allows dictionary files w/o the counts column; rename task's

--max-num-expansions-per-step to
--transducer-max-num-expansions-per-step (same as generation's) and its default is 20; prints out word counts
after WER evaluation; fixes decoding log write out

espresso/speech_recognize.py

@@ -64,6 +64,7 @@ def _main(cfg, output_file):
         datefmt="%Y-%m-%d %H:%M:%S",
         level=os.environ.get("LOGLEVEL", "INFO").upper(),
         stream=output_file,
+        force=True,
     )
     logger = logging.getLogger("espresso.speech_recognize")
     if output_file is not sys.stdout:  # also print to stdout
@@ -359,8 +360,8 @@ def decode_fn(x):
         with open(
             os.path.join(cfg.common_eval.results_path, fn), "w", encoding="utf-8"
         ) as f:
-            res = "WER={:.2f}%, Sub={:.2f}%, Ins={:.2f}%, Del={:.2f}%".format(
-                *(scorer.wer())
+            res = "WER={:.2f}%, Sub={:.2f}%, Ins={:.2f}%, Del={:.2f}%, #words={:d}".format(
+                *(scorer.wer()), scorer.tot_word_count()
             )
             logger.info(header + res)
             f.write(res + "\n")
@@ -370,8 +371,8 @@ def decode_fn(x):
         with open(
             os.path.join(cfg.common_eval.results_path, fn), "w", encoding="utf-8"
         ) as f:
-            res = "CER={:.2f}%, Sub={:.2f}%, Ins={:.2f}%, Del={:.2f}%".format(
-                *(scorer.cer())
+            res = "CER={:.2f}%, Sub={:.2f}%, Ins={:.2f}%, Del={:.2f}%, #chars={:d}".format(
+                *(scorer.cer()), scorer.tot_char_count()
             )
             logger.info(" " * len(header) + res)
             f.write(res + "\n")

espresso/tasks/speech_recognition.py

@@ -7,6 +7,7 @@
 import json
 import logging
 import os
+import tempfile
 from argparse import Namespace
 from collections import OrderedDict
 from dataclasses import dataclass, field
@@ -84,11 +85,11 @@ class SpeechRecognitionEspressoConfig(FairseqDataclass):
             "moving EOS to the beginning of that) as input feeding"
         },
     )
-    max_num_expansions_per_step: int = field(
-        default=2,
+    transducer_max_num_expansions_per_step: int = field(
+        default=II("generation.transducer_max_num_expansions_per_step"),
         metadata={
             "help": "the maximum number of non-blank expansions in a single "
-            "time step of decoding; only relavant when training with transducer loss"
+            "time step of decoding in validation; only relavant when training with transducer loss"
         },
     )
     specaugment_config: Optional[str] = field(
@@ -340,6 +341,7 @@ def setup_task(cls, cfg: SpeechRecognitionEspressoConfig, **kwargs):
         """
         # load dictionaries
         dict_path = os.path.join(cfg.data, "dict.txt") if cfg.dict is None else cfg.dict
+        dict_path = cls._maybe_add_pseudo_counts_to_dict(dict_path)
         enable_blank = (
             True if cfg.criterion_name in ["transducer_loss", "ctc_loss"] else False
         )
@@ -376,13 +378,39 @@ def setup_task(cls, cfg: SpeechRecognitionEspressoConfig, **kwargs):
             feat_dim = src_dataset.feat_dim
 
         if cfg.word_dict is not None:
-            word_dict = cls.load_dictionary(cfg.word_dict, enable_bos=False)
+            word_dict_path = cfg.word_dict
+            word_dict_path = cls._maybe_add_pseudo_counts_to_dict(word_dict_path)
+            word_dict = cls.load_dictionary(word_dict_path, enable_bos=False)
             logger.info("word dictionary: {} types".format(len(word_dict)))
             return cls(cfg, tgt_dict, feat_dim, word_dict=word_dict)
 
         else:
             return cls(cfg, tgt_dict, feat_dim)
 
+    @classmethod
+    def _maybe_add_pseudo_counts_to_dict(cls, dict_path):
+        with open(dict_path, "r", encoding="utf-8") as f:
+            split_list = f.readline().rstrip().rsplit(" ", 1)
+            if len(split_list) == 2:
+                try:
+                    int(split_list[1])
+                    return dict_path
+                except ValueError:
+                    pass
+        logger.info(f"No counts detected in {dict_path}. Adding pseudo counts...")
+        with open(dict_path, "r", encoding="utf-8") as fin, tempfile.NamedTemporaryFile(
+            "w", encoding="utf-8", delete=False
+        ) as fout:
+            for i, line in enumerate(fin):
+                line = line.rstrip()
+                if len(line) == 0:
+                    logger.warning(
+                        f"Empty at line {i+1} in the dictionary {dict_path}, skipping it"
+                    )
+                    continue
+                print(line + " 1", file=fout)
+            return fout.name
+
     def load_dataset(
         self,
         split: str,
@@ -457,7 +485,7 @@ def build_model(self, cfg: DictConfig, from_checkpoint=False):
             self.decoder_for_validation = TransducerGreedyDecoder(
                 [model],
                 self.target_dictionary,
-                max_num_expansions_per_step=self.cfg.max_num_expansions_per_step,
+                max_num_expansions_per_step=self.cfg.transducer_max_num_expansions_per_step,
                 bos=(
                     self.target_dictionary.bos()
                     if self.cfg.include_eos_in_transducer_loss
@@ -528,7 +556,7 @@ def build_generator(
                 beam_size=getattr(args, "beam", 1),
                 normalize_scores=(not getattr(args, "unnormalized", False)),
                 max_num_expansions_per_step=getattr(
-                    args, "transducer_max_num_expansions_per_step", 2
+                    args, "transducer_max_num_expansions_per_step", 20
                 ),
                 expansion_beta=getattr(args, "transducer_expansion_beta", 0),
                 expansion_gamma=getattr(args, "transducer_expansion_gamma", None),

examples/asr_librispeech/run_transformer_transducer.sh

@@ -261,6 +261,7 @@ if [ ${stage} -le 8 ]; then
       --num-shards 1 --shard-id 0 --dict $dict --bpe sentencepiece --sentencepiece-model ${sentencepiece_model}.model \
       --gen-subset $dataset --max-source-positions 9999 --max-target-positions 999 \
       --path $path --beam 5 --temperature 1.3 --criterion-name transducer_loss \
+      --transducer-max-num-expansions-per-step 20 \
       --transducer-expansion-beta 2 --transducer-expansion-gamma 2.3 --transducer-prefix-alpha 1 \
       --results-path $decode_dir $opts
 

fairseq/dataclass/configs.py

@@ -1051,7 +1051,7 @@ class GenerationConfig(FairseqDataclass):
     )
     # for decoding transducer models
     transducer_max_num_expansions_per_step: Optional[int] = field(
-        default=2,
+        default=20,
         metadata={
             "help": "the maximum number of non-blank expansions in a single time step"
         },