands_cuts_small.jsonl.gz) .
+    ln -svf $(realpath ../open-commands/data/fbank/cn_speech_commands_feats_small) .
+    ln -svf $(realpath ../open-commands/data/fbank/nihaowenwen_cuts_dev.jsonl.gz) .
+    ln -svf $(realpath ../open-commands/data/fbank/nihaowenwen_feats_dev) .
+    ln -svf $(realpath ../open-commands/data/fbank/nihaowenwen_cuts_test.jsonl.gz) .
+    ln -svf $(realpath ../open-commands/data/fbank/nihaowenwen_feats_test) .
+    ln -svf $(realpath ../open-commands/data/fbank/nihaowenwen_cuts_train.jsonl.gz) .
+    ln -svf $(realpath ../open-commands/data/fbank/nihaowenwen_feats_train) .
+    ln -svf $(realpath ../open-commands/data/fbank/xiaoyun_cuts_clean.jsonl.gz) .
+    ln -svf $(realpath ../open-commands/data/fbank/xiaoyun_feats_clean.lca) .
+    ln -svf $(realpath ../open-commands/data/fbank/xiaoyun_cuts_noisy.jsonl.gz) .
+    ln -svf $(realpath ../open-commands/data/fbank/xiaoyun_feats_noisy.lca) .
     popd
-    touch data/fbank/.fluent_speech_commands.done
+    touch data/fbank/.cn_speech_commands.done
   else
-    log "Fluent speech commands dataset already exists, skipping."
+    log "CN speech commands dataset already exists, skipping."
   fi
 fi

egs/wenetspeech/KWS/run.sh

@@ -37,7 +37,7 @@ fi
 
 if [ $stage -le 0 ] && [ $stop_stage -ge 0 ]; then
   log "Stage 0: Train a model."
-  if [ ! -e data/fbank/.gigaspeech.done ]; then
+  if [ ! -e data/fbank/.wenetspeech.done ]; then
     log "You need to run the prepare.sh first."
     exit -1
   fi

egs/wenetspeech/KWS/zipformer/decode-asr.py

@@ -19,38 +19,7 @@
 # limitations under the License.
 """
 Usage:
-(1) greedy search
-./zipformer/decode.py \
-    --epoch 35 \
-    --avg 15 \
-    --exp-dir ./zipformer/exp \
-    --lang-dir data/lang_char \
-    --max-duration 600 \
-    --decoding-method greedy_search
-
-(2) modified beam search
-./zipformer/decode.py \
-    --epoch 35 \
-    --avg 15 \
-    --exp-dir ./zipformer/exp \
-    --lang-dir data/lang_char \
-    --max-duration 600 \
-    --decoding-method modified_beam_search \
-    --beam-size 4
-
-(3) fast beam search (trivial_graph)
-./zipformer/decode.py \
-    --epoch 35 \
-    --avg 15 \
-    --exp-dir ./zipformer/exp \
-    --lang-dir data/lang_char \
-    --max-duration 600 \
-    --decoding-method fast_beam_search \
-    --beam 20.0 \
-    --max-contexts 8 \
-    --max-states 64
-
-(4) fast beam search (LG)
+(1) fast beam search (LG)
 ./zipformer/decode.py \
     --epoch 30 \
     --avg 15 \
@@ -61,20 +30,6 @@
     --beam 20.0 \
     --max-contexts 8 \
     --max-states 64
-
-(5) fast beam search (nbest oracle WER)
-./zipformer/decode.py \
-    --epoch 35 \
-    --avg 15 \
-    --exp-dir ./zipformer/exp \
-    --lang-dir data/lang_char \
-    --max-duration 600 \
-    --decoding-method fast_beam_search_nbest_oracle \
-    --beam 20.0 \
-    --max-contexts 8 \
-    --max-states 64 \
-    --num-paths 200 \
-    --nbest-scale 0.5
 """