Add parse_key in set_ids_from_data

TTS/tts/utils/languages.py

@@ -69,10 +69,10 @@ class LanguageManager(BaseIDManager):
         self.ids = self.parse_language_ids_from_config(c)
 
     @staticmethod
-    def parse_ids_from_data(items: list) -> Any:
+    def parse_ids_from_data(items: List, parse_key: str) -> Any:
         raise NotImplementedError
 
-    def set_ids_from_data(self, items: List) -> Any:
+    def set_ids_from_data(self, items: List, parse_key: str) -> Any:
         raise NotImplementedError
 
     def save_ids_to_file(self, file_path: str) -> None:

TTS/tts/utils/managers.py

@@ -1,6 +1,6 @@
 import json
 import random
-from typing import Any, Dict, List, Union
+from typing import Any, Dict, List, Tuple, Union
 
 import fsspec
 import numpy as np
@@ -34,14 +34,13 @@ class BaseIDManager:
         with fsspec.open(json_file_path, "w") as f:
             json.dump(data, f, indent=4)
 
-
-    def set_ids_from_data(self, items: List) -> None:
+    def set_ids_from_data(self, items: List, parse_key: str) -> None:
         """Set IDs from data samples.
 
         Args:
             items (List): Data sampled returned by `load_tts_samples()`.
         """
-        self.ids, _ = self.parse_ids_from_data(items)
+        self.ids = self.parse_ids_from_data(items, parse_key=parse_key)
 
     def load_ids_from_file(self, file_path: str) -> None:
         """Set IDs from a file.
@@ -73,9 +72,18 @@ class BaseIDManager:
         return None
 
     @staticmethod
-    def parse_ids_from_data(items: list) -> Any:
-        raise NotImplementedError
+    def parse_ids_from_data(items: List, parse_key: str) -> Tuple[Dict]:
+        """Parse IDs from data samples retured by `load_tts_samples()`.
 
+        Args:
+            items (list): Data sampled returned by `load_tts_samples()`.
+            parse_key (str): The key to being used to parse the data.
+        Returns:
+            Tuple[Dict]: speaker IDs.
+        """
+        classes = sorted({item[parse_key] for item in items})
+        ids = {name: i for i, name in enumerate(classes)}
+        return ids
 
 class EmbeddingManager(BaseIDManager):
     """ Base `Embedding` Manager class. Every new `Embedding` manager must inherit this.
@@ -273,7 +281,3 @@ class EmbeddingManager(BaseIDManager):
         if self.use_cuda:
             feats = feats.cuda()
         return self.encoder.compute_embedding(feats)
-
-    @staticmethod
-    def parse_ids_from_data(items: list) -> Any:
-        raise NotImplementedError

TTS/tts/utils/speakers.py

@@ -1,6 +1,6 @@
 import json
 import os
-from typing import Any, Dict, List, Tuple, Union
+from typing import Any, Dict, List, Union
 
 import fsspec
 import numpy as np
@@ -68,7 +68,7 @@ class SpeakerManager(EmbeddingManager):
             )
 
         if data_items:
-            self.ids, _ = self.parse_ids_from_data(data_items)
+            self.set_ids_from_data(data_items, parse_key="speaker_name")
 
     @property
     def num_speakers(self):
@@ -78,21 +78,6 @@ class SpeakerManager(EmbeddingManager):
     def speaker_names(self):
         return list(self.ids.keys())
 
-    @staticmethod
-    def parse_ids_from_data(items: list) -> Tuple[Dict, int]:
-        """Parse speaker IDs from data samples retured by `load_tts_samples()`.
-
-        Args:
-            items (list): Data sampled returned by `load_tts_samples()`.
-
-        Returns:
-            Tuple[Dict, int]: speaker IDs and number of speakers.
-        """
-        speakers = sorted({item["speaker_name"] for item in items})
-        speaker_ids = {name: i for i, name in enumerate(speakers)}
-        num_speakers = len(speaker_ids)
-        return speaker_ids, num_speakers
-
     def get_speakers(self) -> List:
         return self.ids
 
@@ -180,7 +165,7 @@ def get_speaker_manager(c: Coqpit, data: List = None, restore_path: str = None,
     speaker_manager = SpeakerManager()
     if c.use_speaker_embedding:
         if data is not None:
-            speaker_manager.set_ids_from_data(data)
+            speaker_manager.set_ids_from_data(data, parse_key="speaker_name")
         if restore_path:
             speakers_file = _set_file_path(restore_path)
             # restoring speaker manager from a previous run.

recipes/multilingual/vits_tts/train_vits_tts.py

@@ -115,7 +115,7 @@ train_samples, eval_samples = load_tts_samples(dataset_config, eval_split=True)
 # init speaker manager for multi-speaker training
 # it maps speaker-id to speaker-name in the model and data-loader
 speaker_manager = SpeakerManager()
-speaker_manager.set_ids_from_data(train_samples + eval_samples)
+speaker_manager.set_ids_from_data(train_samples + eval_samples, parse_key="speaker_name")
 config.model_args.num_speakers = speaker_manager.num_speakers
 
 language_manager = LanguageManager(config=config)

recipes/vctk/fast_pitch/train_fast_pitch.py

@@ -76,7 +76,7 @@ train_samples, eval_samples = load_tts_samples(dataset_config, eval_split=True)
 # init speaker manager for multi-speaker training
 # it maps speaker-id to speaker-name in the model and data-loader
 speaker_manager = SpeakerManager()
-speaker_manager.set_ids_from_data(train_samples + eval_samples)
+speaker_manager.set_ids_from_data(train_samples + eval_samples, parse_key="speaker_name")
 config.model_args.num_speakers = speaker_manager.num_speakers
 
 # init model

recipes/vctk/fast_speech/train_fast_speech.py

@@ -74,7 +74,7 @@ train_samples, eval_samples = load_tts_samples(dataset_config, eval_split=True)
 # init speaker manager for multi-speaker training
 # it maps speaker-id to speaker-name in the model and data-loader
 speaker_manager = SpeakerManager()
-speaker_manager.set_ids_from_data(train_samples + eval_samples)
+speaker_manager.set_ids_from_data(train_samples + eval_samples, parse_key="speaker_name")
 config.model_args.num_speakers = speaker_manager.num_speakers
 
 # init model

recipes/vctk/glow_tts/train_glow_tts.py

@@ -74,7 +74,7 @@ train_samples, eval_samples = load_tts_samples(dataset_config, eval_split=True)
 # init speaker manager for multi-speaker training
 # it maps speaker-id to speaker-name in the model and data-loader
 speaker_manager = SpeakerManager()
-speaker_manager.set_ids_from_data(train_samples + eval_samples)
+speaker_manager.set_ids_from_data(train_samples + eval_samples, parse_key="speaker_name")
 config.num_speakers = speaker_manager.num_speakers
 
 # init model

recipes/vctk/speedy_speech/train_speedy_speech.py

@@ -74,7 +74,7 @@ train_samples, eval_samples = load_tts_samples(dataset_config, eval_split=True)
 # init speaker manager for multi-speaker training
 # it maps speaker-id to speaker-name in the model and data-loader
 speaker_manager = SpeakerManager()
-speaker_manager.set_ids_from_data(train_samples + eval_samples)
+speaker_manager.set_ids_from_data(train_samples + eval_samples, parse_key="speaker_name")
 config.model_args.num_speakers = speaker_manager.num_speakers
 
 # init model

recipes/vctk/tacotron-DDC/train_tacotron-DDC.py

@@ -77,7 +77,7 @@ train_samples, eval_samples = load_tts_samples(dataset_config, eval_split=True)
 # init speaker manager for multi-speaker training
 # it mainly handles speaker-id to speaker-name for the model and the data-loader
 speaker_manager = SpeakerManager()
-speaker_manager.set_ids_from_data(train_samples + eval_samples)
+speaker_manager.set_ids_from_data(train_samples + eval_samples, parse_key="speaker_name")
 
 # init model
 model = Tacotron(config, ap, tokenizer, speaker_manager)

recipes/vctk/tacotron2-DDC/train_tacotron2-ddc.py

@@ -83,7 +83,7 @@ train_samples, eval_samples = load_tts_samples(dataset_config, eval_split=True)
 # init speaker manager for multi-speaker training
 # it mainly handles speaker-id to speaker-name for the model and the data-loader
 speaker_manager = SpeakerManager()
-speaker_manager.set_ids_from_data(train_samples + eval_samples)
+speaker_manager.set_ids_from_data(train_samples + eval_samples, parse_key="speaker_name")
 
 # init model
 model = Tacotron2(config, ap, tokenizer, speaker_manager)

recipes/vctk/tacotron2/train_tacotron2.py

@@ -83,7 +83,7 @@ train_samples, eval_samples = load_tts_samples(dataset_config, eval_split=True)
 # init speaker manager for multi-speaker training
 # it mainly handles speaker-id to speaker-name for the model and the data-loader
 speaker_manager = SpeakerManager()
-speaker_manager.set_ids_from_data(train_samples + eval_samples)
+speaker_manager.set_ids_from_data(train_samples + eval_samples, parse_key="speaker_name")
 
 # init model
 model = Tacotron2(config, ap, tokenizer, speaker_manager)

recipes/vctk/vits/train_vits.py

@@ -84,7 +84,7 @@ train_samples, eval_samples = load_tts_samples(dataset_config, eval_split=True)
 # init speaker manager for multi-speaker training
 # it maps speaker-id to speaker-name in the model and data-loader
 speaker_manager = SpeakerManager()
-speaker_manager.set_ids_from_data(train_samples + eval_samples)
+speaker_manager.set_ids_from_data(train_samples + eval_samples, parse_key="speaker_name")
 config.model_args.num_speakers = speaker_manager.num_speakers
 
 # init model