utt datapipeline

deepspeech/exps/deepspeech2/model.py

@@ -75,7 +75,7 @@ class DeepSpeech2Trainer(Trainer):
         for i, batch in enumerate(self.valid_loader):
             loss = self.model(*batch)
             if paddle.isfinite(loss):
-                num_utts = batch[0].shape[0]
+                num_utts = batch[1].shape[0]
                 num_seen_utts += num_utts
                 total_loss += float(loss) * num_utts
                 valid_losses['val_loss'].append(float(loss))
@@ -191,7 +191,7 @@ class DeepSpeech2Tester(DeepSpeech2Trainer):
             trans.append(''.join([chr(i) for i in ids]))
         return trans
 
-    def compute_metrics(self, audio, audio_len, texts, texts_len):
+    def compute_metrics(self, utt, audio, audio_len, texts, texts_len):
         cfg = self.config.decoding
         errors_sum, len_refs, num_ins = 0.0, 0, 0
         errors_func = error_rate.char_errors if cfg.error_rate_type == 'cer' else error_rate.word_errors

deepspeech/io/collator.py

@@ -51,7 +51,7 @@ class SpeechCollator():
         audio_lens = []
         texts = []
         text_lens = []
-        for audio, text in batch:
+        for utt, audio, text in batch:
             # audio
             audios.append(audio.T)  # [T, D]
             audio_lens.append(audio.shape[1])
@@ -75,4 +75,4 @@ class SpeechCollator():
         padded_texts = pad_sequence(
             texts, padding_value=IGNORE_ID).astype(np.int64)
         text_lens = np.array(text_lens).astype(np.int64)
-        return padded_audios, audio_lens, padded_texts, text_lens
+        return utt, padded_audios, audio_lens, padded_texts, text_lens

deepspeech/io/dataset.py

@@ -284,7 +284,7 @@ class ManifestDataset(Dataset):
         return self._local_data.tar2object[tarpath].extractfile(
             self._local_data.tar2info[tarpath][filename])
 
-    def process_utterance(self, audio_file, transcript):
+    def process_utterance(self, utt, audio_file, transcript):
         """Load, augment, featurize and normalize for speech data.
 
         :param audio_file: Filepath or file object of audio file.
@@ -323,7 +323,7 @@ class ManifestDataset(Dataset):
         specgram = self._augmentation_pipeline.transform_feature(specgram)
         feature_aug_time = time.time() - start_time
         #logger.debug(f"audio feature augmentation time: {feature_aug_time}")
-        return specgram, transcript_part
+        return utt, specgram, transcript_part
 
     def _instance_reader_creator(self, manifest):
         """
@@ -336,7 +336,9 @@ class ManifestDataset(Dataset):
 
         def reader():
             for instance in manifest:
-                inst = self.process_utterance(instance["feat"],
+                # inst = self.process_utterance(instance["feat"],
+                #                               instance["text"])
+                inst = self.process_utterance(instance["utt"], instance["feat"],
                                               instance["text"])
                 yield inst
 
@@ -347,4 +349,6 @@ class ManifestDataset(Dataset):
 
     def __getitem__(self, idx):
         instance = self._manifest[idx]
-        return self.process_utterance(instance["feat"], instance["text"])
+        return self.process_utterance(instance["utt"], instance["feat"],
+                                      instance["text"])
+        # return self.process_utterance(instance["feat"], instance["text"])

deepspeech/models/deepspeech2.py

@@ -161,7 +161,7 @@ class DeepSpeech2Model(nn.Layer):
             reduction=True,  # sum
             batch_average=True)  # sum / batch_size
 
-    def forward(self, audio, audio_len, text, text_len):
+    def forward(self, utt, audio, audio_len, text, text_len):
         """Compute Model loss
 
         Args:

examples/chinese_g2p/local/ignore_sandhi.py

@@ -12,8 +12,9 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 import argparse
-from typing import List, Union
 from pathlib import Path
+from typing import List
+from typing import Union
 
 
 def erized(syllable: str) -> bool:
@@ -67,7 +68,9 @@ def ignore_sandhi(reference: List[str], generated: List[str]) -> List[str]:
     return result
 
 
-def convert_transcriptions(reference: Union[str, Path], generated: Union[str, Path], output: Union[str, Path]):
+def convert_transcriptions(reference: Union[str, Path],
+                           generated: Union[str, Path],
+                           output: Union[str, Path]):
     with open(reference, 'rt') as f_ref:
         with open(generated, 'rt') as f_gen:
             with open(output, 'wt') as f_out:

examples/dataset/librispeech/.gitignore

-dev-clean/
-dev-other/
-test-clean/
-test-other/
-train-clean-100/
-train-clean-360/
-train-other-500/
+dev-clean
+dev-other
+test-clean
+test-other
+train-clean-100
+train-clean-360
+train-other-500

examples/librispeech/s0/README.md

@@ -3,7 +3,7 @@
 ## Deepspeech2
 
 | Model | release |  Config | Test set | Loss | WER |  
-| --- | --- |  --- | --- | --- | --- |   
+| --- | --- |  --- | --- | --- | --- |  
 | DeepSpeech2 | 2.1.0 | conf/deepspeech2.yaml | 15.184467315673828 | test-clean | 0.072154 |  
 | DeepSpeech2 | 2.0.0 | conf/deepspeech2.yaml | - | test-clean | 0.073973 |  
 | DeepSpeech2 | 1.8.5 | - | test-clean | - | 0.074939 |  

examples/tiny/s0/run.sh

@@ -11,7 +11,7 @@ avg_num=1
 source ${MAIN_ROOT}/utils/parse_options.sh || exit 1;
 
 avg_ckpt=avg_${avg_num}
-ckpt=$(basename ${conf_path} | awk -F'.' '{print $1}')
+ckpt=$(basename ${conf_path} | awk -F'.' '{print $1}') ###ckpt = deepspeech2
 echo "checkpoint name ${ckpt}"
 
 if [ ${stage} -le 0 ] && [ ${stop_stage} -ge 0 ]; then